Data Management

How to Optimize Data in Any Environment

Actian Corporation

February 15, 2024

Data Optimization

New demands, supply chain complexity, truly understanding customers, and other challenges have upended the traditional business landscape and forced organizations to rethink their strategies and how they’re using data. Organizations that are truly data-driven have opportunities to gain new market share and grow their competitive advantage with proper data management. Those that don’t will continue to struggle—and in a worst-case scenario, may not be able to keep their doors open.

Data Management is Needed to Drive and Support Use Cases

As organizations face the threat of a recession, geopolitical instability, concerns about inflation, and uncertainty about the economy, they look to data for answers. Data has emerged as a critical asset for any organization striving to intelligently grow their business, avoid costly problems, and position themselves for the future.

As explained in the webinar “Using Data in a Downturn: Building Business Resiliency with Analytics,” successful organizations optimize their data to be proactive in changing markets. The webinar, featuring William McKnight from McKnight Consulting Group, notes that data is needed for a vast range of business uses, such as:

  • Gaining a competitive advantage.
  • Increasing market share.
  • Developing new products and services.
  • Entering new markets.
  • Increasing brand recognition and customer loyalty.
  • Improving efficiency.
  • Enhancing customer service.
  • Developing new technologies.

McKnight says that when it comes to prioritizing data efforts, you should focus on projects that are easy to do with your current technology set and skill set, those that align with your business priorities, and ones that offer a high return on investment (ROI).

Justifying Data and Analytics Projects During a Downturn

The webinar explains why data and analytics projects are needed during an economic downturn. “Trusted knowledge of an accurate future is undoubtedly the most useful knowledge to have,” McKnight points out. Data and analytics predict that future, giving you the ability to position your company for what’s ahead.

Economic conditions and industry trends can change quickly, which means you need trustworthy data to inform the analytics. When this happens, you can uncover emerging opportunities such as products or features your customers will want or identify areas of risk with enough time to take action.

McKnight explains in the webinar that a higher degree of accuracy in determining your future can have a significant impact on your bottom line. “If you know what’s going to happen, you can either like it and leave it, or you can say, ‘I don’t like that, and here’s what I need to do to tune it,’ and that’s the essence of analytics,” he says.

Applying Data Management and Customer Analytics to Achieve High-Value Results

Not surprisingly, the more data you make available for analytics, the more precise your analytics will be. As the webinar explains, artificial intelligence (AI) can help with insights. AI enhances analytics, provided the AI has the robust and quality data sets needed to deliver accurate and actionable results. The right approach to data and analytics can help you determine the next best step you can take for your business.

You can also use the insights to drive business value, such as creating loyal customers and repeat buyers, and proactively adjusting your supply chain to stay ahead of changing conditions. McKnight says in the webinar that leading companies are using data management and customer analytics to drive ROI in a myriad of ways, such as optimizing:

  • Product placement in stores.
  • Product recommendations.
  • Content recommendations.
  • Product design and offerings.
  • Menu items in restaurants.

All of these efforts increase sales. Likewise, using data and analytics can drive results across the supply chain. For example, you can use data to optimize inventory and ensure fast delivery times, or incorporate real-time data on customer demand, inventory levels, and transportation logistics to have products when and where they’re needed. Similarly, you can take a data-driven approach to demand forecasting, then optimize product distribution, and improve visibility across the entire supplier network.

Data Best Practices Hold True in Soft Economies

Using data to drive the business and inform decision-making is essential in any economy. During an economic downturn, you may need to shift priorities and decide what projects and initiatives to pursue, and which to pause or discontinue.

To help with these decisions, you can use your data foundation, follow data management best practices, continue to use data virtualization, and ensure you have the ability to access accurate data in real time. A modern data platform is also needed to integrate and leverage all your data.

The Actian Data Platform offers integration as a service, makes data easy to use, gives users confidence in their data, improves data quality, and more. The platform empowers you to go from data source to decision with confidence. You have the ability to better utilize data in an economic downturn, or any other market conditions.

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About Actian Corporation

Actian empowers enterprises to confidently manage and govern data at scale. Actian data intelligence solutions help streamline complex data environments and accelerate the delivery of AI-ready data. Designed to be flexible, Actian solutions integrate seamlessly and perform reliably across on-premises, cloud, and hybrid environments. Learn more about Actian, the data division of HCLSoftware, at actian.com.

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Data Management

Reduce the Risk of Application Modernization – Retain Business Logic

Teresa Wingfield

February 13, 2024

Risk of Application Modernization

While legacy database applications power the business operations of many organizations, they can prevent them from realizing the benefits of digital transformation. Yet organizations settle for the status quo because application modernization can be a long, expensive, and risky journey that can involve replacing thousands of lines of custom-developed business logic. OpenROAD, Actian’s solution for rapid database application development, makes it easy to modernize applications with low risk by retaining your investment in existing business logic. This blog will cover all the details of how this is possible.

Application Modernization: Rethinking Business Logic

Before delving into OpenROAD, let’s start with a brief overview of what application business logic is. Application business logic includes the set of rules, processes, and workflows that define how an application operates and how it handles data and user interactions to deliver specific business functionality. It governs how an application processes and validates data, performs calculations, manages workflows, enforces business rules, handles errors and exceptions, and generates outputs. The application business logic also defines how the application is integrated with external systems and security controls to protect data, maintain data integrity, and prevent unauthorized access.

OpenROAD and Preservation of Business Logic

When creating OpenROAD, Actian realized that applications require continuous adaptation and improvement as technology evolves, business requirements change, and new opportunities emerge over time. This is why OpenROAD’s key features and design principles focus so heavily on preserving business logic for application modernization projects as discussed below:

Model-Driven Development

OpenROAD makes it possible for developers to follow a model-driven development approach, allowing them to define the business logic of their applications using high-level models rather than low-level code. This helps to abstract away technical complexities and focus on capturing the essential business rules and processes.

Data Independence

OpenROAD provides a data abstraction layer that decouples the application’s business logic from the underlying database schema. This allows developers to define business rules and logic independently of the database structure, facilitating easier maintenance and future changes to the application.

Component-Based Architecture

OpenROAD applications are built using a component-based architecture that promotes code reuse, simplifies maintenance, and ensures consistency across the application.

Business Logic Encapsulation

Encapsulation separates the implementation details of the business logic from other parts of the application, promoting modularity, maintainability, and reusability. OpenROAD Server is a critical component of the OpenROAD platform, providing the runtime environment and infrastructure needed to deploy and execute OpenROAD applications effectively and allowing developers to encapsulate reusable business logic into modular components.

Integration Capabilities

OpenROAD provides integration capabilities that allow developers to incorporate existing business logic and functionality from other systems or applications. This enables organizations to leverage their existing investments in business logic while modernizing their applications with OpenROAD.

Version Control and Change Management

OpenROAD includes features for version control and change management, allowing developers to track and manage changes to the application’s business logic over time. This helps to preserve the integrity of the business rules and ensure that modifications are properly documented and auditable.

Modernize Your OpenROAD Applications

Your legacy database applications may be stable, but most may not meet the needs of digital business today. You don’t have to settle for the status quo. OpenROAD preserves business logic to reduce application modernization work. OpenROAD provides a flexible and scalable development platform that supports a model-driven development approach, data independence, a component-based architecture, encapsulation, integration capabilities, and version control. These features help organizations maintain and evolve their business logic effectively while developing and modernizing their applications.

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About Teresa Wingfield

Teresa Wingfield is Director of Product Marketing at Actian, driving awareness of the Actian Data Platform's integration, management, and analytics capabilities. She brings 20+ years in analytics, security, and cloud solutions marketing at industry leaders such as Cisco, McAfee, and VMware. Teresa focuses on helping customers achieve new levels of innovation and revenue with data. On the Actian blog, Teresa highlights the value of analytics-driven solutions in multiple verticals. Check her posts for real-world transformation stories.

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Data Intelligence

What are APIs?

Actian Corporation

February 13, 2024

Api Application Programming Interface. Software Development Tool. Business, Modern Technology, Internet And Networking Concept

You’ve undoubtedly heard of APIs—ubiquitous yet often misunderstood. Curious to learn everything about APIs, or Application Programming Interfaces? Let’s uncover what they do, their benefits, and how they operate.

API—three letters without which companies today couldn’t seamlessly deploy their data strategies. An Application Programming Interface is a set of rules and protocols enabling two distinct software programs to communicate. It defines the methods and data formats allowed for information exchange, facilitating the integration of different applications or services.

The concept of APIs dates back to the early days of computing. In the 2000s, with the growth of the Internet and the rise of web services, APIs gained significant importance. Companies began providing APIs to enable the integration of their services with other applications and systems. In 2020, it’s estimated that nearly 2 billion euros were invested worldwide to develop APIs.

How Does an API Work?

In the world of diplomacy, there are interpreters. In the IT universe, there are APIs. This somewhat straightforward comparison sums up the function of an API. It acts as an intermediary, receiving requests and returning structured responses. An API operates by defining endpoints accessible via HTTP requests. These endpoints represent specific functionalities of the application, and developers interact with them using standard HTTP methods such as GET, POST, PUT, and DELETE. Data is then exchanged in JSON or XML format. The API specifies necessary parameters, expected data types, and possible responses. HTTP requests contain information like headers and query bodies, allowing data transmission. Responses provide status codes to indicate success or failure, accompanied by structured data.

API documentation, usually based on specifications like Open API, describes in detail how to interact with each endpoint. Authentication tokens can be used to secure API access. In summary, an API acts as an external interface, facilitating integration and communication between different applications or services.

What are the Benefits of APIs?

Using APIs offers numerous advantages in the software and system integration realm. They simplify access to an application’s features, allowing developers to leverage external services without necessarily understanding their internal implementation. This promotes modularity and accelerates the development of interconnections between essential business solutions for your employees’ efficiency.

Furthermore, APIs facilitate integration between different applications, creating interconnected software ecosystems. The key advantage? Substantially improved operational efficiency. Updates or improvements can be made to an API without affecting the clients using it. Code reuse is encouraged, as developers can leverage existing functionalities via APIs rather than recreating similar solutions, resulting in significant cost savings and shorter development timelines that contribute to your business’s agility.

Finally, APIs offer an improved collaboration perspective between teams, as different groups can work independently using APIs as defined interfaces.

Different Types of APIs

APIs form a diverse family. Various types cater to specific needs:

Open API

Also known as an external API or public API, it is designed to be accessible to the public. Open APIs follow standards like REST or GraphQL, fostering collaboration by allowing third-party developers or other applications to access a service’s features and data in a controlled manner.

Partner API

Partner APIs, or partner-specific APIs, are dedicated to specific partners or trusted external developers. These APIs offer more restricted and secure access, often used to extend an application’s features to strategic partners without exposing all functionalities to the public.

Composite API

Behind the term Composite API lies the combination of several different API calls into a single request. The benefit? Simplifying access to multiple functionalities in a single call, reducing interaction complexity, and improving performance.

Internal API

Designed for use within an organization, this type of API facilitates communication between different parts of a system or between different internal systems. It contributes to the modularity and coherence of applications within the company.

Different API Protocols

If APIs can be compared to interpreters, the protocols they use are, in a sense, the languages that enable them to communicate. There are four protocols:

SOAP (Simple Object Access Protocol)

Using XML, SOAP is a standardized protocol that offers advanced features such as security and transaction management. However, it can be complex and require significant resources.

XML-RPC (XML Remote Procedure Call)

The primary quality of this protocol is its simplicity. Based on XML, it allows the calling of remote procedures. Although less complex than SOAP, it offers limited features and is often replaced by more modern alternatives.

REST (Representational State Transfer)

Founded on HTTP principles, REST uses standard methods like GET, POST, PUT, and DELETE to manipulate resources. It exploits the JSON data format, deriving its simplicity, scalability, and flexibility.

JSON-RPC (JavaScript Object Notation Remote Procedure Call)

Lightweight and based on JSON, JSON-RPC facilitates the calling of remote procedures. It provides a simple alternative to XML-RPC and is often used in web and mobile environments.

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About Actian Corporation

Actian empowers enterprises to confidently manage and govern data at scale. Actian data intelligence solutions help streamline complex data environments and accelerate the delivery of AI-ready data. Designed to be flexible, Actian solutions integrate seamlessly and perform reliably across on-premises, cloud, and hybrid environments. Learn more about Actian, the data division of HCLSoftware, at actian.com.
Data Intelligence

Why a Data Catalog is Essential for Data Product Management

Actian Corporation

February 12, 2024

Data Mesh is one of the hottest topics in the data space. In fact, according to a recent BARC Survey, 54% of companies are planning to implement or are implementing the Data Mesh in their companies. Implementing Data Mesh architecture in your enterprise means incorporating a domain-centric approach to data and treating data as a product. Data Product Management is, therefore, crucial in the Data Mesh transformation process. Eckerson Group Survey 2024 found that 70% of organizations have or are in the process of implementing Data Products.

However, many companies are struggling to manage, maintain, and get value out of their data products. Indeed, successful Data Product Management requires establishing the right people, processes, and technologies. One of those essential technologies is a data catalog.

In this article, discover how a data catalog empowers data product management in data-driven companies.

Quick Definition of a Data Product

In a previous article on Data Products, we detailed the definition and characteristics of Data Products. We define a Data Product as being:

“A set of value-driven data assets specifically designed and managed to be consumed quickly and securely while ensuring the highest level of quality, availability, and compliance with regulations and internal policies.”

Let’s get a refresher on the characteristics of a Data Product. According to Zhamak Dehghani, the Data Mesh guru, to deliver the best user experience for data consumers, data products need to have the following basic qualities:

  • Discoverable
  • Addressable
  • Trustworthy and truthful
  • Self-describing semantics and syntax
  • Inter-operable and governed by global standards
  • Secure and governed by a global access control

How can you ensure your sets of data meet the criteria for becoming a functional and value-driven Data Product? This is where a data catalog comes in.

What Exactly is a Data Catalog?

Many definitions exist of what a data catalog is. We define it as “A detailed inventory of all data assets in an organization and their metadata, designed to help data professionals quickly find the most appropriate data for any analytical business purpose.” Basically, a data catalog’s goal is to create a comprehensive library of all company data assets, including their origins, definitions, and relations to other data. And like a catalog for books in a library, data catalogs make it easy to search, find, and discover data.

Therefore, in an ecosystem where volumes of data are multiplying and changing by the second, it is crucial to implement a data cataloging solution – a data catalog answers the who, what, when, where, and why of your data.

But, how does this relate to data products? As mentioned in our previous paragraph, data products have fundamental characteristics that they must meet to be considered data products. Most importantly, they must be understandable, accessible, and made available for consumer use. Therefore, a data catalog is the perfect solution for creating and maintaining data products.

View our Data Catalog capabilities.

A Data Catalog Makes Data Products Discoverable

A data catalog collects, indexes, and updates data and metadata from all data sources into a unique repository. Via an intuitive search bar, data catalogs make it simple to find data products by typing simple keywords.

Our data catalog enables data users to not only find their data products but to fully discover their context, including their origin and transformations over time, their owners, and most importantly, to which other assets it is linked for a 360° data discovery. Actian Data Intelligence Platform was designed so users can always discover their data products, even if they don’t know what they are searching for. Indeed, our platform offers unique and personalized exploratory paths so users can search and find the information they need in just a few clicks.

A Data Catalog Makes Data Products Addressable

Once a data consumer has found the data product, they must be able to access it or request access to it in a simple, easy, and efficient way. Although a data catalog doesn’t play a direct role in addressability, it certainly can facilitate and automate part of the work. An automated Data Catalog solution plugs into policy enforcement solutions, accelerating data access (if the user has the appropriate permissions).

A Data Catalog Makes Data Products Trustworthy

We strongly believe that a data catalog is not a data quality tool. However, our catalog solution automatically retrieves and updates quality indicators from third-party data quality management systems. With the Actian Data Intelligence Platform, users can view their quality metrics via a user-friendly graph and instantly identify the quality checks that were performed, their quantity, and whether they passed, failed, or issued warnings. In addition, our Lineage capabilities provide statistical information on the data and reconstruct the lineage of the data product, making it easy to understand the origin and the various transformations over time. These features combined increase trust in data and ensure data users are always working with accurate data products.

A Data Catalog Makes Data Products Understandable

One of the most significant roles of a data catalog is to provide all the context necessary to understand the data. By efficiently documenting data, with both technical and business documentation, data consumers can easily comprehend the nature of their data and draw conclusions from their analyses. In the Actian Data Intelligence Platform, Data Stewards can easily create documentation templates for their Data Products and thoroughly document them, including detailed descriptions, associating Glossary Items, relationships with other Data Products, and more. By delivering a structured and transparent view of your data, the Actian Data Intelligence Platform’s data catalog promotes the autonomous use of Data Products by data consumers in the organization.

A Data Catalog Enables Data Product Interoperability

With comprehensive documentation, a data catalog facilitates data product integration across various systems and platforms. It provides a clear view of data product dependencies and relationships between different technologies, ensuring the sharing of standards across the organization. In addition, a data catalog maintains a unified metadata repository, containing standardized definitions, formats, and semantics for various data assets. Our platform is built on powerful knowledge graph technology that automatically identifies, classifies, and tracks data products based on contextual factors, mapping data assets to meet the standards defined at the enterprise level.

A Data Catalog Enables Data Product Security

A data catalog typically includes robust access control mechanisms that allow organizations to define and manage user permissions. This ensures that only authorized personnel have access to sensitive metadata, reducing the risk of unauthorized access or breaches. With the Actian Data Intelligence Platform, you create a secure data catalog, where only the right people can act on a data product’s documentation.

Start Managing Data Products in the Actian Data Intelligence Platform

Interested in learning more about how Data Product Management works in the Actian Data Intelligence Platform? Get a 30-minute personalized demo with one of our experts now.

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About Actian Corporation

Actian empowers enterprises to confidently manage and govern data at scale. Actian data intelligence solutions help streamline complex data environments and accelerate the delivery of AI-ready data. Designed to be flexible, Actian solutions integrate seamlessly and perform reliably across on-premises, cloud, and hybrid environments. Learn more about Actian, the data division of HCLSoftware, at actian.com.
Databases

Legacy Transactional Databases: Oh, What a Tangled Web

Teresa Wingfield

February 8, 2024

Transactional Database

Database modernization is increasingly needed for digital transformation, but it’s hard work. There are many reasons why; this blog will drill down on one of the main ones: legacy entanglements. Often, organizations have integrated legacy databases with business processes, the applications they run (and their dependencies), and systems such as enterprise resource planning, customer relationship management, supply chain management, human resource management, point-of-sales systems, and e-commerce. Plus, there’s middleware and integration, identify and access management, backup and recovery, replication, and other technology integrations to consider.

Your Five-Step Plan for Untangling Legacy Dependencies

So, how do you safely untangle legacy databases for database modernization in the cloud? Here’s a list of steps that you can take for greater success and a less disruptive transition.

1. Understand and Document Dependencies and Underlying Technologies

There are many activities involved in identifying legacy dependencies. A good start is to review any available database documentation for integrations, including mentions of third-party libraries, frameworks, and services that the database relies on. Code review, with the help of dependency management tools, can identify dependencies within the legacy codebase. Developers, architects, database administrators, and other team members may be able to provide additional insights into legacy dependencies.

2. Prioritize Dependencies

Prioritization is important since you can’t do everything at once. Prioritizing legacy dependencies involves assessing the importance, impact, and risk associated with each dependency in the context of a migration or modernization effort. Higher-priority dependencies should incorporate those that are critical for the database to function and that have the highest business value. When assessing business impact, include how dependencies affect revenue generation and critical business operations.

Also, consider risks, interdependencies, and migration complexity when prioritizing dependencies. For example, outdated technologies can threaten database security and stability. Database dependencies can have significant ripple effects throughout an organization’s systems and processes that require careful consideration. For example, altering a database schema during a migration can lead to application errors, malfunctions, or performance issues. Finally, some dependencies are easier to migrate or replace than others and this might impact its importance or urgency during migration.

3. Take a Phased Approach

A phased migration approach to database modernization that includes preparation, planning, execution, operation, and optimization helps organizations manage complexity, minimize risks, and ensure continuity of operations throughout the migration process. Upfront preparation and planning are necessary to ensure success. It may be beneficial to start small with low-risk or non-critical components to validate procedures and identify issues. The operating phase involves managing workloads, including performance monitoring, resource management, security, and compliance. It’s critical to optimize activities and address concerns in these areas.

4. Reduce Risks

To reduce the risks associated with dependencies, consider approaches that run legacy and modern systems in parallel and use staging environments for testing. Replication offers redundancy that can help ensure business continuity. In case unexpected issues arise, always have a rollback plan to minimize disruption.

5. Breakdown Monolithic Dependencies

Lastly, don’t recreate the same monolithic dependencies found in your legacy database so that you can get the full benefits of digital transformation. A microservices architecture can break down the legacy database into smaller, independent components that can be developed, deployed, and scaled independently. This means that changes to one part of the database don’t affect other parts, reducing the risk of system-wide failures and making the database much easier to maintain and enhance.

How Actian Can Help with Database Modernization

The Ingres NeXt Readiness Assessment offers a pre-defined set of professional services tailored to your requirements. The service is designed to assist you with understanding the requirements to modernize Ingres and Application By Forms (ABF) or OpenROAD applications and to impart recommendations important to your modernization strategy formulation, planning, and implementation.

Based on the knowledge gleaned from the Ingres NeXt Readiness Assessment, Actian can assist you with your pilot and production deployment. Actian can also facilitate a training workshop should you require preliminary training.

For more information, please contact services@actian.com.

 

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About Teresa Wingfield

Teresa Wingfield is Director of Product Marketing at Actian, driving awareness of the Actian Data Platform's integration, management, and analytics capabilities. She brings 20+ years in analytics, security, and cloud solutions marketing at industry leaders such as Cisco, McAfee, and VMware. Teresa focuses on helping customers achieve new levels of innovation and revenue with data. On the Actian blog, Teresa highlights the value of analytics-driven solutions in multiple verticals. Check her posts for real-world transformation stories.

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Data Management

Analysts Say Data Processing Across Hybrid Environments is Important

Actian Corporation

February 6, 2024

data processing with actian zen and apache kafka

Insights from Matt Aslett, VP Research Director at Ventana Research: Would you be surprised to know that by 2026, eight in 10 enterprises will have data spread across multiple cloud providers and on-premises data centers? This prediction by Ventana Research’s Matt Aslett is based, at least in part, on the trend of organizations increasingly using more than one cloud service in addition to their on-premises infrastructure.

Optimizing all of this data—regardless of where it lives—requires a modern data platform capable of accessing and managing data in hybrid environments. “As such, there is a growing requirement for cloud-agnostic data platforms, both operational and analytic, that can support data processing across hybrid IT and multi-cloud environments,” Aslett explains.

For many organizations, managing data while ensuring quality in any environment is a struggle. New data sources are constantly emerging and data volumes are growing at unprecedented rates. When you couple this with an increase in the number of data-intensive applications and analysts who need quality data, it’s easy to see why data management is more complex but more necessary than ever before.

As organizations are finding, data management and data quality problems can and will scale—challenges, silos, and inefficient data processes that exist on-premises or in one cloud will compound as you migrate across multiple clouds or hybrid infrastructures. That’s why it’s essential to fix those issues now and implement effective data management strategies that can scale with you. 

Replacing Complexity With Simplicity

Ventana research also says that traditional approaches to data processing rely on a complex and often “brittle” architecture. This type of architecture uses a variety of specialized products cobbled together from multiple vendors, which in turn require specialized skill sets to use effectively.

As additional technologies are bolted onto the architecture, processes and data sharing become even more complex. In fact, one problem we see at Actian is that organizations continue to add new data and analytics products into ecosystems that are bogged down with legacy technologies. This creates a complicated tech stack of disparate tools, programming languages, frameworks, and technologies that create barriers to integrating, managing, and sharing data.

For a company to be truly data-driven, data must be easily accessible and trusted by every analyst and data user across the enterprise. Any obstacles to tapping into new data sources or accessing quality data, such as requiring ongoing IT help, encourage data silos, and shadow IT—common problems that can lead to misinformed decision-making and will cause stakeholders to lose confidence in the data.

A modern data platform that makes data easy to access, share, and trust with 100% confidence is needed to encourage data use, automate processes, inform decisions, and feed data-intensive applications. The platform should also deliver high performance and be cost-effective to appeal to everyone from data scientists and analysts who use the data to the CFO who’s focused on the IT budget.

Manageability and Usability Are Critical Platform Capabilities

Today’s data-driven environment demands an easy-to-use cloud data platform. Choosing the best platform to meet your business and IT needs can be tricky. Recognized industry analyst research can help by identifying important platform capabilities and identifying which vendors lead in those categories.

For example, Ventana Research’s “Data Platforms Value Index” is an assessment you can use to evaluate vendors and products. One capability the assessment evaluated is product manageability, which is how well the product can be managed technologically and by the business, and how well it can be governed, secured, licensed, and supported in a service level agreement (SLA).

The assessment also looked at the usability of the product—how well it meets the various business needs of executives, management, workers, analysts, IT, and others. “The importance of usability and the digital experience in software utilization has been increasing and is evident in our market research over the last decade,” the assessment notes. “The requirements to meet a broad set of roles and responsibilities across an organization’s cohorts and personas should be a priority for all vendors.”

The Actian Data Platform ranked second for manageability and third for usability, which reflects the platform’s ease of use by making data easy to connect, manage, and analyze. These key capabilities are must-haves for data-driven companies.

Cut Prep Time While Boosting Data Quality

According to Ventana Research, 69% of organizations cite data prep as consuming the most time in analytics initiatives, followed by reviewing data for quality issues at 64%. This is consistent with what we hear from our customers

This is due to data silos, data quality concerns, IT dependency, data latency, and not knowing the steps to optimize data to intelligently grow the business. Organizations must remove these barriers to go from data to decision with confidence and ease.

The Actian Data Platform’s native data integration capabilities can help. It allows you to easily unify data from different sources to gain a comprehensive and accurate understanding of all data, allowing for better decision-making, analysis, and reporting. The platform supports any source and target data, offers elastic integration and cloud-automated scaling, and provides tools for data integration management in hybrid environments.

You benefit from codeless API and application integration, flexible design capabilities, integration templates, and the ability to customize and re-use integrations. Our integration also includes data profiling capabilities for reliable decision-making and a comprehensive library of pre-built connectors.

The platform is unique in its ability to collect, manage, and analyze data in real-time with its transactional database, data integration, data quality, and data warehouse capabilities. It manages data from any public cloud, multi- or hybrid cloud, and on-premises environments through a single pane of glass. In addition, the platform offers self-service data integration, which lowers costs and addresses multiple use cases, without needing multiple products.

As Ventana Research’s Matt Aslett noted in his analyst perspective, our platform reduces the number of tools and platforms needed to generate data insights. Streamlining tools is essential to making data easy and accessible to all users, at all skill levels. Aslett also says, “I recommend that all organizations that seek to deliver competitive advantage using data should evaluate Actian and explore the potential benefits of unified data platforms.”

At Actian, we agree. That’s why I encourage you to experience the Actian Data Platform for yourself or join us at upcoming industry events to connect with us in person.

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About Actian Corporation

Actian empowers enterprises to confidently manage and govern data at scale. Actian data intelligence solutions help streamline complex data environments and accelerate the delivery of AI-ready data. Designed to be flexible, Actian solutions integrate seamlessly and perform reliably across on-premises, cloud, and hybrid environments. Learn more about Actian, the data division of HCLSoftware, at actian.com.

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Actian Life

The Trend Continues: Actian Once Again Named a Top Workplace

Actian Corporation

February 6, 2024

hands representing teamwork for Actian being a top workplace

At Actian, we’re about enabling customers to trust their data. But, within our company, we also trust each other—our highly skilled, talented, and personable employees have confidence in each other and in our leadership team. That’s one of the reasons why Actian Careers stands out as a top choice for employment opportunities.

Our dedicated staff and employee-first approach to business make a significant difference in the services and technologies we provide to customers. They’re also why Actian is recognized by our employees for our culture and also why we just earned another award for being a Top Workplace.

Elevating the Employee Experience in the Virtual Workspace

Actian was recognized by Monster—a global leader in connecting people and jobs—with a 2024 Top Workplaces for Remote Work award. “These awards underscore the importance of listening to employees about where and when they can be their most productive and happiest selves,” explains Monster CEO Scott Gutz. “We know that this flexibility is essential to helping both employers and candidates find the right fit.”

The 2024 Top Workplaces for Remote Work award celebrates organizations with 150 or more employees that provide an exceptional remote working environment. The Top Workplaces employer recognition program has a 17-year history of researching, surveying, and celebrating people-first organizations nationally and across 65 regional markets.

The company Energage determines the awards through an employee survey. This means we received the award based on direct and honest employee feedback. Results of a confidential employee engagement survey were evaluated by comparing responses to research-based statements that predict high performance against industry benchmarks.

Proven History of Offering an Inclusive, Supportive, and Flexible Workplace

Actian offers a culture where people belong, are enabled to innovate, and can reach their full potential. It’s not just a place to work—it’s a place to thrive, belong, and make a difference.

Being honored with a Top Workplace award demonstrates that when we say we place employees first, we mean it and employees experience it every day. Some of the ways we engage and reward our staff include:

  • A Rewards and Recognition Program that showcases an individual’s work and contributions.
  • Professional development to empower employees to grow their skill set.
  • Seasonal events and regular gatherings—including some that are virtual.
  • A commitment to work-life flexibility.
  • Time off to volunteer and give back to communities.
  • Quarterly peer nominations to recognize colleagues for their work.

People feel welcome at Actian, which is why we’ve seen a pattern of being recognized for our workplace and culture. This includes receiving 10 Top Workplace awards for Culture Excellence in 2023, seven in 2022, and one each in 2021 and 2020.

These awards span Innovation, Work-Life Balance, Leadership, Cross-Team Collaboration, Meaningful Work, Employee Appreciation, and more. We’ve also been named a Top Workplace by other organizations based on employee feedback.

Join Us

It is the highest honor to have employees give us high marks for our workplace. If this sounds like an environment where you’d like to work, and you’re interested in bringing your talent to Actian, view our open career opportunities.

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About Actian Corporation

Actian empowers enterprises to confidently manage and govern data at scale. Actian data intelligence solutions help streamline complex data environments and accelerate the delivery of AI-ready data. Designed to be flexible, Actian solutions integrate seamlessly and perform reliably across on-premises, cloud, and hybrid environments. Learn more about Actian, the data division of HCLSoftware, at actian.com.

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Data Intelligence

What is a Data Product Owner? Role, Skills and Responsibilities

Actian Corporation

February 5, 2024

In our previous article on Data Products, we discussed the definition, characteristics, and examples of data products as well as the necessity to switch to a product-thinking mindset to truly transform your datasets into viable data products. Amid this shift towards a Data Mesh architecture, it is important to highlight a very important part of data product management – data product ownership. Indeed, it is crucial to appoint the right people as stakeholders for your enterprise data products.

In this article, we go over the human side of data products – the role, responsibilities, and required skills of a Data Product Owner.

What are the Role and Skills of a Data Product Owner?

As the name suggests, Data Product Owners are the guarantors of the development and success of data products within an organization. They act as a bridge between data teams, stakeholders, and end-users, translating complex data concepts into actionable insights that drive value and innovation. To do so, Data Product Owners have unique sets of technical skills, including the ability to extract insights from data & identify patterns, understand programming languages such as Python or R, and have a strong foundation in data technologies such as data warehouses, databases, data lakes, etc.

In addition to technical skills, a Data Product Owner has great business acumen, with the ability to understand the business context, objectives, trends, and overall landscape and develop data strategies that are aligned with said context. They therefore use data for decision-making by correctly collecting and analyzing data.

Lastly, Data Product Owners have great communication skills, with the ability to convey data insights to the different stakeholders in the company such as data scientists and developers but also non-technical roles such as business users and analysts. They usually also have experience in agile methodologies and problem-solving skills to deliver successful data products on time.

What are a Data Product Owner’s Core Responsibilities?

The multifaceted nature of a Data Product Owner as described above makes them have a variety of responsibilities. In Data Mesh in Action, by J. Majchrzak et al., they list Data Product Owners’ tasks as:

  • Vision definition: They are responsible for determining the purpose of creating a data product, understanding its users, and capturing their expectations through the lens of product thinking.
  • Strategic planning of product development: They are in charge of creating a comprehensive roadmap for the data product’s development journey, as well as defining key performance indicators (KPIs).
  • Ensuring satisfaction requirements: Ensuring the data product meets all requirements is a critical responsibility. This includes providing a detailed metadata description and ensuring compliance with accepted standards and data governance rules.
  • Backlog Management & Prioritization: The Data Product Owner makes tactical decisions regarding the management of the data product backlog. This involves prioritizing requirements, clarifying them, splitting stories, and approving implemented items.
  • Stakeholder Management: They must gather information to understand expectations and clarify any inconsistencies or conflicting requirements to ensure alignment.
  • Collaboration With Development Teams: Engaging with the data product development team is essential for clarifying requirements and making informed decisions on challenges affecting development and implementation.
  • Participation in Data Governance: The Data Product Owner actively contributes to the data governance team, influencing the introduction of rules within the organization and providing valuable feedback on the practical implementation of data governance rules.

While the principle dictates one Data Product Owner for a specific data product, a single owner may oversee multiple products, especially if they are smaller or require less attention. The size and complexity of data products vary, leading to differences in the specific responsibilities shouldered by Data Product Owners.

What are the Differences Between a Data Product Owner and a Product Owner?

The relationship between a Product Owner and a Data Product Owner can vary based on specific characteristics and requirements. While in some instances, these roles overlap, in others, they distinctly diverge. In the book Data Mesh in Action, they distinguish between three different scenarios:

Case 1: The Dual Role

In this scenario, the Data Product Owner also serves as a Product Owner, and the development teams for both the data product and the overall product alignment. This configuration is most fitting when the data product extends from the source system, and the complexity is manageable, not requiring separate development efforts.

An example would be a subscription purchase module providing data on purchases seamlessly integrated into the source system.

Case 2: Dual Ownership, Separate Teams

Here, the Data Product Owner holds a dual role as a Product Owner, but the teams responsible for the data product and the overall product development are distinct. This setup is applied when analytical data derived from the application is extensive, requiring a distinct backlog and a specialized team for execution.

An example would be a subscription purchase module offering analytical data supported by a ML model, enabling predictions of purchase behavior.

Case 3: Independent Entities

In this scenario, the roles of the Data Product Owner and Product Owner are distinct, and the teams responsible for the data product and the overall product development operate independently. This configuration is chosen when the data product is a complex solution demanding independent development efforts.

An example would be building a data mart supported by an ML model for predicting purchase behavior.

In essence, the interplay between the roles of Product Owner and Data Product Owner is contingent upon the intricacies of the data product and its relationship with the overarching system. Whether they converge or diverge, the configuration chosen aligns with the specific demands posed by the complexity and integration requirements of the data product in question.

Conclusion

In conclusion, as organizations increasingly adopt Data Product Management within a Data Mesh architecture, the effectiveness of dedicated Data Product Owners becomes essential. Their capacity to connect technical intricacies with business goals, combined with a deep understanding of evolving data technologies, positions them as central figures in guiding the journey toward unleashing the full potential of enterprise Data Products.

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About Actian Corporation

Actian empowers enterprises to confidently manage and govern data at scale. Actian data intelligence solutions help streamline complex data environments and accelerate the delivery of AI-ready data. Designed to be flexible, Actian solutions integrate seamlessly and perform reliably across on-premises, cloud, and hybrid environments. Learn more about Actian, the data division of HCLSoftware, at actian.com.
Data Management

How to Develop a Multi-Cloud Approach to Data Management

Teresa Wingfield

January 26, 2024

multi cloud data management

A recent 451 Research survey found that an astonishing 98% of companies are using more than one cloud provider. Two-thirds of organizations use services from 2 or 3 public cloud providers and nearly one-third of organizations use four or more providers. Using a multi-cloud strategy involves using the services of multiple cloud providers simultaneously. It’s the dominant data management strategy for most organizations.

Top Multi-Cloud Advantages

There’s a long list of reasons why organizations choose to adopt a multi-cloud approach versus just being tied to a single provider.  Here’s a look at some of the top reasons.

You Can Match the Right Cloud to the Right Job

The features and capabilities of cloud vendors vary greatly, so using a multi-cloud approach can let you select the best providers for your specific workload requirements. Differences in services for analytics, machine learning, big data, transactions, enterprise applications, and more are factors to consider when deciding where to run in the cloud. Product integrations, security, compliance, development tools, management tools, and geographic locations unique to a cloud provider may also influence your choice.

You Can Save Money

Pricing between providers can differ significantly. These are just a few examples of what you need to take into account when comparing costs:

  • Providers price the same services differently.
  • Resources such as compute, memory, storage, and networks have different configurations and pricing tiers.
  • The geographic location of a data center can lead to differences in the cost of cloud provider services.
  • Discounts for reserved instances, spot instances, and committed use can save you dollars depending on your usage patterns.
  • Data transfer costs between regions, data centers, and the internet can add up quickly and you should factor these into your costs.
  • The cost of support services can also impact overall expenses.

You Can Enhance Business Continuity

Multi-cloud strategies can enhance business continuity so your cloud processing can resume quickly in the face of disruptions. Below are some aspects of multi-cloud business continuity:

  • There’s no single point of failure.
  • Geographic redundancy enhances resilience against adverse regional events.
  • Cloud provider diversification mitigates the impact of vendor-specific issues such as a service outage or a security breach. Traffic can be redirected to another provider to avoid service disruption.
  • Data storage redundancy and backup across clouds can help prevent data loss and data corruption.
  • Redundant network connectivity across multiple clouds can prevent network-related disruptions.

You Can Avoid Vendor Lock-In

Using multiple cloud providers prevents organizations from being tied to a single provider. This avoids vendor lock-in, giving organizations more freedom to switch providers or negotiate better terms as needed.

You Can Strengthen Your Compliance

Different cloud providers may offer different compliance certifications and different geographic locations for where data is stored. A choice of options helps improve compliance with industry standards and regulations as well as compliance with data residency and data sovereignty-specific regulations.

Some organizations choose to operate a hybrid cloud environment with capabilities stratified across multiple clouds, private and public. Sensitive data applications may be on a private cloud where an organization has more control over the deployment infrastructure.

Actian in a Multi-Cloud World

Despite these advantages, it’s essential for organizations to carefully plan and manage their multi-cloud data management strategy to ensure seamless integration, efficient resource utilization, and strong security.

The Actian Data Platform is a platform that meets multi-cloud data management requirements with features such as a universal data fabric and built-in data integration tools to process and transform data across clouds. You will also benefit from cloud economics, paying only for what you use, having the ability for the service to shut down or go to sleep after a pre-defined period of inactivity, and scheduling starting, stopping, and scaling the environment to optimize uptime and cost. Security such as data plane network isolation, industry-grade encryption, including at-rest and in-flight, IP allow lists, and modern access controls handle the complexities of multi-cloud security.

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About Teresa Wingfield

Teresa Wingfield is Director of Product Marketing at Actian, driving awareness of the Actian Data Platform's integration, management, and analytics capabilities. She brings 20+ years in analytics, security, and cloud solutions marketing at industry leaders such as Cisco, McAfee, and VMware. Teresa focuses on helping customers achieve new levels of innovation and revenue with data. On the Actian blog, Teresa highlights the value of analytics-driven solutions in multiple verticals. Check her posts for real-world transformation stories.

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Data Intelligence

Enhance Your Data Catalog With an Enterprise Data Marketplace (EDM)

Actian Corporation

January 25, 2024

data catalog data marketplace

Over the past decade, Data Catalogs have emerged as important pillars in the landscape of data-driven initiatives. However, many vendors on the market fall short of expectations with lengthy timelines, complex and costly projects, bureaucratic Data Governance models, poor user adoption rates, and low-value creation. This discrepancy extends beyond metadata management projects, reflecting a broader failure at the data management level.

The present situation reveals a disconnection between technical proficiency and business knowledge, a lack of collaboration between data producers and consumers, persistent data latency and quality issues, and unmet scalability of data sources and use cases. Despite substantial investments in both personnel and technology, companies find themselves grappling with a stark reality – the failure to adequately address business needs.

The good news, however, is that this predicament can be reversed by embracing an Enterprise Data Marketplace (EDM) and leveraging existing investments.

Introducing the Enterprise Data Marketplace

An EDM is not a cure-all but rather a transformative solution. It necessitates that companies to reframe their approach to data, introducing a new entity – Data Products. A robust Data Mesh, as advocated by Zhamak Dehghani in her insightful blog post, becomes imperative, with the EDM serving as the experiential layer of the Data Mesh.

However, the landscape has evolved with a new breed of EDM – a Data Sharing Platform integrated with a robust federated Data Catalog:

EDM = Data Sharing Platform + Strong Data Catalog

This is precisely what the Actian Data Intelligence Platform accomplishes, and plans to enhance further, with our definition of an EDM:

An Enterprise Data Marketplace is an e-commerce-like solution, where Data Producers publish their Data Products, and Data Consumers explore, understand, and acquire these published Data Products.

The Marketplace operates atop a Data Catalog, facilitating the sharing and exchange of the most valuable Domain Data packaged as Data Products.

Why Complement Your Data Catalog With an Enterprise Data Marketplace?

We’ve compiled 5 compelling reasons to enhance your Data Catalog with an Enterprise Data Marketplace.

Reason #1: Streamline the Value Creation Process

By entrusting domains with the responsibility of creating Data Products, you unlock the wealth of knowledge possessed by business professionals and foster a more seamless collaboration with Data Engineers, Data Scientists, and Infrastructure teams. Aligned with shared business objectives, the design, creation, and maintenance of valuable, ready-to-use Data Products will collectively adopt a Product Design Thinking mindset.

Within this framework, teams autonomously organize themselves, streamlining ceremonies for the incremental delivery of Data Products, bringing fluidity to the creation process. As Data Products incorporate fresh metadata to guide Data Consumers on their usage, an EDM assumes a pivotal role in shaping and exploring metadata related to Data Products – essentially serving as the Experience Plane within the Data Mesh framework.

By adhering to domain-specific nuances, there is a notable reduction in both the volume and type of metadata, alongside a more efficient curation process. In such instances, a robust EDM, anchored by a potent Data Catalog like the Actian Data Intelligence Platform, emerges as the core engine. This EDM not only facilitates the design of domain-specific ontologies but also boasts automated harvesting capabilities from both on-premises and cloud-based data sources. Moreover, it empowers the federation of Data Catalogs to implement diverse Data Mesh topologies and grants end-users an effortlessly intuitive eCommerce-like Data Shopping experience.

Reason #2: Rationalize Existing Investments

By utilizing an EDM (alongside a powerful Data Catalog), existing investments in modern data platforms and people can be significantly enhanced. Eliminating intricate data pipelines, where data often doesn’t need to be moved, results in substantial cost savings. Similarly, cutting down on complex, numerous, and unnecessary synchronization meetings with cross-functional teams leads to considerable time savings.

Therefore, a focused approach is maintained by the federated governance body, concentrating solely on Data Mesh-related activities. This targeted strategy optimizes resource allocation and accelerates the creation of incremental, delegated Data Products, reducing the Time to Value.

To ensure measurable outcomes, closely monitoring the performance of Data Products with accurate KPIs becomes paramount – This proactive measure enhances decision-making and contributes to the delivery of tangible results.

Reason #3: Achieve Better Adoption Than With a Data Catalog Only

An EDM, coupled with a powerful Data Catalog, plays a pivotal role in facilitating adoption. At the domain level, it aids in designing and curating domain-specific metadata easily understood by Domain Business Users. This avoids the need for a “common layer”, a typical pitfall in Data Catalog adoption. At the Mesh Level, it offers means to consume Data Products effectively, providing information on location, version, quality, state, provenance, platform, schema, etc. A dynamic domain-specific metamodel, coupled with strong search and discovery capabilities, makes the EDM a game-changer.

The EDM’s added value lies in provisioning and access rights, integrating with ticketing systems, dedicated Data Policy enforcement platforms, and features from Modern Data platform vendors – a concept termed Computational Data Governance.

Reason #4: Clarify Accountability and Monitor Value Creation Performance

Applying Product Management principles to Data Products and assigning ownership to domains brings clarity to responsibilities. Each domain becomes accountable for the design, production, and life cycle management of its Data Products. This focused approach ensures that roles and expectations are well-defined.

The EDM then opens up Data Products to the entire organization, setting standards that domains must adhere to. This exposure helps maintain consistency and ensures that Data Products align with organizational goals and quality benchmarks.

In the EDM framework, companies establish tangible KPIs to monitor the business performance of Data Products. This proactive approach enables organizations to assess the effectiveness of their data strategies. Additionally, it empowers Data Consumers to contribute to the evaluation process through crowd-sourced ratings, fostering a collaborative and inclusive environment for feedback and improvement.

Reason #5: Apply Proven Lean Software Development Principles to Data Strategy

The creation of Data Products follows a similar paradigm to the Lean Software Development principles that revolutionized digital transformation. Embracing principles like eliminating waste, amplifying learning, deciding late, delivering fast, and building quality is integral to the approach that a Data Mesh can enable.

In this context, the EDM acts as a collaborative platform for teams engaged in the creation of Data Products. It facilitates:

  • Discovery Features: Offering automatic technical curation of data types, lineage information, and schemas, enabling the swift creation of ad hoc products.
  • Data Mesh-Specific Metadata Curation: The EDM incorporates automatic metadata curation capabilities specifically tailored for Data Mesh, under the condition that the Data Catalog has federation capabilities.
  • 360 Coverage of Data Products Information: Ensuring comprehensive coverage of information related to Data Products, encompassing their design and delivery aspects.

In essence, the collaboration between an Enterprise Data Marketplace and a powerful Data Catalog not only enhances the overall data ecosystem but also brings about tangible benefits by optimizing investments, reducing unnecessary complexities, and improving the efficiency of the data value creation process.

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About Actian Corporation

Actian empowers enterprises to confidently manage and govern data at scale. Actian data intelligence solutions help streamline complex data environments and accelerate the delivery of AI-ready data. Designed to be flexible, Actian solutions integrate seamlessly and perform reliably across on-premises, cloud, and hybrid environments. Learn more about Actian, the data division of HCLSoftware, at actian.com.
Data Management

Digital Transformation: Database Modernization in Applications

Teresa Wingfield

January 18, 2024

digital transformation and database modernization

In my previous blog on digital transformation, I wrote about the benefits of migrating mission-critical databases to the cloud. This time, I’m focusing on database modernization in applications. Application modernization can involve modernizing an application’s code, features, architecture and/or infrastructure. It’s a growing priority according to The 2023 Gartner CIO and Technology Executive Survey that places it in the top 4 technology areas in spending, with 46% of organizations increasing their spending on application modernization. Further, Foundry, an IDG company, reports that 87% of its survey respondents cite modernizing critical applications as a key success driver.

7 Benefits of Database Application Modernization

Why all the recent interest in transitioning to modern applications? Application modernization and database modernization are closely intertwined processes that work together to enhance the overall agility, efficiency, performance, security, innovation, and capabilities of an organization’s business. Here’s how application modernization complements database modernization:

Accelerated Time to Market

Monolithic legacy applications are time-consuming to update. Modernized applications with a loosely coupled architecture can enable faster development cycles, reducing the time it takes to bring new features or products to market. Agile development methodologies often accompany application modernization, enabling incremental and iterative development so that teams can respond rapidly to changing business requirements.

Cloud-Enabled Opportunities

Moving applications to the cloud as part of an application modernization initiative provides an extensive list of advantages over on-premises deployments, including elasticity, scalability, accessibility, business continuity, environmental sustainability, and more.

Optimized User Experience

Modernizing applications offers many ways to increase user satisfaction, and productivity, including more intuitive interfaces, personalization, improved response times and better accessibility.  Multi-channel support such as mobile and web and cross-platform compatibility extend reach while advanced search and navigation, rich media incorporation, and third-party integrations add value for users.

Stronger Security and Compliance

Legacy applications built on outdated technologies may lack security features and defenses against contemporary threats and may not comply with regulatory compliance requirements. Modernizing applications allows for the implementation of the latest security measures and compliance standards, reducing the likelihood of security breaches and non-compliance.

Staff Productivity

Legacy systems can be difficult to maintain and may require significant technical resources for updates and support. Modern applications can improve staff efficiency, reduce maintenance expenses, and lead to better utilization of resources for strategic initiatives that deliver greater value to the business.

Easier Integration

Application modernization supports integration with technologies and architectural best practices that enhance interoperability, flexibility, and efficiency. Using technologies such as microservices, APIs, containers, standardized protocols, and/or cloud services, it’s easier to integrate modernized applications within complex IT environments.

Support for Innovation

Legacy applications often make it difficult to incorporate newer technologies, hindering innovation. Modernizing applications allows organizations the ability to leverage emerging technologies, such as machine learning and Internet of Things (IoT) for competitive advantage.

Database Application Modernization With Ingres NeXt

In summary, database application modernization is a strategic digital transformation initiative that can help organizations stay ahead in the digital age.  However, application modernization can be expensive and risky without the right approach.

Ingres NeXt is designed to protect existing database application investments in OpenROAD while leveraging them in new ways to add value to your business, without costly and lengthy rewrites. Flexible options to modernize your OpenROAD applications include:

  • ABF and Forms-Based Applications – Modernize ABF applications to OpenROAD frames using the abf2or migration utility and extend converted applications to mobile and web applications.
  • OpenROAD and Workbench IDE – Migrate partitioned ABF applications to OpenROAD frames.
  • OpenROAD Server – Deploy applications securely in the OpenROAD Server to retain and use application business logic.

In addition, The Ingres NeXt Readiness Assessment offers a pre-defined set of professional services that can lower your risk for application modernization and increase your confidence for a successful cloud journey. The service is designed to assist you with understanding the requirements to modernize Ingres and ABF or OpenROAD applications and to impart recommendations important to your modernization strategy formulation, planning, and implementation.

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About Teresa Wingfield

Teresa Wingfield is Director of Product Marketing at Actian, driving awareness of the Actian Data Platform's integration, management, and analytics capabilities. She brings 20+ years in analytics, security, and cloud solutions marketing at industry leaders such as Cisco, McAfee, and VMware. Teresa focuses on helping customers achieve new levels of innovation and revenue with data. On the Actian blog, Teresa highlights the value of analytics-driven solutions in multiple verticals. Check her posts for real-world transformation stories.

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Data Intelligence

Everything You Need to Know About Data Products

Actian Corporation

January 18, 2024

data products blue cubes

In recent years, the data management and analytics landscape has witnessed a paradigm shift with the emergence of the Data Mesh framework. Coined by Zhamak Dehghani in 2019, Data Mesh is a framework that emphasizes a decentralized and domain-oriented approach to managing data. One notable discipline in the Data Mesh architecture is to treat data as a product, introducing the concept of “data products”. However, the term “data product” is often tossed around without a clear understanding of its essence. In this article, we will shed light on everything you need to know about data products and data product thinking.

Shifting to Product Thinking

For organizations to treat data as products and transform their datasets as data products, it is essential for teams to first shift to a product-thinking mindset. According to J. Majchrzak et al. in Data Mesh in Action,

Product thinking serves as a problem-solving methodology, prioritizing the comprehensive understanding of user needs and the core problem at hand before delving into the product creation process. The primary objective is to narrow the gap between user requirements and the proposed solution.

In their book, they highlight two main principles:

  • Love the problem, not the solution: Before embarking on the design phase of a product, it is imperative to gain an understanding of the users and the specific problem being addressed.
  • Think in terms of products, not features: While there is a natural inclination to concentrate on adding new features and customizing assets, it is crucial to view data as a product that directly satisfies user needs.

Therefore, before unveiling a dataset, adhering to product thinking involves posing essential questions:

  • What is the problem that you want to solve?
  • Who will use your data product?
  • Why are you doing this? What is the vision behind it?
  • What is your strategy? How will you do it?
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About Actian Corporation

Actian empowers enterprises to confidently manage and govern data at scale. Actian data intelligence solutions help streamline complex data environments and accelerate the delivery of AI-ready data. Designed to be flexible, Actian solutions integrate seamlessly and perform reliably across on-premises, cloud, and hybrid environments. Learn more about Actian, the data division of HCLSoftware, at actian.com.