Blog | Data Analytics | July 19, 2022 | 3 min read

How the Right Data Platform Approach Unleashes Competitive Advantage

By Jennifer Jackson

#Data Analytics
data partitioning

By Jennifer Jackson

#Data Analytics
In this post:

For some time now, we at Actian have been focusing squarely on making the Actian Data Platform the most trusted, flexible, and easy-to-use data platform on the market.

These, of course, are traits that anybody in any industry would want to trumpet. But they’re especially important in the world of data, where the market is shifting rapidly and customers are making technology decisions that will determine their level of business success for years to come.

Here’s what we mean. In recent years, data’s role as a competitive asset has grown substantially. As data volumes swell and calls for data-driven insights increase, companies have scrambled to piece together the best possible ways to store, access, manage, and analyze this critical resource. Many vendors have responded by pursuing a “platform approach,” trying to pull capabilities previously siloed in data warehouses, data lakes, data hubs, and analytics hubs into new, more versatile data platforms.

It’s driven a market convergence where industry upstarts and veterans are competing in the same field. We believe we’re positioned well in this competition for a few reasons. We have the data expertise and knowledge the new, born-in-the-cloud data vendors don’t have. Traditional, legacy brands, meanwhile, are struggling to pivot. We bring all of this expertise to the cloud in a way that makes data easy.

We’ve built trust, flexibility, and ease of use into the Actian Data Platform in several ways.

Through Superior Price Performance

The platform outperformed, on speed and price performance, four other leading cloud services, including Google BigQuery, in an Enterprise Strategy Group Technical Validation report. Actian Data Platform performed up to 7.9 times faster with up to 92% lower cost for simulated queries run by five concurrent users of cloud-based data warehouses.

Through Native Integration

For customers to use born-in-the-cloud vendor platforms for analytics purposes, they have to partner with a data integration vendor. In the Actian platform, the warehouse, database, and integration capabilities are native. Hundreds of connectors are available, allowing customers to connect any source to any target. It’s built into the platform, not the warehouse, and customers can consume services all through the same mechanism.

Through REAL, Real-Time Data

A lot of vendors claim to return data queries in real-time, but as they’re updating the database with real-time information, they experience latency. In Actian, queries still run at the same speed. Customers are powered to have data in their hands when they truly need it.

Through Hybrid Deployment

For Actian, it’s the ability to use the same platform to deploy on different clouds, on-premises, and in hybrid environments. Pure cloud players can’t operate in hybrid or on-prem situations, and major cloud providers won’t operate instances provided by a chief competitor. The platform is agnostic.

Actian customers are seeing value in the platform approach. The London Stock Exchange is using Actian for trade analysis, enabling customers to make smart trade decisions in the moment. The AA, an insurance company in EMEA, offers on-demand insurance quotes on its website using Actian’s real-time engine.

Companies that win the most use data as a key differentiator. Leveraging a platform that inspires trust, performs flexibly and is easy to use enables them to separate themselves in the market. We believe our vision and capabilities make Actian the perfect company to partner with to unlock the competitive advantage data brings.

Blog | Data Intelligence | July 11, 2022 | 3 min read

What is Data Virtualization?

By Actian Corporation

#Data
Data Virtualization

By Actian Corporation

#Data
In this post:

Committing to a data-driven project can sometimes feel like opening Pandora’s box. To avoid getting lost along the way, you need to have a global, secure, and agnostic view of all your data. Among the avenues to explore, there is data virtualization. 

Companies that embark on the path of a data-driven strategy have a compelling need to rely on real-time data. All processes and thought patterns are oriented around data to make faster and more relevant decisions to bring more value to their customers. However, there is a challenge: the more data you use, the more likely it is to be scattered across different platforms, and therefore, the more you need to reconcile your data sources. The risk? Degrading the effectiveness of your data-driven project. To avoid exposure to this risk, there is a path to explore.

This path involves deploying an advanced data integration methodology, called data virtualization.

What is Data Virtualization?

Data is central to your company’s strategy, making it essential to collect data from different sources. However, this creates the risk of having scattered information. When data is disparate, it’s difficult to get an overview that allows for quick and informed decision-making. If some of your data remains in the shadows, if it doesn’t fit into the scope of your analyses, there is a risk of making mistakes.

The objective of data virtualization is to fight against this scattering by bringing together all your data, regardless of their origin, without moving or copying them. The principle is to create a single virtual zone where all your data assets are available regardless of origin or format. Data virtualization provides a global, unified, organized, and encapsulated view of all your data, whether it comes from the same or different data sources, without having to manipulate or move it. A single “virtual” data layer is created to deliver unified data services.

What are the Benefits of Data Virtualization?

Data virtualization supports multiple applications and users while providing:

  • Faster access to data, limiting the latency between data collection and exploitation.
  • Significantly reduced time to market for data.
  • A decrease in data redundancy.
  • Agile decision-making.

The first essential benefit of this approach is to have a global and exhaustive vision of all your data. But data virtualization also has another advantage: you don’t have to move, copy or manipulate data, which remains stored in its original platforms. Because the source data is preserved, it cannot be altered or degraded and therefore retains its original quality. And because it is not manipulated, you save considerable time in making decisions.

How Does Data Virtualization Work?

A data virtualization solution works as a single platform that provides access to all data in a virtual environment. The data can be accessed directly, without being moved from its original source. This not only simplifies data access to the maximum extent but also minimizes the risk of degrading or damaging the data. A data virtualization solution aggregates all structured and unstructured data sources to offer a virtual visualization, all available via a dashboard. It allows you to visualize metadata while eliminating the complexity of reconciling disparate data sources.

To reduce storage costs, optimize data governance, simplify access to data and, ultimately, develop your data-driven culture, why not start data virtualization?

Blog | Data Security | July 7, 2022 | 5 min read

Data Security, Data Privacy, and Moving to the Public Cloud

By Actian Corporation

#Cloud Data Platform #Data Security
Data security and privacy when moving to the cloud.

By Actian Corporation

#Cloud Data Platform #Data Security
In this post:

The cloud has revolutionized the way modern businesses operate. By moving to the cloud, companies can access data and applications from anywhere globally, scale their remote infrastructures in real-time, and take advantage of cloud-based analytics and machine learning tools.

Transitioning to cloud-based applications and solutions offers unparalleled flexibility for businesses, but it also comes with certain risks. When moving to the cloud, one of the biggest concerns for businesses is data security and data privacy, which are essential for companies to get right.

The Importance of Data Security and Privacy in Today’s Cloud Landscape

The cloud has become the go-to platform for businesses of all sizes. It is flexible, scalable, and cost-effective, making it the perfect solution for organizations looking to improve their IT infrastructure. However, with the cloud comes new security challenges.

Data security and privacy are top concerns for companies moving to the cloud. And rightfully so—the cloud is a shared environment, which means your data is stored on servers that are managed by other organizations. This creates risk if the servers are not properly secured.

To add to some of these concerns, recent high-profile data breaches have made headlines and spotlighted the importance of effective cloud security. In 2019, Capital One experienced a data breach in which a hacker was able to access the personal information of more than 100 million people’s credit card applications and accounts stored on cloud data servers.

This instance and many others prove how important it is for companies to maintain a robust cloud security strategy to successfully protect their data and that of their customers.

Best Practices for Securing Cloud Data Platforms

While there are risks associated with moving more data through the cloud, there are best practices businesses can follow to ensure their cloud data platforms meet their organization’s data security and privacy requirements.

Encrypting Data at Rest and in Transit

One of the most important things companies can do to secure their cloud data is to encrypt it. This makes it much more difficult for hackers to access and steal data if they penetrate your cloud servers.

There are two main types of encryption: at-rest and in-transit. At-rest encryption refers to encrypting data that is stored on cloud servers. In-transit encryption protects data as it is being transmitted between different systems—for example, when you are sending an email or accessing a website.

Both at-rest and in-transit encryption are essential for securing cloud data. And while at-rest data is typically considered more secure because of its reduced attack surface, it is critical to ensure it’s adequately encrypted as it is targeted more by attackers.

Many different cloud encryption key management systems are available, so do your research and choose one that meets your organization’s specific needs.

Implementing Identity and Access Management

Another best practice for securing cloud data is implementing an identity and access management (IAM) system. IAM is a process of managing users’ identities, roles, and permissions. It is designed to allow authorized users access to the data and resources they need while preventing unauthorized entry.

IAM can be used to control who has access to your cloud servers and data and what actions they can take. For example, you can use IAM to grant read-only access to specific files or folders for some users while allowing others to read, write, and delete files.

Using Multi-Factor Authentication

Multi-factor authentication (MFA) is an additional layer of security that can be added to cloud data platforms. MFA requires users to provide more than one piece of evidence (or factor) to verify their identity before being granted access to a system.

The most common type of MFA is two-factor authentication, which requires a user to provide a password and a one-time code generated by an app or sent via text message.

Adding MFA can help to further protect your cloud data by making it more difficult for hackers to gain access to your servers. Even if a user’s password is obtained, hackers would also need the one-time code making it less likely that your storage solutions could be compromised.

Establishing Real-Time Monitoring and Protection

Taking a proactive approach to cloud security is always best, and an effective way to do so is to establish real-time monitoring and protection. This means setting up alerts, so you are notified immediately if there is any suspicious activity on your cloud servers.

Most cloud data platforms have some form of built-in security monitoring that helps keep an eye on your servers and data, but many third-party cloud security tools can provide additional protection.

When deciding on the level of security monitoring and protection that is right for your organization, it is essential to consider the type of data you are storing in the cloud and the sensitivity of that data. For example, if you are storing financial or personal health information, you will need a higher level of security than what is needed to store basic contact information.

Either way, it is essential to have a form of monitoring and protection in place so you can quickly identify and respond to any potential threats before they evolve into business-wide security and compliance issues.

Balancing Cloud Flexibility and Adequate Security

Cloud data platforms offer flexibility, which is often one of the main reasons organizations choose to use them. However, this flexibility can also present some challenges when securing cloud data.

Organizations must strike a balance between providing adequate security for their cloud data and maintaining the flexibility they need to run their business.

The good news is that many different security measures can be taken to protect cloud data. With a proactive approach and by implementing the best security practices, organizations can keep their data safe while enjoying the benefits of using a cloud data platform.

Blog | Data Intelligence | July 6, 2022 | 5 min read

Does a Data Catalog Help Companies With Data Stewardship Programs?

By Actian Corporation

#Data Catalog #Metadata Management
Data Stewardship Data Catalog Benefits

By Actian Corporation

#Data Catalog #Metadata Management
In this post:

By implementing a data stewardship program in your organization, you ensure not only the quality of your data but also that it can be used easily and effectively by all your employees. As a key player in data governance and management, the Data Steward needs specific tools, the first of which is the data catalog.

The role of data in companies is becoming increasingly strategic, and not just for large organizations. Indeed, to define business strategies, manage distribution, or organize production, the exploitation of data constitutes a major competitive advantage. To deliver its full potential, data must be reliable, of high quality, and perfectly organized. These characteristics are linked to a discipline: Data Stewardship.

The Data Steward, also known as the Master of Data, acts as the guarantor of optimal data exploitation. How? By centralizing all data, regardless of its source, in an environment that is accessible to all business lines in a simple, intuitive, and operational manner. A Data Stewardship program is based on a rigorous methodology, a global vision of available data, and an ambition to rationalize data to develop a strong data culture. However, vision, understanding, and methodology do not exempt the Data Steward from relying on the right tools to accomplish their missions: a data catalog is one of the essential tools for a successful Data Stewardship project.

A Data Catalog’s Objectives

A data catalog exploits metadata – data on data – to create a searchable repository of all enterprise information assets. This metadata, collected by various data sources (Big Data, Cloud services, Excel sheets, etc.), is automatically scanned to enable users of the catalog to search for their data and get information such as the availability, freshness, and quality of a data asset. A data catalog centralizes and unifies the metadata collected so that it can be shared with IT teams and business functions. This unified view of data allows organizations to:

  • Sustain a data culture.
  • Accelerate data discovery.
  • Build agile data governance.
  • Maximize the value of data.
  • Produce better and faster.
  • Ensure good control over data.

The Benefits of a Data Catalog for Data Stewards

From importing new data sources to tracking information updates, the ability of a data catalog to track and monitor metadata in real-time automatically allows data stewards to gain efficiency. A data catalog provides 360° visibility into your data from its origin to all of its transformations over time. There are four key benefits to using a data catalog as part of a Data Stewardship program:

Benefit 1: Maintain up-to-Date Documentation

Your data is constantly active. It is collected, valued, exploited, enriched… To have a perfect understanding of your data assets, you need up-to-date documentation regarding its data sources and how they are used. A data catalog is designed to do just that.

Actian Data Intelligence Platform advantage: Our catalog automatically retrieves and collects metadata through our APIs and scanners to always ensure that your data is up-to-date. View your data’s origins and transformations over time with our smart lineage capabilities.

Benefit 2: Ensure Data Quality

The first vocation of a data catalog is to keep a clear view of your data via metadata. The definitions, structures, sources, uses, procedures to follow…by nature, metadata management by a data catalog contributes to guarantee the quality of your data.

Actian Data Intelligence Platform advantage: Our data catalog enables your Data Stewards to build flexible metamodel templates for predefined and custom item types. Simply drag & drop your properties, tags, and other fields into your documentation templates for all your catalog items.

Benefit 3: Comply With Data Regulations

Compliance with data regulations is a crucial issue in a Data Stewardship program. A data catalog, through its ability to organize data and centralize it in a clear, healthy, and readable environment, helps to comply with these regulatory requirements.

Actian Data Intelligence Platform advantage: Through machine learning capabilities, our Data Catalog speeds up time-consuming tasks by analyzing similarities between existing personal data. It provides smart recommendations by identifying and giving suggestions to tag personal data.

Benefit 4: Monitor Data Lifecycle

Between governance, quality, and security, your Data Stewardship project implies monitoring the lifecycle of your data in real-time. The data catalog responds to this challenge by offering you the possibility to monitor all activities affecting your data.

Actian Data Intelligence Platform advantage: our data catalog provides Data Stewards with a dashboard that tracks and monitors metadata activity. Check the completion levels of your documentation, the most frequently accessed and searched for catalog items, the connectivity status of your catalog, and get smart recommendations on the sensitivity level and additional properties to add to your fields.

Organization, knowledge, transparency, scalability…a data catalog is tailored to accompany your Data Stewardship project.

Start a Data Stewardship Program

Actian Data Intelligence Platform Data Catalog provides a metadata management solution that enables Data Stewards to overcome the challenges associated with handling increasingly large volumes of data. Our solution helps organizations maximize the value of their data by reducing the time spent on complex and time-consuming documentation tasks, and by breaking data silos to increase enterprise data knowledge.

Blog | Data Platform | July 5, 2022 | 3 min read

The Benefits of Cloud Compared to On-Premises

By Keith Bolam

#Cloud Data Warehouse #On-Premises
What are the benefits of cloud versus on-premises

By Keith Bolam

#Cloud Data Warehouse #On-Premises
In this post:

Starting at the turn of the century, there has been a steady move to the cloud across industries. It started slowly at first but has evolved into a paradigm shift for many businesses.

Security-conscious players – bricks-and-mortar financial institutions, healthcare providers, retailers and utilities – have been slower than others in adopting the cloud. New digital-first FinTechs, however, have been much more aggressive in their strategies. In many cases, these businesses would not exist if it were not for the cloud.

Overwhelmingly, we see that businesses operating in the cloud enjoy much greater flexibility, allowing them to compete in a fierce market and adapt to customer demands quickly. Without the shackles of legacy applications and the need to support a slow-changing culture of manual checks and balances, they have expanded quickly. According to Foundry’s Cloud Computing Study 2022, “just 27% of companies in the Asia-Pacific (APAC) region currently have most or all of their IT environment in the cloud, compared to 41% globally – but they expect that to double to 53% in the next 18 months.” While APAC still has a way to go, it is positioned well to become a world leader in the cloud.

The companies that have been making investments in cloud, mobile computing, security, and big data are reporting higher growth than those that are predominantly on-premises based. Tech-aware companies and industry leaders are leveraging the advantages of the cloud-computing trend to modernize their operations. A paradigm shift is taking place, from individual investments to collaborative (cloud) investment. Companies are using cloud technology to operate their businesses differently, helping them to identify prospects, improve customer service, and, in turn, generate greater ROI.

Cloud computing is a practical solution for small and large businesses alike. A small business can use as much instantaneous computing power as a large business, which previously would have been impossible if they had to invest in the on-premises hardware and infrastructure.

The Benefits of Cloud

Cloud offers a wide range of benefits for many applications. Take, for example, the strategic use of data. Creating a cloud data platform gives organizations the ability to store, access, and analyze data without being held back by legacy technologies. Consider what these benefits can unleash when they’re applied to data.

  1. No investment in on-premises hardware – It frees up limited financial CapEx so organizations can innovate and keep up with customers/competitors.
  2. Genuinely highly resilient storage – Theoretically indestructible limitless storage for anything digital enables them to scale projects as needed.
  3. The ability to locate compute near the point of consumption – While on-premises solutions tend to be in a limited number of data centers, cloud’s dispersed resources help users operate with more agility.
  4. Robust security – Once thought of as risky, cloud security now provides as good or significantly better protection than on-premises security.
  5. The option to pay as you go – Rather than pay a flat fee, organizations can scale usage and payments up and down seamlessly, avoiding unnecessary costs.

Taken together, all these benefits have enabled organizations to take advantage of the data revolution. Cloud data platforms give them the ability to process data quickly, scale their data usage as necessary, simplify their budgets and conduct deeper analyses of a wide range of data stores. The cloud paradigm shift has taken place – and it’s exerting its impact on the world of data.

Blog | Data Intelligence | June 28, 2022 | 4 min read

All You Need to Know About the Data Governance Act

By Actian Corporation

#Data Governance
Data Governance Act Zeenea

By Actian Corporation

#Data Governance
In this post:

The Council of the European Union has just approved the Data Governance Act, a document that aims to facilitate the re-use of certain protected public sector data and encourage data sharing throughout the European Union while ensuring strict respect of data privacy. It should be executed by 2023. 

When it comes to data, the European Union plays a major role. While the GDPR celebrated its fourth anniversary on May 25th, the European Parliament and the Council of the European Union continue to work for a reasonable and responsible use of data. The Data Governance Act (also known as the DGA) has been in the works since 2019 – the result of a broad consultation covering the private and public sectors. Based on 11 workshops, the DGA is devoted to the strengthening of the control offered to individuals and legal entities on the use and dissemination of their data. 

After an initial agreement on April 6th, 2022, to define the scope of the Data Governance Act, the Council of the European Union officially approved the DGA on May 16th, 2022. The Act is expected to be fully implemented by the summer of 2023. Beyond its main ambition, which is to define a unique and homogeneous framework for all European countries, the Data Governance Act is conceived as a legal instrument that should facilitate, fluidify, and rationalize the exploitation of data. 

Unlike the GDPR, the Data Governance Act is not limited to personal data but has much broader ambitions. These are ambitions that not only frame good practices related to data governance but also encourage the exploitation of data from the public sector. Behind the DGA, there is a double aspiration: to preserve the freedom of the business while protecting data privacy.

What Exactly is the DGA?

To fulfill its mission of protecting data while creating the conditions for freeing up innovation and creativity, the Data Governance Act is based on four key principles. 

The first principle concerns public actors. Like private sector companies, public agencies generate and use large amounts of data. This data falls under the scope of the GDPR and is subject to strict protection and oversight, whether it is personal data, privacy rights, or intellectual property. The DGA sets out a legal and technical framework that defines the rules for the re-use of this protected data, with essential levers such as anonymization or pseudonymization.

The second major component of the Data Governance Act is devoted to the sharing of data (personal or corporate) with non-profit organizations. The regulator’s ambition is to encourage innovation in the public interest in key sectors such as the environment and health sectors. A specific status called ‘altruistic organization’ will thus be created. To benefit from this status, it will be necessary to register officially via a European form and to respect a demanding framework, placed under the line of transparency.

The third principle of the DGA concerns the sharing of data between companies and private actors. These actors use intermediaries whose missions are redefined by the DGA. The principle is clear: to avoid that these intermediaries can exploit the information for their own purposes by sharing it. Once again, the DGA sets out the principle of total transparency, combined with an ambition for sovereignty. For example, these intermediaries must be located in the European Union or the European Economic Area.

Finally, the DGA institutes the creation of a European Data Innovation Council that will compile and share best practices related to data governance, with ongoing reflections on standardization at the European level.

What is the Impact of the Data Governance Act for Your Company?

While the DGA may seem restrictive in developing a precise framework, particularly for data intermediation, it is nevertheless a major step forward. Indeed, behind the native requirement inscribed in the spirit of the Data Governance Act, you will find above all, the ground of trust with your customers as well as your partner ecosystems. A trust that is essential to legitimize all data projects in the service of the efficiency and productivity of your company.

Blog | Data Management | June 21, 2022 | 5 min read

Cloud Economics – The Advantage of Moving Your Data to the Cloud (TCO)

By Actian Corporation

#Data Management
Digital cloud to illustrate how to calculate TCO

By Actian Corporation

#Data Management
In this post:

Cloud economics is a relatively new term, but it is growing in importance as businesses increasingly move their data to the cloud. As more organizations look for new ways to model their business in support of scalability and agility, it has become imperative that they better understand the short and long-term costs of cloud services.

There are many factors to consider when evaluating the economics of a move to the cloud, but one of the most important is Total Cost of Ownership (TCO).

What Exactly is Cloud Economics?

Cloud economics is the study of the financial impact of moving data and workloads to the cloud. This includes both the short-term and long-term costs associated with such a move, as well as any potential benefits that may be realized.

Understanding TCO

TCO is a financial metric that attempts to quantify all of the direct and indirect costs associated with a given investment over its lifetime. In the context of cloud computing, TCO analysis can be used to compare the costs of running a workload on-premises versus in the cloud.

There are several factors to consider when conducting a TCO analysis for cloud migration. You’ll need to think about short-term costs, such as data egress fees and one-time migration expenses. However, it is also essential to consider long-term costs, such as running and maintaining on-premises infrastructure and the opportunity cost of not taking advantage of cloud-native features and services.

Other vital things to keep in mind when evaluating TCO include:

  • Capex vs. Opex – While many believe that Opex is preferable, you may want to consider waiting for compelling reasons, such as data center decommissioning or hardware refreshes.
  • Labor – While the cloud can often require less human capital to operate, the cost of highly skilled cloud professionals may be higher than traditional data center staff.
  • Cost of Migration – This cost includes many facets, consultants, time, and risk. This is probably the biggest consideration and should be a big part of cloud planning.
  • Architecture – Vendor lock-in, portability, ecosystem integrations, and security all play a part in determining how to architect a shift to the cloud.

While TCO analysis can vary depending on the complexity of your business and its move to the cloud, it is essential to remember that the goal is to get a holistic view of all costs associated with a cloud transition. By understanding TCO, you can make more informed decisions about when, where, and how to plan and invest your resources.

The Advantages of Moving to the Cloud

As businesses calculate their TCO when moving data to the cloud, it becomes evident to most that there are many advantages to be gained. These benefits can be broken down into four main categories.

1. Increased Agility and Scalability

The cloud is an ideal platform for businesses looking to scale their operations quickly and easily. By moving to the cloud, you can take advantage of the elasticity and flexibility that the cloud provides, allowing you to scale up or down as needed. This can help you save on both capital and operational expenditures.

Additionally, the cloud allows you to quickly provision new resources and services as your business needs change. This increased agility can give you a competitive edge in today’s ever-changing business landscape and improve your customer experience.

2. Better Business Efficiency

The cloud can help you optimize your IT infrastructure and increase your operational efficiencies. By moving to the cloud, you can take advantage of features like auto-scaling and self-healing, which can help you reduce downtime and improve your overall efficiency.

The cloud also provides businesses with access to a global network of data centers, which can help you improve your latency and speed. This can be a significant advantage for businesses looking to improve customer experience. Additionally, all of the major cloud providers boast a robust set of ecosystem partners.

3. Enhanced Security

One of the common misconceptions about the cloud is that it is less secure than on-premises. However, this could not be further from the truth. In fact, the cloud can provide you with a number of security advantages.

When you move to the cloud, you gain access to a team of experts who are constantly working to keep your data safe. Additionally, the cloud provides you with robust security features like firewalls, intrusion detection, and encryption, which can help you protect your data. Of course, it’s important to remember that it’s a shared security model. In the most basic terms, your cloud provider secures the infrastructure, but your teams will still need to understand how to secure databases and applications.

4. Improved Disaster Recovery

The cloud can provide you with a robust disaster recovery solution that is scalable and reliable. By leveraging the cloud, you can ensure that your data is always protected and available, even in the event of a significant outage.

The cloud can also help you save on disaster recovery costs. With the cloud, you only pay for the resources you use, which can help you keep your disaster recovery costs to a minimum.

Bottom Line

When comparing costs between on-premise and cloud solutions, it is important to think about the total cost of ownership by considering all of the costs associated with a move to the cloud while also weighing the benefits of better scalability, agility, and improved business efficiency. Even with all the pros, there will always be situations, especially in highly regulated environments, where some data and applications will need to remain on-premises. Thankfully, hybrid cloud is also a viable choice and certainly should be considered as you plan for the ever-expanding future of cloud technology.

Blog | Data Intelligence | June 6, 2022 | 4 min read

What are the Benefits of Big Data in the Retail Industry?

By Actian Corporation

#Artificial Intelligence #Big Data #Machine Learning
Data Retail

By Actian Corporation

#Artificial Intelligence #Big Data #Machine Learning
In this post:

The recent COVID-19 crisis has forced retail players to reinvent themselves and accelerate their digital transformation. To gain a competitive advantage, the retail industry must rely on Big Data. Personalized experiences, optimized pricing, supply-chain connectivity; discover how data has transformed the retail & e-commerce sector.

Figures from the FEVAD (Federation of e-commerce and distance selling) indicate that the e-commerce sector has exceeded 129 billion euros in 2021, up 15.1% since 2020. The increasing success of online vendors has attracted more and more historical retailers to launch their e-commerce adventures. The consequence? The line between e-retail and retail is becoming increasingly tenuous. According to the LSA/HiPay 2021 study, 63% of French shoppers say they have used click & collect at least once, 44% have had a product delivered to their home, and 37% have returned a product purchased online.

In this very competitive context, the use of Big Data, driven by artificial intelligence and machine learning, has many advantages for this industry.

Benefit 1: A 360° View of Customers

Faced with an increasing number of digital and omnichannel consumers, retail players can have a 360° view of their customers through data. Indeed, data plays a huge role in building a relationship between customers and the retailer by providing point-of-sale experts with in-depth knowledge about a customer or a product. With a better understanding of the customers, their habits and expectations, as well as the products that are sold, salespeople can have richer and more satisfying jobs. An advantage that can be seen as a response to the talent shortage affecting the industry.

But that’s not all. By using purchase records from a large portfolio of customers, retailers can use predictive analysis to adapt their offers in real-time. For example, companies can define specific personas or offer personalized discounts. 

Benefit 2: Optimize Pricing

The analysis of supply and demand is a must for any business. In a hyper-competitive context, with tense consumer purchasing power, selling at the right price is an absolute necessity. One of the main guarantees of the use of data to optimize pricing is to preserve the attractiveness of the brand while protecting its margins.

This is even more critical for multi-site brands, spread over a vast territory. They must not only adapt their pricing based on customer expectations and behavior, but also to the competition in a given area – two major strategic levers for the retail industry.

Benefit 3: Innovate to Improve Products & Services

Under the effect of digitalization, consumer habits are evolving at a very fast pace. Brands must therefore constantly innovate. But innovating can be a risky and expensive process.

With data, retail players can rely on the knowledge they have on their customers’ preferences and expectations to define the roadmap for innovating their products and services. The challenge? Winning the race to constantly conquer new markets, while keeping the R&D budgets under control.

Benefit 4: Offer Personalized Shopping Experiences

Since the beginning of the COVID-19 crisis, the explosion of online shopping has attracted a population that used to shop in physical stores. To differentiate themselves, retail players must do everything they can to offer personalized shopping experiences.

Data is the basis of all personalization, especially for retailers who have embarked on the path of e-commerce. The ambition? To exploit the knowledge of on and off-line customers to harmonize experiences. Optimized and controlled data allows retailers to take advantage of the benefits of digital platforms while reinforcing the quality of in-store contact.

Benefit 5: Fluidify the Supply-Chain

One of the reasons why customers will visit a physical store rather than purchase a product online is to make physical contact with the said-product. In fashion for example, trying on a piece of clothing almost always makes the difference. In addition, having the possibility of leaving with one’s purchase without shipping delays is one of the most important factors for purchasing in a physical store.

Optimized inventory management, fluidity of supplies, control of logistics costs… It is crucial to ensure the excellence of data in order to guarantee the availability of products at the point of sale.

Blog | Data Management | June 3, 2022 | 4 min read

Technical Trifecta: The Future of Data Professionals

By Actian Corporation

#Data Management
Group of data professionals reviewing information in a digital environment

By Actian Corporation

#Data Management
In this post:

Data-driven roles are in demand. According to research firm Deloitte, the number of postings for positions in data science, data engineering, machine learning (ML), and visualization now surpasses those for more familiar skill sets such as customer service, marketing, and public relations (PR).

For database administrators (DBAs), business technologists, and data engineers, this increasing demand comes with the opportunity to explore new roles within their organization and expand existing skill sets to make better use of emerging technologies.

But what comes next? Beyond the growing need for skilled data staff, what does the future hold for this trifecta of technology professionals? How will these roles evolve over the next few years to align with the growing impact of cloud technologies, Internet of Things (IoT) deployments, and the increasing use of artificial intelligence (AI) and machine learning (ML) frameworks?

The Database Administrator: Delivering Dynamic Architecture

DBAs are responsible for managing, monitoring, and upkeep of SQL, NoSQL, Oracle, and other database environments. The advent of process automation and machine learning tools, however, has led to questions about the future of this role: If software tools can handle most of the heavy lifting when it comes to repetitive and error-prone tasks, where does that leave DBAs?

Moving forward, database administrators should expect a shift in priorities that sees them focusing on the dynamic nature of database architecting, capacity planning, and scaling to help businesses reliably access and leverage data across multiple clouds and on-premises instances. Put simply, the role of DBAs is shifting away from managing databases to assisting organizations in making the most of evolving and interconnected database architecture.

The Data Engineer: Abstracting the Source

Data engineers leverage their expertise to discover trends and develop new algorithms that help companies pinpoint actionable information within data sets. Historically, data sources defined the scope of this work—each unique source required its own set of processes and algorithms to facilitate effective data capture.

Consider user data stored across different databases. While the underlying asset—the user—remains the same in each case, disparate data sources meant different analysis models for each. Once extracted and formatted, data from different sets could then be combined to facilitate trend analysis and strategic decision-making.

The future of data engineering, however, is about abstracting the source. By leveraging both machine learning algorithms and AI frameworks, new engineering approaches are capable of capturing and understanding data in a way that’s set- and source-agnostic.

The Business Technologist: Finding Common Ground

Business technologists often have a combination of operations and development skills—for example, they may be data analytics experts who also have experience designing and building applications. This diversified expertise empowers technologists to help improve communication and collaboration across multiple departments. By functioning outside the traditional paradigm of IT, business technologists are better equipped to see the bigger picture and identify opportunities for increased efficiency.

The ongoing integration of IT into business processes at scale, however, sets the stage for an evolution of the business technologist role that broadens their communications strategy. This starts with the C-suite. To secure executive support and ensure appropriate funding for new IT projects, business technologies must now bridge the gap between technical and tactical communication to capture C-suite attention and encourage specific action.

There’s also a growing need for business technologists to cultivate connections with outside experts such as managed service providers. From data backup and disaster recovery solutions to on-demand data management platforms, there are now a host of solutions that can make business operations easier—if companies can pinpoint where they’re best used and how they can integrate with current operations.

The Evolving Future of Data Expertise

In the near term, data professionals will see increasing demand for their skills as businesses look to effectively leverage the volume, variety, and velocity of information produced across their networks.

Over the next few years, however, members of this technology trifecta should expect changes in their roles as technology continues to evolve. For DBAs, this means a move away from static management and monitoring to dynamic architecting and scaling. For data engineering staff, a shift to source-agnostic data analysis is on the horizon. And for business technologists, communication is key—not just across departments but outside traditional boundaries to leverage the potential of provider-driven expertise.

Blog | Data Platform | May 23, 2022 | 3 min read

The Customer Journey and the Role of Data

By Jennifer Jackson

#Cloud Data Warehouse
customer journey role data

By Jennifer Jackson

#Cloud Data Warehouse
In this post:

A typical buyer’s journey moves through distinct phases starting with Awareness, continuing on to Consideration, Purchase, and Onboarding/Post-Purchase, and hopefully ending in Advocacy. Much of the journey is carried out digitally – up to 67%, according to some estimates. Data breadcrumbs are left behind along a digital path, as people search online, sign up for activities, open emails, buy products, and post reviews. Each of these signals tells a story.

But how can marketers make sense of the story? That takes skill – and a helping hand from modern technology.

First, marketers do what they can to encourage customers to keep moving forward. They do this by feeding the types of content customers crave based on where they are in their journey. Each interaction gives marketers a chance to collect and interpret the digital signals – and the more signals, the better. As they pull mounds of data from all the different channels, apps, and information sources, marketers consolidate it into a single profile – often referred to as a 360-degree view of the customer. Once the resulting event table is established, organizations can respond more strategically with the appropriate message at the appropriate time in the right channel.

A Data Platform for a 360-Degree Customer Journey

A data platform integrates data from all sources and puts it in one place. This allows analysts to explore what’s there to ferret out patterns and trends. The insights generated can be put to good use, such as predicting buyer behavior, preventing churn, or recommending meaningful offers. This turns a run-of-the-mill customer experience into a positive engagement, personalized for each buyer’s journey.

Still, a data platform doesn’t just enable a 360-degree view – it opens up a whole new landscape for marketers. While customer data platforms, or CDPs, offer a view of the customer, a data platform like Actian gives you so much more. The same people, the same investment, the same data, and the same processes can be used to analyze other sets of data. This allows marketers to review other types of data – everything from financial to supply chain to support – and use it to enhance the customer experience.

The Actian Data Platform helps companies understand where customers are, and where they’re going. Using sophisticated analytics, companies can better interpret customer sentiment and intent when interacting with your brand and/or products, which can also be a valuable asset for other parts of the organization. Better insights can fuel product and service development, improve customer service, and make financial planning more efficient.

At Actian, we’re focused squarely on customer experience. We provide that integrated, 360-degree view that enables you to know your customers and respond to them in the most strategic way possible. With Actian Data Platform, you not only understand the customer journey, you make it memorable.

Blog | Data Intelligence | May 8, 2022 | 4 min read

What is Data Profiling?

By Actian Corporation

#Data #Data Intelligence
Businesswoman Looking At Contract Form Through Magnifying Glass

By Actian Corporation

#Data #Data Intelligence
In this post:

The purpose of any data project is to transform available data into valuable assets that will put your company on the path to excellence. To achieve this, data must be easy to discover and catalog. The objective is to make it not only accessible but above all understandable and exploitable for your employees who use it daily. One of the levers to achieve this is Data Profiling. Here are some explanations.

The very principle of a data strategy is to give your teams the means to rely on tangible, representative, and quality information to fulfill their missions. But raw data is not enough. Like a precious mineral, data must be methodically refined. One of the essential phases of making data speak is called Data Profiling. It is a process that relies on analyzing and exploring the available data to understand:

  • How they are structured.
  • The information it contains.
  • The relationships between different datasets.
  • How they could be associated, combined, and used more efficiently.

What are the Different Types of Data Profiling?

When you launch a data profiling process, you examine and analyze all of your data assets to determine their structure, nature, and possible combinations. In this way, you can identify the interdependencies between datasets to better make them talk. According to data experts, there are three types of Data Profiling: structure profiling, content profiling, and relationship profiling.

Structure Discovery

One of the key elements of data exploitation is its optimal organization. To do this, you need to look at the structures of the data. Structure profiling is the type of Data Profiling that ensures that the data is correctly formatted and consistent within a database. Structure Discovery or “structure profiling”, refers to a process of validating the format and consistency between datasets.

Content Discovery

Content discovery, or content profiling, is based on the analysis of rows of data to identify errors and systemic problems. For example, the most common use is to examine a list of customers to identify those with invalid email addresses. The goal is to highlight null or erroneous values so that they can be corrected as soon as possible.

Relationship Discovery

The third type of data profiling, called relationship discovery, is used to analyze and identify the relationships of data used between spreadsheets or database tables. To do this, you will need to perform a metadata analysis to detect possible connections between different data sources and identify overlaps.

The Benefits of Data Profiling

There are three main benefits of Data Profiling. The first is that it saves time before launching a data project. You can take an exploratory approach to determine whether the data you have will really enable you to gain the knowledge you need. Then, and only then, can you implement your project.

The second benefit of Data Profiling is that it improves data quality. Data Profiling ensures that your data is clean, accurate, and ready to be distributed throughout the organization.

Finally, Data Profiling allows you to expand the scope of what is possible. Your employees need to quickly and easily find specific types of data that can help them launch new projects or capture new markets. When data is not searchable, it can be difficult to locate it in a longer chain. With Data Profiling, data is better identified, categorized, and sorted. Your teams can then easily manipulate it and assemble it into databases using specific keywords.

By engaging in Data Profiling, you create the conditions for optimized exploitation of your data. Done methodically, Data Profiling is a promise of efficiency, relevance, and cost optimization, as it will allow your teams to save precious time and rationalize the exploitation of your data.

Blog | Actian Life | May 2, 2022 | 2 min read

Welcome to IMPACTIAN!

By Rae Coffman-Bueb

#Company Culture
new impactian logo

By Rae Coffman-Bueb

#Company Culture

It’s been said that we’re all living through unprecedented times. That’s why at Actian, we wanted to put a stake in the ground about how important it is for us to make a positive impact, not only for our customers and employees, but for our communities and society at large.

Today, we’re introducing IMPACTIAN, a new program to drive IMPACT at Actian and beyond. With a focus on corporate social responsibility (CSR) and doing good for our communities and society, Actian is kicking off this program by committing to three core areas:

  • Science, technology, engineering, and mathematics (STEM).
  • Food insecurity.
  • Climate and sustainability.

Through our CSR Program, we are excited to offer employees opportunities for donation matching and volunteer time off to support their philanthropic endeavors. We are eager and excited to champion our employees’ passions for helping those in need and supporting our communities. Whether it be $5 or $1,000, we urge all our employees to take advantage of our employee matching program to help us create a lasting impact.

To jump-start IMPACTIAN, Actian is proud to announce that, for the second consecutive year, we have donated a total of $10,000 to Girls Who Code in recognition of Women’s History Month and in alignment with our pillar of commitment to STEM! If you would like to join us in our commitment and are interested in donating to this organization, you can do so here.

Additionally, we have matched over $2,000 in efforts to support Ukraine relief, donating to organizations such as the Red Cross, Nothilfe für die Ukraine, Four Paws, LSVD, World Central Kitchen, and more.

We’re excited about what lies ahead for IMPACTIAN and can’t wait for you to join us on this journey.

Are you ready to make an impact on the world and change the face of data management and integration? Join our team of enthusiastic, talented minds in a diverse, collaborative environment where you can thrive and grow. Learn more about our career openings at https://www.actian.com/company/careers/.

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