Actian Life

A Look Inside the Actian Internship Program

Actian Corporation

May 16, 2023

Actian internships and careers

The Actian internship program offers an engaging, unique, and educational opportunity for college students to learn, expand their skill sets, and make connections in the data analytics industry. The program started in 2020, but is already proving to be successful for dozens of science, technology, engineering, and mathematics (STEM) students, as well as students in other disciplines such as marketing, human resources, and finance.

The 12-week program supports up-and-coming professionals while giving Actian staff the chance to interact with students who may be a good fit to work at the company after graduating.

Rae Coffman-Bueb, Director of Employee Experience for Actian, is proud of the program’s success. “Interns are the future,” they noted. “In order for us to support that, we bring in and shepherd new talent. Giving them experience in a real-world setting is incredibly important not only for interns but also for us as an organization.”

A Learning Experience That’s Truly Unique

Actian’s internship program lets students work on actual projects, which are then shared across the company. Projects range from program implementations to fixing bugs to conducting research.

“We have a really unique structure to our internship program,” Coffman explains. “Many organizations, when they bring on interns, just give them random, day-to-day activities that an employee in that role would have. But our internship program is project-based, so each intern is brought onto a large-scale project that they work on over the course of 12 weeks.”

The hands-on work lets interns experience what real-world jobs actually entail, and the learning is mutually beneficial. While the interns learn from Actian employees, the company learns about the latest technology and business approaches taught in colleges.

“From an intern’s perspective, their project is a really great thing to showcase on a resume because they can say, ‘I was able to accomplish this giant project in 12 weeks,’” Coffman said. “And as an organization, we have the benefit of being able to learn from the students who are coming in with cutting-edge technology and information and are able to apply that to our problems and programs. That’s a huge benefit overall.”

Building Skills and Confidence

“One thing across the board that students gain is at the end of the 12 weeks, they all present in our internship showcase. It’s a way for them to show the whole company the project they worked on,” Coffman said. “One of the things that Sara and I are both passionate about is managing neurodiversity. We use a lot of those principles and apply them to presentations and public speaking.”

Coffman-Bueb and Sara Lou, Employee Experience Specialist for Actian, work with interns to help them prepare for their presentations. This includes one-on-one coaching sessions to build their skills and confidence.

Actian employees at all levels of the organization are always impressed by the work the interns do, especially their presentations.

“Every year, the entire executive team and the whole company say they want to expand the program,” Coffman notes. “We hear, ‘We need more interns!’ People really look forward to the presentations and are excited about them.”

The Path from Intern to Highly Productive Employee

Mollie Kendall is a shining example of how the internship program benefits both participants and Actian. She worked as an intern during the summer of 2021. Her manager was Kimmah Lewis, Senior Director, Digital and Demand Generation.

“During my internship, I dabbled in a lot of areas inside of demand generation, like digital, SEO, and content creation and management. I was able to sit in on a lot of meetings and learn what each entails,” she said. “I liked that I got that peek into each and every part of demand gen. That’s not something you get in school. Classes don’t go into the level of detail I experienced as an intern. Learning on the job and hands-on work is so valuable and prepares you for what comes after graduation.”

Kendall, who had 15 years of experience running her own photography business, liked the experience so much that after the internship ended, she continued to work part-time at Actian while in college. After graduating from Texas State University in San Marcos in December 2021, she accepted a full-time offer and is now Actian’s Demand Generation Specialist. She also handles the company’s social media and content management.

Other former interns are also now working at Actian. This includes three people who participated in last summer’s program and recently accepted full-time offers.

Learning, Connecting, and Engaging

“Every intern has a buddy who teaches them the ropes and day-to-day activities and is their dedicated point of contact for all questions big and small,” Coffman said. “They also have a manager who is very involved and acts as a mentor, and Sara and I meet with the students every week. We help bridge the gap between managers, buddies, and students. We make sure everything is on track. If there are any deviations, we’re able to course correct and guide them back.”

Everyone involved in the program is dedicated to setting up the interns for success and making sure what’s asked of them is achievable. This support made a big impact on Kendall.

“Working with Kimmah Lewis was what impressed me the most,” Kendall said. “I never thought I would go into tech and go into social media, but Kimmah was great. I learned so much, and I had fun doing it. It was great to be part of the program.”

She is now working with an intern as part of her job. “I mentored an intern last year and will do so again this summer,” she said. “I want to help her learn and build her skill set. It was invaluable what Kimmah did for me, and I can give interns that perspective.”

One of the highlights for Kendall and other interns is the social aspect. For example, interns typically work remotely, so Actian sent each intern a package to make s’mores. Then in a group event, the interns got together virtually, made s’mores, and told ghost stories.

“The connections through games and activities really completed the experience for me,” Kendall said.

Career Opportunities at Actian

Interested in joining an exciting team? Actian is hiring. See our openings.

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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

The Top 5 Benefits of Data Lineage

Actian Corporation

May 15, 2023

Copy Space Of Abstract Background With Butterfly Growth Evolution Transformation Concept. Business Innovation, Technology Disruption

Do you have the ambition to turn your organization into a data-driven enterprise? You cannot escape the need to accurately map all your data assets, monitor their quality, and guarantee their reliability. Data lineage can help you accomplish this mission. Here are some explanations.

To know what data you use, what it means, where it comes from, and how reliable it is throughout its life cycle, you need a holistic view of everything that is likely to transform, modify, or alter it. This is exactly the mission that data lineage fulfills, which is a data analysis technique that allows you to follow the path of data from its source to its final use. A technique that has many benefits.

Benefit 1: Improved Data Governance

Data governance is a key issue for your business and for ensuring that your data strategy can deliver its full potential. By following the path of data, from its collection to its exploitation, data lineage allows you to understand where it comes from and the transformations it has undergone over time to create a rich and contextualized data ecosystem. This 360° view of your data assets guarantees reliable and quality data governance.

Benefit 2: More Reliable, Accurate, and Quality Data

As mentioned above, one of the key strengths of data lineage is its ability to trace the origin of data. However, another great benefit is its ability to identify the errors that occur during its transformation and manipulation. Hence, you can take measures to not only correct these errors but also ensure that they do not reoccur, ultimately improving the quality of your data assets. A logic of continuous improvement that is particularly effective for the success of your data strategy.

Benefit 3: Quick Impact Analysis

Data lineage accurately identifies data flows, making sure you never stay in the wrong for too long. The first phase is based on the detailed knowledge of your business processes and your available data sources. When critical data flows are identified and mapped, it is possible to quickly analyze the potential impacts of a given transformation on data or a business process. With the impacts of each data transformation assessed in real-time, you have all the information you need to identify the ways and means to mitigate the consequences. Visibility, traceability, reactivity – data lineage saves you precious time.

Benefit 4: More Context to the Data

As you probably understood by now, data lineage continuously monitors the course of your data assets. Therefore, beyond the original source of the data, you have full visibility of the transformations that have been applied to the data throughout its journey. This visibility also extends to the use that is made of the data within your various processes or through the applications deployed in your organization. This ultra-precise tracking of the history of interactions with data allows you to give more context to data in order to improve data quality, facilitate analysis and audits, and make more informed decisions based on accurate and complete information.

Benefit 5: Build (Even More) Reliable Compliance Reports

The main expectations of successful regulatory compliance are transparency and traceability. This is the core value promise of data lineage. By using data lineage, you have all the cards in your hand to reduce compliance risks, improve data quality, facilitate audits and verifications, and reinforce stakeholders’ confidence in the compliance reports produced.

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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 Analytics

What is Supply Chain Analytics?

Teresa Wingfield

May 11, 2023

worker assessing supply chain analytics

What is Supply Chain Analytics?

Supply chain analytics uses data and advanced analytics to analyze and optimize various aspects of the supply chain, including procurement, manufacturing, and logistics. The main goals of supply chain analytics are to improve efficiency, lower costs, and increase revenue. Supply chain analytics can also provide real-time insights that help businesses adjust to changing conditions quickly and effectively.

Using the power of supply chain analytics, you can ask the right questions, find the right answers, and realize the benefits of a well-optimized supply chain.

Frequently Asked Questions

There are four primary types of supply chain analytics: descriptive, diagnostic, predictive, and prescriptive. These advanced analytics techniques may sound complex, but you should find this simple business-level overview of what each type reveals with examples to be straightforward.

What Events Have Happened?

Descriptive analytics mines historical data to identify trends and relationships. Examples include identifying excess inventory and late deliveries.

Why Did These Events Happen?

Diagnostic analytics examines trends and correlations between variables to determine the root cause of a supply chain event. This type of analytics can diagnose events such as why there was too much stock and why deliveries were late.

What Might Happen in the Future?

Predictive analytics uses supply chain data to predict future outcomes, such as forecasting demand or anticipating possible transportation bottlenecks.

What Should We Do?

Prescriptive analytics uses data to prescribe the best course of action, such as decreasing production or using alternative shippers.

Benefits of Supply Chain Analytics

Answering these types of questions provides a myriad of benefits. Below are just a few of them:

  • Improved Efficiency and Cost Savings: Through using supply chain analytics to streamline processes, reduce waste and optimize operations. Examples include optimizing routes and schedules, reducing manufacturing downtime, using less fuel and better sourcing of materials, and many more opportunities.
  • Increased Visibility and Transparency: Allow organizations to identify potential problems early on and take proactive measures to address them.
  • Better Risk Management: By highlighting interdependencies and uncovering areas along the supply chain where disruption can lead to failure.
  • More Accurate Planning: Gain better insight into sourcing, manufacturing, and distribution to meet customer demand.
  • Better Customer Experience: Real-time insights into customer demand can improve how you manage inventory levels and ensure that products are in stock when customers want them.
  • Less Environmental Impact: Normalize analyzing energy consumption, waste, and other sustainability factors.

Getting Started

Supply chain analytics provides a data-driven way for businesses to optimize their operations, with its ability to provide real-time visibility, highlight risks, reduce costs and inefficiencies, better plan for customer demand, improve the customer experience, and reduce environmental impact.

To get started, you’ll need the right data platform to run your descriptive, diagnostic, predictive, and prescriptive supply chain analytics. Actian Data Platform can help you transform your supply chain, by simplifying how you connect, manage, and analyze data. Using the Actian Data Platform, you can easily aggregate and analyze massive amounts of supply chain data to gain data-driven insights in real-time, for optimizing supply chain operations.

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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.
Data Architecture

Embedded Databases Everywhere: Top 3 IoT Use Cases

Teresa Wingfield

May 9, 2023

numbers showing embedded databases and iot use cases

The rise of edge computing is fueling demand for embedded devices for Internet of Things (IoT). IoT describes physical objects with sensors, processing ability, software and other technologies that connect and exchange data with other devices and systems over the Internet or other communications networks. Diverse technologies such as real-time data analytics, machine learning, and automation tie in with IoT to provide insights across various edge-to-cloud use cases. 

It is not surprising that embedded databases are widely used for IoT given its explosive growth. International Data Corporation (IDC) estimates there will be 55.7 billion connected IoT devices (or “things”) by 2025, generating almost 80B zettabytes (ZB) of data. 

Our research reveals the top six use cases for embedded databases for IoT. Here, we will discuss the first 3: manufacturing, mobile and isolated environments, and medical devices.

Manufacturing

In fiercely competitive global markets, IoT-enabled manufacturers can get better visibility into their assets, processes, resources, and products. For example, connected machines used in smart manufacturing at factories help streamline operations, optimize productivity, and improve return on investment. Warehouse and inventory management can leverage real-time data analytics to source missing production inputs from an alternative supplier or to resolve a transportation bottleneck by using another shipper. Predictive maintenance using IoT can help identify and resolve potential problems with production-line equipment before they happen and spot bottlenecks and quality assurance issues faster.  

Mobile/Isolated Environments

IoT is driving the shift towards connected logistics, infrastructure, transportation, and other mobile/isolated use cases. In logistics, businesses use edge computing for route optimization and tracking vehicles and shipping containers. Gas and oil companies take advantage of IoT to monitor remote infrastructure such as pipelines and offshore rigs. In the transportation industry, aviation and automotive companies use IoT to improve the passenger experience and to improve safety and maintenance.  

Medical Devices

Healthcare is one of the industries that will benefit the most from IoT, given its direct connection with improving lives. IoT is recognized as one of the most promising technological advancements in healthcare analytics. Medical IoT devices are simultaneously improving patient outcomes and providers’ return on investment. The processing of medical images and laboratory equipment maintenance are particularly important use cases. Data from MRIs, CTs, ultrasounds, X-Rays, and other imaging machines help medical experts diagnose diseases at earlier stages and provide faster and more accurate results. Edge analytics enables predictive maintenance of laboratory equipment to reduce maintenance costs, but more importantly, to help prevent the failure of critical equipment that is often in short supply.  

What is possible today with IoT in healthcare was inconceivable a decade ago: tracking medications, their temperature, and safe transportation at any point in time. 

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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.
Data Intelligence

Enabling Data Literacy: 5 Ways a Data Catalog is Key

Actian Corporation

May 9, 2023

Laptop And Book Low Poly Vector Illustrating Data literacy

In today’s data-driven world, organizations from all industries are collecting vast amounts of data from various sources, including IoT, applications, and social media. This data explosion has created new opportunities for businesses to gain insights into their operations, customers, and markets. However, these opportunities can only be realized if organizations have a data-literate workforce that can understand and use data effectively.

Indeed, data literacy refers to the ability to read, understand, analyze, and interpret data. It is a crucial skill for individuals and organizations to stay competitive and make data-driven decisions. In fact, according to a recent study by Accenture, organizations that prioritize data literacy are more likely to be successful in their digital transformation initiatives.

To enable data literacy, organizations need to provide their employees with easy access to high-quality data that is well-organized, well-documented, and easy to use. This is where a data catalog comes in.

In this article, discover the 5 ways a data catalog enables successful data literacy in organizations.

A Quick Definition of Data Catalog

We define a data catalog as an organized inventory of an organization’s data ecosystem that provides a searchable interface to find, understand, and trust their data.

Indeed, created to unify all enterprise data, a data catalog enables data managers and users to improve productivity and efficiency when working with their data. In 2017, Gartner declared data catalogs as “the new black in data management and analytics”. And in “Augmented Data Catalogs: Now an Enterprise Must-Have for Data and Analytics Leaders,” they state: “The demand for data catalogs is soaring as organizations continue to struggle with finding, inventorying, and analyzing vastly distributed and diverse data assets.”

A data catalog is, therefore, a crucial component in an organization’s data literacy journey. Let’s see how.

1. A Data Catalog Centralizes all Data into a Single Source of Truth

A data catalog automatically collects and updates all enterprise data from across your various sources into a single repository to help create a comprehensive view of an organization’s data landscape. By indexing your organization’s metadata, data catalogs increase data visibility and enable data and business users to easily find their information across multiple systems.

This boosts data literacy for organizations as data catalogs help break down silos between different departments and teams by providing a single, searchable repository of all available data assets. Indeed, with a data catalog, no technical expertise is required to access and understand a company’s data ecosystem: organizations can easily collaborate and share their information assets in a single platform.

2. A Data Catalog Increases Data Knowledge via Documentation Capabilities

Data catalogs enable the increase of enterprise-wide data knowledge via the automation of documentation capabilities. By providing data producers with documentation features, users get descriptive information about their data assets, such as their purpose, usage, and relevance to business processes. With comprehensive documentation capabilities in a data catalog, data users can easily understand and use data assets, ultimately promoting data literacy across the organization.

By ensuring that documentation is accurate, consistent, and up-to-date, organizations with data catalogs can reduce the risk of data errors and inconsistencies. This leads to more reliable data, which is essential for informed decision-making and better business outcomes.

3. A Data Catalog Provides Powerful Data Discoverability

Data discovery is the process of exploring and analyzing data in order to gain insights and uncover hidden patterns or relationships. This must-have data catalog feature promotes data literacy by providing users with a better understanding of the data they are working with and encouraging them to ask questions and explore the data in more depth.

With data discoverability features, a data catalog helps users identify patterns and trends in the data. By visualizing data in different ways, users can identify correlations, outliers, and other patterns that may not be immediately apparent in raw data. This can help users to gain new insights and develop a deeper understanding of the data they are working with.

4. A Data Catalog Provides a Common Data Vocabulary via a Business Glossary

A business glossary is a key component of a data catalog that provides a common language and understanding of business terms and definitions across the organization. A business glossary defines the meaning of key business terms and concepts, which enables data users to understand the context and relevance of the data they are working with.

This, in turn, promotes data literacy across the organization. Data catalogs, therefore, help data teams avoid data misunderstandings and maximize trust in enterprise data.

5. A Data Catalog Provides Powerful Lineage Features

Data lineage provides a clear understanding of the origin and transformation of data, which is essential for understanding how data is used and how it relates to other data assets. This information is essential for data management initiatives, as it helps to ensure data accuracy, reliability, and compliance.

By tracing data from its source to its destination, data lineage boosts data literacy by providing users with information about the purpose of the data, the business processes that use the data, and the dependencies that exist between different data assets. This information can help users to understand the relevance and importance of the data they are working with, and how it fits into the broader context of the organization. Data lineage can also help identify any anomalies, inconsistencies, or data quality issues that may affect the accuracy or reliability of the data.

Conclusion

In conclusion, data catalogs are a powerful tool for promoting data literacy within organizations. By centralizing data and metadata, providing access to data lineage information, and offering data discovery capabilities, data catalogs can make it easier for users to find and understand the data they work with, and are key for a data literate organization.

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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.
Actian Life

Actian Employees Give Back for Earth Day

Actian Corporation

May 4, 2023

Actian Hamburg team giving back for Earth Day

As a company that strongly believes in making human connections and embracing corporate social responsibility, Actian supports employees who volunteer their time and talents to help their communities. Our staff members around the globe are using volunteer time off to inspire positive change by building stronger communities.

For example, many of our employees recently took volunteer time off to participate in Earth Day activities. Actian organized events in various locations and encouraged all employees to participate in volunteer projects that helped and inspired others.

Organized events included:

Unity Park Community Garden, Round Rock, Texas

Actian employees helped improve the look and vibe of the garden by assisting with tasks such as weeding, gardening, and laying down mulch in the first community garden in the city of Round Rock. The community garden provides a local organic food supply, stewardship for land and water resources, a place to learn, and more.

“I had a great time working with Unity Park Community Garden in Round Rock for Earth Day,” said Siobhan Mulhern, Actian Executive Assistant. “The head gardener, Les, was helpful and knowledgeable and got us working quickly—while giving us all a few gardening tips.”

The garden offers 44 plots of various sizes for gardeners of all skill levels. The all-organic community garden grows produce for the Round Rock Serving Center and shares the latest organic gardening practices.

“Learning about how much organic produce they grow to donate to local food pantries made our tiny contribution of a few hours’ work feel more meaningful, and I intend to be involved going forward,” Mulhern said.

Hayling Island Beach, United Kingdom

Hayling Island Beach has more than three miles of beaches along the seafront in the county of Hampshire. Actian employees helped keep the beach clean by picking up trash. “We met on Hayling Island beach and walked east and picked up litter along the way,” said Karen Langridge, Regional Sales Director, Actian.

Ilmenau, Germany

Actian employees in Germany volunteered their time to collect garbage in nearby parks to contribute to a cleaner environment. Actian volunteers were encouraged to see that people are taking responsibility for their surroundings and making use of the numerous garbage cans to ensure that nature stays unblemished. The team, therefore, took its activity to an area closer to the city, near the market that takes place twice a week. There, the volunteers discovered their help was urgently needed—so much so that after three hours of collecting garbage, there was still a lot more to do!

The team believes that every day should be Earth Day. That’s because we all need to contribute to keeping our environment clean and healthy for everyone, for the entire year.

Looking for an Exciting Career?
If you’re passionate about data and want to help advance the world of data and analytics, join our team of enthusiastic and talented employees who encourage you to thrive, grow, and learn.

See our current job openings and learn more about our company culture.

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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

Data Literacy: The Must-Have Skill for Remote Workers

Actian Corporation

May 4, 2023

data literacy in remote work

The COVID-19 pandemic has forced organizations worldwide to adopt remote work as the new norm. In fact, according to McKinsey & Company, the pandemic accelerated remote work, with up to 25 percent more workers than previously estimated needing to switch occupations. And in a world with increasing numbers of remote workers, the need for data-driven decision-making has become more crucial than ever before.

However, with remote work comes a new set of challenges for data-driven enterprises. To make informed decisions, remote workers need to understand, analyze, and interpret their data accurately. As a result, data literacy has become an essential skill for workers to succeed in a remote work environment.

In this article, we will explore the importance of data literacy in a world working remote, its advantages and challenges, and some best practices to adopt for implementing data literacy for remote work.

The Importance of Data Literacy

Let’s briefly define data literacy. Data literacy is the ability to understand, analyze, and communicate around data. Indeed, in today’s fast-paced and data-driven environment, data literacy enables individuals to better understand the data they work with, analyze it critically, and make informed decisions based on the insights gained from the data.

The importance of data literacy in today’s workforce, therefore, cannot be overstated. The amount of data being generated by organizations is growing exponentially, and the ability to access, analyze, and interpret data is vital to making informed business decisions. With the right data literacy skills, employees can turn raw data into actionable insights that help them identify patterns and trends to achieve their strategic and business goals.

The Challenges of Becoming Data Literate When Working Remotely

With remote work, employees are not physically present in the same location as their colleagues or data sources. Therefore, remote workers need to be able to access, analyze, and interpret data independently, without relying on face-to-face interactions. Data literacy is crucial in ensuring that remote workers can effectively navigate data and use it as well as be able to communicate data effectively to their colleagues, which is essential for collaboration in a remote work environment. With the lack of face-to-face interactions, remote workers may not receive the necessary guidance or support to build their data literacy skills.

Another key challenge is the lack of access to their data sources. Remote workers need to be able to access data sources quickly and easily to be able to analyze their information. In addition, remote workers may also face challenges in terms of data security and protection. Therefore, efficient data management and analysis are critical in ensuring that remote workers can access and use data securely and effectively.

Finally, many organizations that aim to become data literate lack the appropriate data management tools. Without the appropriate solutions, it can be difficult to collect, organize, and analyze data in an effective manner. In addition, data users lack context on their data, leading to a siloed and incomplete understanding of their data. Having the right data management tools, such as data visualization software, data cataloging solutions, and data discovery platforms, can help data teams to better comprehend their data and gain deeper insights, leading to a more successful journey towards data literacy.

The Advantages of Data Literacy for Remote Workers

When implemented effectively, data literacy has many benefits for remote workers.

First, data literacy enables remote workers to communicate and collaborate effectively with their colleagues. By understanding and analyzing data, remote workers can share their insights and findings with their colleagues, leading to better decision-making and outcomes. Additionally, data literacy enables remote workers to present data in a clear and concise manner, making it easier for others to understand and act upon the insights presented.

Second, data literacy can improve productivity and efficiency and can access, analyze, and interpret data quickly and accurately, enabling them to complete tasks more efficiently. By leveraging data insights, remote workers can identify patterns, trends, and anomalies in data, which can help them prioritize tasks, optimize processes, and achieve their goals more effectively.

Finally, data literacy can help reduce errors and risks in a remote work environment. By analyzing and interpreting data accurately, remote workers can identify potential errors or risks before they occur, allowing them to take proactive measures to mitigate them. Additionally, being data literate reduces the likelihood of making decisions based on assumptions or incomplete information. By leveraging data insights, remote workers can ensure that their decisions are informed, objective, and aligned with organizational goals.

Tips on Creating a Data Literate Environment for Remote Workers

Building data literacy skills in a remote work environment can be challenging, but there are several strategies that can be employed to develop these skills.

One of those solutions is to provide online training and resources for remote workers to build their data literacy skills. Online training modules, courses, and webinars can help remote workers develop their skills in data analysis, interpretation, and presentation. In addition, providing access to online resources such as data visualization tools, dashboards, and analytics platforms can enable remote workers to explore and analyze data independently.

Another strategy for building data literacy skills in a remote work environment is to incorporate data literacy into the remote work culture. Encouraging remote workers to share their data insights and findings with their colleagues can foster a culture of collaboration and knowledge-sharing, promoting the development of data literacy skills across the organization.

The Future of Data Literacy in Remote Working

As data becomes more prevalent in remote work, the need for remote workers to develop and maintain their data literacy skills will become increasingly important. By investing in continuous learning and upskilling in data literacy, remote workers can effectively leverage data insights to make informed decisions, improve productivity, and reduce errors and risks.

We are convinced that data literacy is an essential skill to master for any data-driven organization. This is why we developed a next-generation data discovery platform for all data and business initiatives from metadata management applications from search and exploration to data governance, compliance, and cloud transformation initiatives.

Are you ready to unlock the potential of data for your remote workers? Contact us.

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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 Analytics

Do You Need AI to Transform Your Supply Chain?

Teresa Wingfield

May 2, 2023

ai transforming your supply chain

I recently shared a blog called “The Power of Real-Time Supply Chain Analytics” that discusses how manufacturers can use real-time supply chain analytics to reinvent their supply chain across sourcing, processing, and distribution of goods. Its focus is mostly on understanding events as they unfold in real-time. This time around, I’m providing an overview of using predictive analytics to understand what will happen in the future.  

As a subset of Artificial Intelligence (AI), predictive analytics makes predictions about future outcomes using historical data. Predictive analytics also helps businesses transform their supply chain to increase efficiency, reduce risk, and grow revenue. Let’s look at four areas in which predictive analytics can revolutionize the supply chain: demand forecasting, procurement, supply chain risk management, and customer experience.   

Demand Forecasting

Demand forecasting in supply chain management refers tothe process of planning or predicting the demand of materials to ensure delivery of the right products in the right quantities at the right time to satisfy customer demand, without creating excess inventory. 

The benefits of being able to anticipate customer needs and buying behavior are tremendous. With this knowledge, manufacturers can better ensure that they have the right levels of inventory, plan for the optimal production schedule, and obtain the most cost-effective and efficient logistics. An accurate demand forecast can also help businesses determine the best price to charge for their product to make the most profit.  

Intelligent Procurement

Manufacturers that implement intelligent procurement can gain better insight into and control over their spending and sourcing higher quality production components. Using predictive analytics, purchasing departments have a better understanding of what, where, and when to source based on their past purchases, commodity prices, and other industry trends.  

Supply Chain Risk Management

Supply chain risk management is the implementation of strategies to manage everyday and exceptional risks along the supply chain based on continuous risk assessment with the objective of reducing vulnerability and ensuring continuity.  

While there are many market disruptions that are typically unpredictable, such as natural disasters, pandemics, and cyber and terrorist attacks, there are many risks that can be forecast. Manufacturers can apply predictive analytics to their data for early detection and remediation of:  

  • Equipment and product issues at factories.
  • Capacity constraints at warehouses.
  • Late deliveries by logistics providers.
  • Financial distress of supplies and customers.  

Customer Experience

Delivering a great customer experience entails timely delivery of quality goods and keeping customers informed. The sooner a manufacturer can see a potential disruption to its supply chain, the faster it can react to avoid the interruption or at least lessen its impact. Even when the manufacturer can’t prevent the disruption, it can warn its customers of issues so that they aren’t blind sighted at the last minute. 

Your Bottom-Line Deserves AI

A manufacturer does indeed need AI to optimize its supply chain. By using predictive analytics to optimize inventory levels, sourcing, transportation routes, and many other aspects of the supply chain, manufacturers can improve their bottom-line and provide better service to their customers.  

Interested in more information? You can learn more about how Actian’s solutions are used in manufacturing and review this related blog for further details on real-time supply chain analytics.

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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.
Data Analytics

Using Cloud Data Analytics to Drive Engagement

Traci Curran

April 27, 2023

cloud data analytics in a warehouse of servers

The decisions a business makes to help drive revenue and increase customer loyalty are only as good as the available data being referenced. Given the state of consumer demands and the changing ways they prefer to interact with brands, now is a crucial time for businesses to take stock of their cloud data analytics strategies. If data in the cloud isn’t being effectively integrated into the enterprise for analysis and insights, then meaningful business decisions cannot be made accurately. 

Customers are now taking their buying experiences more seriously than ever before. Nearly three-quarters of US consumers rank their experience dealing with a business as being important to their buying decisions. A large majority (86%) say they’d even pay more if it meant getting a better customer experience (CX) out of it. 

For businesses, this means that learning as much as possible about customers and getting their buying experience right is the #1 priority. Combining the power of modern-day analytics with the flexibility offered by the cloud can help businesses generate the real-time insights needed to grow and develop CX. Understanding a customer through data requires a thoughtful approach to cloud data analytics and how to effectively harness data for maximum output.  

Cloud Data Analytics, Explained

The phrase “cloud data analytics” can mean many things to many different businesses, but broadly speaking, it’s all about using data to make smarter decisions to retain customers and win new ones. In some cases, it may refer to the way customer information is gathered to profile a new target sector. In other cases, it may refer to the way a business pinpoints where a customer is on their customer lifecycle and how they’ve engaged with a brand. 

However, the goal of cloud data analytics is to paint a holistic image of how to best reach the audiences that are needed to push the business forward. The use and application of these analytics have surged within the past few years. The rise of social media in the past decade has created groundswells of data on consumer feedback, with sites like Facebook and Instagram providing spaces for customers to describe their experiences with brands. Similarly, aggregator sites like G2 Crowd and Quora allow for reviews and direct questions to be asked to and about companies. 

Businesses can leverage this data for their analytics in several ways, but perhaps the most important gain is using those insights to improve marketing and advertising campaigns. Consumers want personalization more than ever when interacting with businesses, and the insights generated from existing customer data can help make that personalization a reality.  

Understanding a consumer’s buying history and behavior can better help marketers choose the messaging that will resonate best with that customer and hopefully retain them. The need for personalization here cannot be overstated – competitive businesses must know their customers.  

I’m sure that we’ve all gotten offers from companies after visiting their website or buying a product. If a consumer buys a set of sheets online from a major retailer, the next email they receive should probably be for a sale on comforters, not refrigerators. Too many irrelevant offers, and your customers will begin to view little value in your communications and unsubscribe, meaning losing opportunities to attain leads. 

Cloud data analytics can also help organizations meet consumers where they are and on the channels they prefer. As mentioned, the near-ubiquitous use of social media in recent years has ushered in a new wave of opportunities for marketers to meet consumers on these platforms. Leveraging data in the cloud for analytics can help organizations build up an effective social media strategy, one that offers insights into the way customers are using these platforms. Given the nature of today’s interconnected world, social media represents a huge chance for marketers to meet their customers on familiar ground. 

Moving Up to the Cloud

Before a cloud data analytics strategy can get off the ground, the data being used needs to be clean, secure and easily accessible in infrastructure that can scale with today’s data growth. Traditional storage setups like on-premises data warehouses may have a role in today’s enterprise tech stack, but they can’t keep pace with the explosive growth of data from marketing applications. This means businesses still using legacy data centers should consider a move to the cloud for data storage.  

By leveraging a cloud storage model, users can dynamically scale their warehouses according to their business needs. Cloud data warehouses also ensure that the datasets stored inside of them are structured, compliant with regulatory standards, accurate, and accessible to any team that needs access. Furthermore, cloud-based warehouse architectures are significantly speedier than their on-premises counterparts, so you gain access to customer data quickly and efficiently – allowing you to meet customer demands as they happen. 

Perhaps most important, by leveraging the elasticity of the cloud, you have a more cost-effective way to handle spikes in business activity. Seasonality, market changes, and changes in current events can be addressed immediately, instead of wasting time waiting on infrastructure provisioning to accommodate the change in demand. This is particularly true when that demand is unforeseen, like we witnessed during the early days of the pandemic. 

Putting It All to Use

Now that the goals of a customer data analytics strategy have been identified and the data has been moved to the cloud, a business can then begin using the data for analysis. Here are some key ways to leverage data to connect with customers: 

Find Areas of Opportunity

It’s important to know your customers as intimately as possible, including their likes, dislikes and needs. The more you know about your customer base, the better you can pinpoint areas of opportunity within your company. The more opportunities you find, the higher chance you have of meeting those needs and making a sale. 

Keep an Eye on Customer Sentiment

There are more channels than ever for customers to leave product reviews, ask questions, and engage in conversations surrounding your products. A large portion of those channels will not be within your control, but by leveraging the data from these places, you can not only respond to customers where they are, but over time gain a bird’s eye view of customer sentiment as well – both good and bad. The trends you uncover will help your product teams to address areas of improvement and help your marketing teams to zero in on clear value propositions. 

Get Early Warning Signs Before They Happen

One of the most important benefits of customer data analytics is being able to see early warning signs before shifts in behavior happen. Whether that means a dip in sales or a shift in sentiment from customers, getting ahead of changes can give you more time to react and address issues before they impact your goals. Being able to take preemptive action will allow you to do some damage control before it becomes an irreversible issue for your company. Effectively leveraging cloud data analytics can be a major influence on how businesses drive CX and secure revenue. Access to clean data that can be easily shared can unlock new insights on customers and how to keep them coming back for more. 

For more information on how the Actian Data Platform can help you better connect your cloud data for real-time analytics, check out our blog. 

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About Traci Curran

Traci Curran is Director of Product Marketing at Actian, focusing on the Actian Data Platform. With 20+ years in tech marketing, Traci has led launches at startups and established enterprises like CloudBolt Software. She specializes in communicating how digital transformation and cloud technologies drive competitive advantage. Traci's articles on the Actian blog demonstrate how to leverage the Data Platform for agile innovation. Explore her posts to accelerate your data initiatives.
Data Analytics

Best Practices for Using Data to Optimize Your Supply Chain

Teresa Wingfield

April 25, 2023

plane and truck showing supply chain optimization

When a company is data-driven, it makes strategic decisions based on data analysis and interpretation rather than mere intuition. A data-driven approach to supply chain management is the key to building a strong supply chain, one that’s efficient, resilient, and can easily adapt to changing business conditions.  

How to Optimize Your Supply Chain:     

1. Build a Data-Driven Culture

Transitioning to a data-driven approach requires a cultural change where leadership views data as valuable, creates greater awareness of what it means to be data-driven, and develops and communicates a well-defined strategy with buy-in from all levels of the organization.  

2. Identify Priority Business Use Cases

The good news is that there are a lot of opportunities to use supply chain analytics to optimize your supply chain across sourcing, processing, and distribution of goods. But you’ll have to start somewhere and should prioritize opportunities that will generate the greatest benefits for your business and that are solvable with the types of data and skills available in your organization.  

3. Define Success Criteria

After you’ve decided which use cases will add the most value, you’ll need to define what your business hopes to achieve and the key performance indicators (KPIs) you’ll use to continuously measure your progress. Your KPIs might track things such as manufacturing downtime, labor costs, and on-time delivery.  

4. Invest in a Data Platform

You’ll need a solution that includes integration, management, and analytics and that supports real-time insights into what’s happening across your supply chain. The platform will also need to be highly scalable to accommodate what can be massive amounts of supply chain data.  

5. Use Advanced Analytics

Artificial intelligence techniques such as machine learning power predictive analytics to identify patterns and trends in data. Insights help manufacturers optimize various aspects of the supply chain, including inventory levels, procurement, transportation routes, and many other activities. Artificial intelligence uncovers insights that can allow manufacturers to improve their bottom line and provide better customer service.  

6. Collaborate With Suppliers and Partners

Sharing data and insights can help develop strategies aimed at improving supply chain efficiency and developing innovative products and services.  

7. Train and Educate Employees

The more your teams know about advanced analytics techniques, especially artificial intelligence, and how to use and interpret data, the more value you can derive from your supply chain data. Plus, with demand for analytics skills far exceeding supply, manufacturers will need to make full use of the talent pool they already have.  

Learn More

Hopefully, you’ve found these best practices for using data to optimize your supply chain useful and actionable. Here’s my recommended reading list if you’d like to learn more about data-driven business and technologies:   

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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.
Data Analytics

6 Things You Must Know About Data Modernization

Teresa Wingfield

April 21, 2023

laptop showing a cloud for data modernization and data analytics

Data is the heart of digital transformation and the digital+ economy. Data modernization moves data from siloed legacy systems to the digital world to help organizations optimize their use of data as a strategic asset. For a successful data modernization journey, the following are some important things you need to know: 

1. Data Strategy

A data strategy lays out your plan to improve how your business acquires, stores, manages, uses, and shares data. The creation of a strategy, according to McKinsey, ranks as the top reason for companies’ success in data and analytics. Your data strategy should include your vision, business objectives, use cases, goals, and ways to measure success. 

2. Data Architecture and Technologies

To improve access to information that empowers “next best action” decisions, you will need to transfer your data from outdated or siloed legacy databases in your on-premises data center to a modern cloud data platform. Gartner says that more than 85% of organizations will embrace a cloud-first principle by 2025 and will not be able to fully execute their digital strategies without the use of cloud-native architectures and technologies. For successful data modernization, your cloud data platform must be a cloud-native solution to provide the scalability, elasticity, resiliency, automation, and accessibility needed to accelerate cycles of innovation and support real-time data-driven decisions.  

3. Data Analytics

Another important part of data modernization is data analytics. Traditional business tools aren’t enough to support modern data needs. Advanced analytics such as predictive modeling, statistical methods, and machine learning are needed to forecast trends and predict events. Further, embedding analytics directly within applications and tools helps users better understand and use data since it’s in the context of their work.    

4. Data Quality

Quality matters a lot in data modernization because users who rely on data to help them make important business decisions need to know that they can trust its integrity. Data should be accurate, complete, consistent, reliable, and up-to-date. A collaborative approach to data quality across the organization increases knowledge sharing and transparency regarding how data is stored and used.   

5. Data Security 

Strong data security is the foundation for protecting modern cloud data platforms. It includes safeguards and countermeasures to prevent, detect, counteract, or minimize security risks. In addition to security controls to keep your data safe, including user authentication, access control, role separation, and encryption, you’ll need to protect cloud services using isolation, a single tenant architecture, a key management service, federated identity/single sign-on, and end-to-end data encryption.  

6. Data Governance

Data governance determines the appropriate storage, use, handling, and availability of data. As your data modernization initiative democratizes data, you’ll need to protect privacy, comply with regulations, and ensure ethical use. This requires fine-grained techniques to prevent inappropriate access to personally identifiable information (PII), sensitive personal information, and commercially sensitive data, while still allowing visibility to data attributes a worker needs. 

Make Modernization Easier

 Your modernization journey depends on a cloud data platform that eliminates internal data silos and supports cloud-native technologies. You’ll also need to choose the right data analytics tools, ensure that your data is trustworthy and implement solid data and cloud security and data governance. The Actian Data Platform can help make your digital transformation easier with proven data integration, data management, and data analytics services. Learn more about how Actian Data Platform accelerates data modernization so you can deliver today while building your digital future.  

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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.
Actian Life

Steffen Kläbe Wins Best Paper at 2023 EDBT/ICDT Conference

Actian Corporation

April 19, 2023

Steffen wins best paper at conference

We’d like to recognize Steffen Kläbe, a Research Engineer at Actian in llmenau (Thuringia, Germany). He attended the 2023 joint conference by EDBT/ICDT in Greece, one of the top database conferences worldwide, where he presented two research papers. For his research on Patched Multi-Key Partitioning for Robust Query Performance he received an award for Best Paper. In the research community, this award is quite a success.

View The Abstract: 

“Data partitioning is the key for parallel query processing in modern analytical database systems. Choosing the right partitioning key for a given dataset is a difficult task and crucial for query performance. Real world data warehouses contain a large amount of tables connected in complex schemes resulting in an overwhelming amount of partition key candidates. In this paper, we present the approach of patched multi-key partitioning, allowing to define multiple partition keys simultaneously without data replication. The key idea is to map the relational table partitioning problem to a graph partition problem in order to use existing graph partitioning algorithms to find connectivity components in the data and maintain exceptions (patches) to the partitioning separately. We show that patched multi-key partitioning offer opportunities for achieving robust query performance, i.e. reaching reasonably good performance for many queries instead of optimal performance for only a few queries.” 

Kläbe’s additional paper Exploration of Approaches for In-Database ML covers the increasing role of integrating ML models with specialized frameworks for classification or prediction. 

View The Abstract:

“Database systems are no longer used only for the storage of plain structured data and basic analyses. An increasing role is also played by the integration of ML models, e.g., neural networks with specialized frameworks, and their use for classification or prediction. However, using such models on data stored in a database system might require downloading the data and performing the computations outside. In this paper, we evaluate approaches for integrating the ML inference step as a special query operator – the ModelJoin. We explore several options for this integration on different abstraction levels: relational representation of the models as well as SQL queries for inference, the use of UDFs, the use of APIs to existing ML runtimes and a native implementation of the ModelJoin as a query operator supporting both CPU and GPU execution. Our evaluation results show that integrating ML runtimes over APIs perform similarly to a native operator while being generic to support arbitrary model types. The solution of relational representation and SQL queries is most portable and works well for smaller inputs without any changes needed in the database engine.”

Congratulations, Steffan! We look forward to seeing more of your wins and research in the future. 

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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.