5 Best Practices to Help You Reap the Benefits of Data Democratization

Born out of the necessity to leverage more value out of Big Data, data democratization is an approach that allows data to pass from the hands of a few data analysts into the hands of business users.

With a data democratization strategy in place, every user in the organization, regardless of their technical prowess, can have access to data for timely and more insightful decision-making. This, in turn, helps analysts spend more time using data and less time finding it. However, even when an organization wants to empower every employee with easy access to data, there can be several infrastructure, culture, and governance-related impediments to making data available freely to them.

In this blog, we have listed 5 best practices that a business can adopt to overcome these challenges and establish enterprise-wide data democracy.

1. Gain an Understanding of the Entire Data Ecosystem

As an organization grows, so do the volume, variety, and velocity of incoming data and the challenges associated with managing it. Information becomes siloed in systems and is accessible by relevant teams only, thereby offering a myopic vision of the data space to users.

In-depth understanding of the data ecosystem and the fragmented systems that comprise it is integral to designing an integrated data space that offers all the users a holistic view of the information assets, along with the metadata and context they need to feel more confident about the relevance and trustworthiness of data.

2. Make Data Available to Everyone

In most organizations, data integration and analysis tools sit with IT departments who act as the gatekeepers of data, with business users at the mercy of data scientists to gain access to relevant data for BI and analytics. This can result in a data management process that is slow, frictional, and highly IT-reliant.

For businesses that wish to benefit from data democratization, it is essential to invest in data integration and analysis tools that offer the same usability and performance to everyone from developers to the end-user with limited technical knowledge.

3. Tame Your Legacy Data

Data democratization is not just about making fresh data accessible for analysis and reporting. It also involves liberating the data trapped within legacy systems for answering questions that were not contemplated by people who originally collected this information.

However, legacy systems are inherently inflexible and can hamper the data democratization efforts of any organization. To overcome the challenge and integrate legacy data into modern infrastructures, businesses must invest in data integration tools that offer instant API connectivity to not only popular databases but also cloud-based systems and applications to ensure interoperability.

4. Empower Users with Self-Service Analytics

For organizations to reap the full benefits of data democratization, they must empower their users to not only access data but also make data analysis and reporting part of day-to-day operations.

Although data integration and BI tools and technologies have evolved greatly over the past few years, finding a data management platform that facilitates access, analysis, and reporting of data in highly consumable ways remains an ongoing quest for most enterprises.

The solution to the problem lies in finding a data integration solution that lets you take advantage of the data the resides in previously disconnected systems, offers out-of-the-box connectivity to BI and analytics tools, as well as allows employees without technical knowledge to easily manipulate and analyze data.

5. Train Employees on How to Best Use Data

Data governance go hand in hand with data democratization, and lack of a data governance plan can quickly result in information overload, poor decisions, and reputational risk. To avoid these demerits of data democratization, everyone in the organization should be trained on how to best use the data, importance of understanding data lineage, and how it can be transformed for BI and analytics.

By taking these steps to democratize data, you can dramatically increase the value your business extracts from information assets and make data your basis of competitive differentiation.

data democratization infographics download

Common Challenges of COBOL Data Extraction and How Centerprise Addresses Them

Although technologies like Ruby, Hadoop, and Cloud Computing continue to dominate headlines, there are still a large number of businesses that rely on legacy technologies. Many businesses, particularly those operating in the banking and insurance sector, use solutions that are COBOL-based.

According to Reuters, over 220 billion lines of COBOL code are in use today. As a result, a tremendous amount of data remains tied up in legacy systems. For any legacy modernization and BI initiative to be successful, it is important that this data must be integrated, transformed, and offloaded onto an analytics platform.

While extracting data from COBOL-based legacy applications is essential for improved decision-making, it remains a challenge for most businesses due to two primary reasons:

  • Shortage of COBOL Skills

There is a growing gap between the number of skilled COBOL programmers and organizations relying on the programming language. The average age of COBOL programmers is 55 years, and 70 percent of universities are favoring fancy languages like Java, C++, Linux, and UNIX over COBOL.

  • Need for Custom Programming

Analyzing data by directly querying the mainframe is a complex process. It requires custom development and therefore can be time-consuming and costly, with billing based on MIPS.

To addresses these two challenges, businesses need a solution that can fuel their data integration efforts, while ensuring data quality and reducing the need for hand-coding the processes.

How Centerprise Facilitates COBOL Data Extraction

Centerprise is a complete data integration solution that allows users to import data from a variety of sources, including legacy systems, transform it and write it to a destination of their choice. With its user-friendly, drag-and-drop interface and unparalleled data mapping capabilities, Centerprise makes the process of extracting data from COBOL-based systems simple, quick, and cost-effective.

cobol data extraction, legacy modernization

Centerprise offers complete support for COBOL data extraction with the functionality to:

  • Read a COBOL File — Centerprise features a high-speed COBOL file reader that can efficiently process large COBOL files.
  • Parse a Copybook — The built-in copybook parser reads a COBOL copybook and automatically builds the layout. When a copybook is not available, users can import a COBOL data file as a fixed length file and manually define field markers, data types, and numeric formats.
  • Identify USAGE, REDEFINES, and OCCURS — Centerprise offers support for different clauses used in a COBOL data file, including REDEFINES, OCCURS, and USAGE, such as COMP, COMP-3, COMP-5.

Once a COBOL data file has been imported, users can leverage the code-free, drag-and-drop environment of Centerprise to transform and write data to a destination of their choice.

Download our whitepaper to learn how Centerprise can help you combine legacy COBOL data with modern data streams and get a unified view of your information assets.