By Emily Washington, Senior Vice President of Product Management at Infogix.

Harnessing big data and its environments can be a complex challenge. Data is constantly in motion, flowing along the data supply chain as it is ingested, created, transformed and leveraged for business use and analytical insights. As data moves across various systems, processes and environments, its integrity is always at risk. Questionable data quality can discourage data users from using data or—worse yet—it can result in inaccurate and unreliable insights when applied.

The primary consumers of data in every organization are business users. They need accurate, complete, consistent and reliable data to make meaningful business decisions. Basing business determinations on bad data can result in a diminished bottom line, negative customer experiences, tarnished reputation and falling behind the competition. However, by giving business users easy access to dependable data through self-service data governance tools and technology, business users can reduce their reliance on IT and grow into knowledgeable and capable data consumers.

The Breakthroughs of Modern Data Governance

Data governance is not new. As long as data has been around, so too has the need to ensure proper data organization, usage, access and understanding. However, it has changed significantly over time. What originally started in many organizations as a compliance effort or a documentation exercise using simple tools like spreadsheets or Wikis to provide basic business definitions and data responsibilities has now evolved into a sophisticated solution capable of providing organizations with a 360-degree view of their data landscape.

This evolution was no accident. Data’s rapid proliferation rendered unscalable tools unfit for the job, as consumers increasingly demanded immediate access and availability. Organizations converged both business and technical data worlds into a singular view, with basic lineage and workflows to manage and provide transparency into data assets. Businesses moved away from spreadsheets and Wikis and began to adopt more vendor-based solutions. Again, businesses had to mature their data governance model as the volume and breadth of data grew due to the introduction of various big data stacks, streaming data, data lakes and more.

In addition, the emergence of regulatory requirements like GDPR, BCBS 239, CCAR, Solvency II and MiFID all require today’s businesses to place rigorous rules and requirements on organizational data and processes.

Business users are also finding new and innovative ways to use data, and as primary data consumers, they desire the ability to emulate the ‘Amazon Marketplace’ experience when searching for, requesting and accessing an organization’s data assets.

Creating an Amazon-Like Approach for Business Users

Certain goals of data governance will always remain the same – to ensure accountability, understanding and transparency regarding an organization’s data assets. However, data governance should also promote the application of data as a valuable enterprise asset. It is only when data is used to uncover insights and reveal opportunity that its greatest value is realized. But to get people to use data, you must engage today’s data consumers. The current on-demand economy has developed a sophisticated new consumer, whether they’re shopping for groceries, shoes…or data. They want the means to see every available option, and the methods to quickly and easily get them. They want to give and receive feedback on when products work—and when they don’t. They want to easily see the quality of the product and they don’t want to wait weeks to get it.

In the realm of data governance, this translates into a need for quality monitoring and metrics, clear visualizations, extensive automation and intuitive workflows. It requires an enterprise-wide effort to define accountability and a commitment to collaboration.

By leveraging machine learning, automation and recommendation engines in the collection, validation and analyses of the data, organizations can eliminate the largely manual efforts involved in populating and maintaining a standalone data governance tool. Organizations can also clear up the complexity business users face when shopping for data by presenting them with an intuitive and easy-to-use visual interface adapted to how they consume data.

To achieve this objective, organizations must connect historically siloed and disparate technologies into one self-service, business-friendly platform. The connected technologies in a business-friendly data governance platform are visual data prep, data quality, predictive analytics, machine learning and data governance workflows. Dashboards empower business users to perform functions which previously required the technical expertise from IT. One platform example with all these capabilities included is Data3Sixty from Infogix.

By utilizing a visual drag-and-drop interface to quickly combine data sets, apply prepackaged data quality checks without writing code, and analyze data by applying machine learning algorithms to enrich data analysis, business users can quickly consume the output in visual dashboards with meaningful data metrics upon which they can base important business decisions. With this state-of-the-art approach to data governance, business users no longer require help from IT every time they have a question about their data, freeing up IT resources to handle higher-value functions and empowering business users to quickly analyze data for business purposes.

In the future, data governance technologies and tactics will continue to evolve. Today, mimicking the Amazon Marketplace experience for data use is the best way to serve the needs and desires of data consumers. Engaged consumers maximize data utilization, which can help your organization stay ahead of the competition. And data governance creates educated consumers, which ensures your data assets are being strategically deployed across your business enterprise.

About the Author: 

Emily Washington is the senior vice president of product management at Infogix, where she is responsible for driving product strategy, product roadmaps and vertical solution initiatives. Since joining Infogix in 2002, Emily has worked closely with product development teams and customers to drive introduction and adoption of all new products.  Before Infogix, Emily worked at Cyborg Systems and  Emily holds a Bachelor of Arts degree from San Jose State University. She also holds a certification in graphics design from The Art Institute.