Optimizing Self-Service Data Governance
Empower Business Users by Putting Data at Their Fingertips
Terms like big data, data management, data governance and data quality have long since left the realm of buzzwords and become a part of the new business lexicon. As these key topics have been covered, discussed and debated in detail, none have lost their importance or impact among organizations. In fact, properly managing data to ensure it is adequately governed to deliver accurate, trustworthy data to business users is more critical than ever before.
Today, data is the engine that not only drives vital business decisions; it also enables profitability and growth across organizations regardless of size or sector. In the financial services industry, banks routinely analyze their customers’ income and savings as well as spending and borrowing habits to identify opportunities to offer personalized products, communications and services. In the insurance industry, organizations are analyzing data to identify potential fraud, opportunities for subrogation and reduce inefficiencies and costs by shortening claim cycle.
While these examples represent just a small sampling of how data is being used across industries, the reality is that organizations across every industry are leveraging their data to enhance day-to-day operations, optimize the customer experience, establish customer loyalty, enable digital initiatives, improve business decisions and ultimately increase growth. Still, many organizations fail to realize maximum value from big data because business users don’t understand how to access and analyze data, and apply the insights they generate for strategic decision making.
Data Evolution for the Business User
Now that data permeates and impacts every aspect of organizations, it comes as no surprise that business users are the primary consumers of enterprise data, in an effort to better understand operations and outlook and to derive insights for strategic decision-making. The sheer volume of data demands means that data access requests are growing and becoming more complex than ever before. Business users need to be empowered to take the lead on data analysis, but often can’t translate technical vernacular into business terms. As valuable as data is, it is only an asset if users can understand it from a business standpoint and turn it into meaningful insights.
Out of necessity, users across all areas of the business must assume a more prominent role in enterprise data management. Organizations are now formally aligning business users, technology and processes through data governance to break through any potential confusion business users face when leveraging data. Fundamentally, data governance is about increasing the understanding of data so that it serves the needs of everyone within an organization. But the most successful organizations create a self-service data governance model that specifically helps business users find new and creative ways to use data.
Self-Service Data Governance
The goal of self-service data governance is to abstract the complexity business users face when searching for and analyzing data. It is important to present them with an intuitive and easy to use visual interface tailored to how business users consume and interact with data. Ultimately, this interaction should mimic something like the ‘Amazon Marketplace’ experience when searching, requesting and accessing the organization’s data assets.
The key to creating self-service data governance is expanding access to data, driven by inherent security and data quality, so business users can serve their own individual needs. By connecting previously different and siloed disciplines into one enterprise-wide initiative, users across all areas of the enterprise can immediately find, sort and analyze data to rapidly reveal meaningful insights.
Technology plays a critical role in facilitating the data marketplace. No matter what solution you used, critical capabilities to ensure success include data governance, data quality and analytics. It should deliver complete transparency into an organization’s data landscape by providing users with a visual drag-and-drop interface to quickly combine data sets, apply prepackaged data quality checks and analyze data through easy-to-use transformation, blending, and machine learning algorithms. Ultimately, users are empowered to quickly consume data and translate to meaningful data metrics and insights for making important business decisions.
If you would like to learn more about establishing self-service data governance, download this data sheet:Download the Data Sheet