3 reasons you need to re-evaluate your information strategy
A flood of big data is bringing with it pressure for real-time insights from business users and from security and privacy regulations.
All organizations now have—or should have—a strategy for managing metadata. But much has likely changed since you implemented your tools. The sheer volume of data is exploding: It is proliferating into the cloud and most likely has outgrown existing data warehouses. These changes have likely degraded your data governance efforts. Your metadata management strategy must evolve to meet these challenges to data quality.
Forrester agrees: “The explosion of types and sources of business data and the pressure on business to make a broader range of decisions on this data have raised the bar for metadata management,” writes the analyst firm.1
Prepare for battle
Efforts to derive business value by connecting disparate sources of data pose huge challenges to existing information architectures:
- More data. A surge of sentiment data and machine data is creating an avalanche. Companies are gathering massive amounts of new types of data across the enterprise and storing them on-premises and in the cloud.
- More demands. Business users are demanding more from data in order to make better, faster decisions in their jobs. Because data is driving strategic business decisions, users are requesting real-time access to this flood of information.
- More regulation. Organizations are bound by industry mandates as well as complex global, national, and local regulations that control how they capture, share, store, and use data. Financial and privacy regulations require some companies to monitor and provide end-to-end data security.
“These data drivers are making the metadata extend to not only include technical metadata, but to also include metadata information that interests the business users, such as context, semantics, data value, and risks,” according to the Forrester report.
Bring in reinforcements
Companies are looking to upgrade existing solutions to next-generation data-management platforms. But as data proliferates, the need for resources required to manage emerging data sources, shifting user needs, and new technologies increases.
Emerging best practices include building a metadata architecture and integration strategy to support the changing landscape. Automating IT processes can help shift resources away from traditional infrastructure toward innovative solutions. One such movement is to future-proof your data management, using technologies such as embedded virtual data machines, to define interactions and create metadata repositories and exchanges.
No matter how massive the volumes of data become, regardless of how business users manipulate the data, and despite changing regulations, the goal of metadata management will remain the same: to deliver trustworthy, timely, and relevant information that supports smart business decisions.
Read more about the changes that big data is mandating and the ways you can translate it into actionable information.