From Gartner’s ‘Modern Data Management Requires a Balance Between Collecting Data and Connecting to Data:’ Data and analytics leaders need to take an aggressive approach that creates an appropriate balance between data collection and data connection.
As the value of data as a core asset to digital business is now widely accepted, the most immediate reaction is attempting to collect it as if that was the key to delivering business value. The very popular data lake trend, for example, puts the collection process at the center. But collecting data doesn’t necessarily deliver business value, and collecting data may not even be possible.
Among the key data management challenges, Gartner cites:
- Data is distributed between cloud and premises, and hybrid deployments are becoming the default approach.
- The scale and pace of creation of data, as well as the need to harness it in real time, make it impossible to always collect data and then process it for a single value proposition or use case.
- As organizations prioritize operational efficiency and analytics, these two forces are making organizations rethink their data management strategies and investments.
- Data governance and regulatory requirements need to span all use cases and data distribution is further challenging centralized data governance approaches.
- Deploying different data management capabilities for each individual use cases leads to unmanageable implementations and escalating operating costs.
According to Gartner, every data and analytics use case, regardless of the approach and business goals, requires the following data management capabilities: describe, organize, integrate, share, govern and implement. All of these capabilities must ideally operate in both “collect mode” (centralized data and processing) and “connect mode” (distributed data and processing).
Download the report to uncover what we believe are Gartner’s recommendations and best practices on how to balance collecting and connecting to data to help modernize your data management for greater flexibility and agility.
Modern Data Management Requires a Balance Between Collecting Data and Connecting to Data, Roxane Edjlali, Ted Friedman, 23 October 2017