Maps are useful tools that graphically show geographical relationships. With a good map, you can figure out where you are in relation to where you want to go, and the best way to get there. These days, with online maps, you can also get real-time information about what’s going on and where, from traffic conditions to weather and everything in-between.
Data maps are similarly useful. A data map can show you the relationships between different data sources; systems that collect, organize, manipulate, and store data; and the reports, dashboards, and other artifacts that consume the data.
Data maps help enterprises in a number of ways:
-Enabling data integration: Data mapping can expose mismatches in different database schemata, showing users where transformations need to be performed when integrating data sources and databases.
-Visualizing data lineage: Data mapping can show users the path data took before ending up on a report or dashboard, helping troubleshoot reporting errors.
-Facilitating data warehouse initiatives: Similar to data integration, data mapping can show users where transformations are needed so data from different sources can be combined for “apples to apples” comparisons.
-Simplifying data migration: Data maps are invaluable for planning and executing migrations from one database system to another or from an onsite system to a cloud system.
-Enabling more effective use of BI reporting tools: Understanding where the data originates is critical to building reports and dashboards using BI reporting tools.
How do you get such a useful thing? By use of data mapping software.
You don’t have to use data mapping software, of course. You can manually trace the data from one place to the next. You might even put together a snazzy spreadsheet file that keeps everything straight and enables reporting. But even in a simple data environment, keeping it up-to-date would be a chore. In the complex and evolving environments typical of medium- and large-size companies, the task would soon become someone’s tedious, soul-crushing full-time job.
Data mapping automation software simplifies the task by discovering metadata in disparate systems and connecting the dots on its own. Because it does so quickly and automatically, data maps are never out of date. This frees up resources for more important, satisfying tasks, such as solving actual business problems.