Data exists to support systems, analytical, and management processes. However, the existence of data alone doesn’t ensure that these processes can be undertaken seamlessly. A seamless undertaking depends heavily on how useable, or meaningful a dataset is, and on how well the processes that created the dataset are understood.
Every company today has some level of data “baggage”. Data baggage is made up of all those legacy systems, data stores, and reports that are heavily relied on, but whose domain knowledge has been slowly lost over the years.
Please join Quest Software expert, Omar Masri, for a discussion on how analysts can map data baggage to new systems and how to prevent adding more baggage. In this informative presentation, you’ll learn: • What is the difference between mapping and traceability
• Data project types
• Sorting out the baggage. Approaches: theory, method, tooling
• Selecting an approach for a project type
• Future proofing your data processes
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