WhitePaper: Bad Data, Real-World Characteristics of Architecture Gone Awry

In this whitepaper, we describe how executive and IT management can get and maintain control of their company’s data architecture to help meet business objectives. We describe the relationship between data integration projects and data architecture concepts and practices. We describe how the business planning and IT development processes that direct and leverage data integration projects depend on tooling. We describe breakthrough ways in which data architects, business analysts, programmers, and business users can collaborate to address their organization’s pressing business challenges.

Your business succeeds or fails based on its performance in the physical world of creating and delivering products or services to meet customer demand. But a critical component at the foundation of your success may exist out of view, in the abstract world of your company’s data architecture. With this in mind, it pays to ask yourself a fundamental question: Do you and your IT staff have a clear picture of the abstract layer of your business and whether it is contributing to your overall performance?

Bad Data: Real-World Characteristics of Architecture Gone Awry

Even if each piece of data in your business is accurate, all the data combined may not be a business asset. Your data overall might be unwieldy and unresponsive to change. While good data can be easy to work with, bad data can be hard to work with. Whether your data is “good” or “bad” in this sense is a result of how you have integrated the sources and consumers of information in your company, how you have created a data architecture.

Data integration? 

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