Chapter 7: Designing a Database Data Management Strategy

Microsoft Exam Objectives Covered in this Chapter:

• Enforce data quality according to business requirements.

  • Establish the business requirements for quality.

  • Create queries to inspect the data.

  • Use checksum.

  • Clean the data.

• Design data integrity.

  • Reconcile data conflicts.

  • Make implicit constraints explicit.

  • Assign data types to control characteristics of data stored in a column.

Strategies recently have been developed to connect distributed systems. With the user interface at the helm, users have choices of workflow and business processes to support and leverage their data needs. Services such as Microsoft SharePoint Services and Microsoft Office make it possible to direct users to the tools they need. But the challenge goes well beyond using these means that have been perfected to gather data located in multiple and often disparate systems. The data must still be qualified and verified so it creates an accurate and complete picture of the enterprise it represents. In this age of regulatory compliance, mergers and acquisitions, and compliancy acts, such as the Health Insurance Portability and Accountability Act of 1996 (HIPAA), mastering data management is imperative. There can be no confusion as to what the data represents; there can be no confusion regarding the quality and integrity of the data. The credibility of a business is built on trusting the data.

In the first part of this chapter, we will show you how you can make these implicit constraints from your business environment work for you in managing your data. You have spent the first several chapters of this book learning the tools; it is time to capitalize on this knowledge and use them effectively in the process of data management. You will further learn how to use the Microsoft Business Intelligence Tools as well as improved methods of querying to enable you to qualify and analyze your data.

In the second part of this chapter, we will discuss how you can restrict control over your data even further by changing from implicit to explicit procedures. You will learn to control data by explicitly defining constraints, employing proper data types, and setting proper replication controls and synchronizations.