In this chapter we will examine how we create and maintain data quality and how we integrate all types of data and data models.
Once databases are created we need to look at data management and database management. Data governance is a set of processes and procedures to manage the data within an organization that have as goals availability, integrity and compliance with regulations. Risk and security exposures are also a critical set of processes that must be developed.
The Sarbanes-Oxley Act of 2002 said that an organization must undertake actions to ensure data accuracy, timeliness and consistence. One way in which companies deal with managing their data is to create positions of a data steward – a person assigned the responsibility of ensuring that organizational applications properly support the organization’s enterprise goald for data quality. Data quality is important to:
Characteristics of Quality date include:
Reasons for Deteriorated data quality:
Key Steps in a Daa Quality Program include:
General Approach to Data Integration include:
ETL – consolidation of data has the following characteristics:
The ETL process is where data is reconciled in two states: the initial Enterprize Data warehouse (EDW) and subsequent updates on a periodic basis. The initial process includes:
Data transformation involves converting data from the format of the source operational systems to the format of the enterprise data wqrehouse. Levels include record-level functions, field-level functions.