Introduction

We looked in the last chapter at the importance of making sure that the data that some organizations hold and supply on various topics are accurate, up to date, not excessive and secure in both their storage and disposal. It is important, though, to remember that, while not all organizations are in the public sector, and not all organizations are data controllers in the eyes of the law, all organizations have a reliance on the quality of their data that extends beyond mere compliance. This chapter deals with the growing importance of data quality in the operation of organizations, and at how data consistency, validity and quality can best be maintained. Although the term ‘databases’ is frequently used in this chapter, it is important to remember that our concern is not only with relational databases and database management systems, such as Oracle, MySQL or Microsoft Access. Many of the information systems we depend on, such as spreadsheets, or even text documents, are ‘flat file’ databases – holding multiple instances of the same record type.

Many systems which are represented as performing quite individual and specialized functions, for example customer relationship management (CRM), content management systems (CMS), or enterprise resource planning (ERP) systems are, in fact, databases with a sophisticated user interface. Another example is integrated library management systems (ILMS). An actual database management system makes it easier to handle and to perform operations on large amounts of data, but any information professional will rely on something which is, effectively, a database, and the points made in this chapter apply to all of these.

The impact of large databases and the application of data quality tools are discussed, and the importance of a data quality policy is stressed. This is primarily an internal issue for the organization – the next chapter deals with external threats.