One of the biggest\u00a0themes in operational databases and data warehouses alike that is universally recognized but far too often ignored is the cleanliness of the data.<\/p>\n
From hundreds of meetings with data processing and IS staff, I have identified three consistent themes.<\/p>\n
Although these three themes stand out dramatically as the biggest problems in corporate data access, the same data processing and IS staffs that identify them are usually attacking only the first two of them.<\/p>\n
The three themes can be expressed by the following comments:<\/p>\n
Given the universality of these comments, it is strange that entire industries are being organized around the first two issues but the third issue seems to be something that we don\u2019t want to talk about.<\/p>\n
The database marketplace has responded to the need for data access with client\/server architectures, dedicated data warehouse hardware and software, and whole families of communications schemes to connect users to their data.<\/p>\n
The query tool marketplace is an embarrassment of riches. There are dozens of ad hoc query tools, report writers, and application development environments. We are well into the magnificent new\u00a0generation of powerful tools for data warehousing end-user applications with dimensional OLAP\/ ROLAP tools and the hot new data mining tools.<\/p>\n
Yet the third issue, data integrity, languishes in the backwater of operational data & data migration & data warehousing. It is talked about briefly and then completely ignored.<\/p>\n
There is a definite avoidance of the topic and very few plans in place to address data integrity at the same level as those plans that address data access or query tools.<\/p>\n
Enterprises across the globe face these issues mostly due to:<\/p>\n
All of the issues above can be mitigated with proper access to expert resources that can deliver and maintain an enterprise data architecture and the business value gained through a data clean up exercise in the long term is priceless<\/p>\n
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