People who read the last post on this blog “What is a Data Warehouse” would probably accept my view that for an organization to get better at anything worthwhile, “data” is everything. If you accept this notion, I propose the immediate creation of a new ‘C’ level organizational position – Chief Data Officer (CDO).
To me, the CDO is a more important position than the more glamorous CIO (Chief Information Officer). After all, the input to any strategic information is raw data and many organizations don’t have a comprehensive focus on data that is present within its boundaries. It is important to realize that ‘Good data is a source of competitive advantage and not just any data’.
To me, the CDO is a more important position than the more glamorous CIO (Chief Information Officer). After all, the input to any strategic information is raw data and many organizations don’t have a comprehensive focus on data that is present within its boundaries. It is important to realize that ‘Good data is a source of competitive advantage and not just any data’.
Let us for a moment assume that there is an organization with the CDO structure in place. The next question is – How should the CDO go about doing the job, given the massive amount of data generated by organizations? – Answer: Divide & Conquer!
The 6 mutually exclusive, collectively exhaustive (MECE) types of organizational data are given below:
Type 1) Transaction Structure Data – Business processes are a series of never-ending transactions. All these transactions has a context and this is defined by this category of data. Examples are: Products, Customers, Departments etc.
Type 2) Transaction Activity Data – These are the transactions themselves. Ex: Purchase Order data, Sales Invoice data etc.
Type 3) Enterprise Structure Data – These data elements are unique to each organization and the inter-relationships between data elements are important. Ex: Chart of Accounts, Org Structure, Bill of materials, etc.
Type 4) Reference Data – Set of codes, typically name-value pairs that drives business rules. Ex: Region Codes, Customer Types etc.
Type 5) Metadata – Data that defines other data thus making the collection a self-defining entity
Type 6) Audit Data – With so much focus on regulatory compliance, this is the data that tracks all the operations within a data store
Type 1,3 & 4 together is defined as Master Data and its management is the subject of numerous BI articles and white papers.
Our CDO would do well to understand all these 6 types of data in the organization and have some specific strategies to improve their quality. This & many other data management strategies will be the focus of this blog – Please do keep reading.
0 comments:
Post a Comment