A Comprehensive Data Definition refers to a formal data definition that provides a complete, meaningful, easily read, readily understood definition explaining the content and meaning of data.
In a business enterprise environment where people are heavily depending on intelligent business systems (business intelligence), there will exist a communication gap between the information technology group and the non-IT group like clerical workers when there is no comprehensive data definition.
A data warehouse supplying the needed data for a business intelligence system has a well defined data model and algorithmic process based in real life business activities, entities and events.
For instance, customer names, address, age and the products and services they avail are all ordinary and day to day that a business’ staff deals with in a non digital way. But these are to be automated so that dealing with these things will a lot faster and less prone to error. So these data will be input to computer systems which will then be gathered, transformed and loaded into the data warehouse.
The transition of data from the front end users (clerk for instance) to the storage in the data warehouse need to follow a certain protocol so that data will be consistent and integrity of business rules maintained. That is why the organization has to have a business data architecture.
The business data architecture could be likened to the blueprint that building architects make when designing a house. The blueprint contains all the specification pertaining to the layout of the house – the placement of all materials, electrical plans and plumbing plans among others.
Business data architecture is the same. All the business data are transformed into a data structure that the computer can understand. To the person on the desk, a customer’s name is just letters. But to the computer, the customer’s name is made of bits with a specific format.
A shared comprehensive data definition is needed for the organization to seamlessly bind together the data warehouse and the group of people running the enterprise. The advantages of having a comprehensive data definition include:
- better understanding of data by both IT and non-IT staff
- structurally accurate, consistent, well defined and high quality data can boost organizational performance by expedited transactions
- reduced uncertainty about data and increased awareness of staff
- less data redundancy
- beneficial delivery of incremental data in achieving a long term goal
- reduced need for data transformation which could result in lighter server load and subsequently means less investment for additional hardware acquisition
- improved productivity of people running the enterprise because there will be less time trying to figure out the meaning of data
One of the very first steps and a process which should be given careful consideration in building a warehouse and intelligent business solution is making a comprehensive data definition in the business vocabulary. The will resolve future problems like inconsistencies and incompatibilities. Some things to consider about a business data vocabulary include:
- Definition and use of the most common names or data and its definition across the business intelligence system
- Use of common integrity rules
- Identification of disparate data
- Mapping the definitions of disparate data
- Assessment of the quality of disparate data
The definition of data should be very clear and detailed. It has to be comprehensive enough to include both the technical and non-technical aspect of how the data is gathered, stored, shared and used.
When there is a comprehensive data definition, there should be no reason why a miscommunication could exist among the staff within the business organization.