Dirty Data from the Business Intelligence Perspective
The dirty data issues have also been looked upon by the business intelligence people and are categorized as a business intelligence issue. The logic in data management is that the extent of data increases with the expansion of a business. It is this duration when the business executives need to be on track with the development and maintenance of the business that goes parallel to the progress of the organization.
If this fact is ignores, it leads to generation of incorrect or inaccurate data that goes on adding over a period of time and may also start affecting other elements in the system. These effects may not be revealed at an early stage and are evident much later. One more factor that results in dirty data issues is the lack of standard operation rules and procedures for data management. For example, the if the inputs into the system are not defined in a particular way, there is no consistency and as a result there is a risk of data being accepted in more than one way which could lead to duplication, overwriting or redundancy.
Business analysts apply the principles and theories of business intelligence to try and understand various issues and the root cause behind them when it comes to dirty data. Business intelligence can be utilized to device various concepts like questionnaires, checklists, rules, procedures that provide a check on any erroneous information from getting into the system. These methodologies can be induced at any levels and executives just need to keep a track on the data that goes into the system as they adhere to these lists or processes. This can save the systems from crashing down with loads of futile information.
As the business intelligence experts work on the theories related to the dirty data issues, they also try to figure out the financial consequences that these failures can cause. As a business intelligent representative it is also essential that they introduce the business representatives to the concepts of data management. The individuals who deal with the data input need to understand the concepts like metadata, data sets, data elements and the way they function in an environment. The possible dirty data issues that can affect these sets and elements in various ways also need to be known. Only when they understand the gravity of these issues and the scale on which they can occur, the business units can have serious perception of the damage that can be caused.
It is the business intelligence officer who best understands that the dirty data can affect the BI applications and environment to irreparable extents. Along with other aspects, they also need to account for the data transmission in external and internal channels and also need to account for operations like data conversion and data merging when applicable. All these operations again need to be related to cost analysis and authorities need to be convinced that these damages can cost a fortune to the organization and need due attention within time.