Tips to Manage the Dirty Data in your Organization

The data that is incorrect, incomplete and filled with errors affects the performance and the business of organizations. These errors can also go to the extent of corrupting entire systems and thus result in a major task to reset elements and environments.

In the B2B world too dirty data can create serious problems that may cost billions of dollars to the company and harm the customer relations and the market value. There are situations when the entire IT department needs to work day and night to set the issues right and there are issues that may even go beyond the control of the IT guys. In worst cases there is no way out but to get the entire system down and summon professional help to reset things. Taking into consideration the gravity of the issues that the dirty data may land you into, it is extremely important to understand the entire concept of the root causes of these problems. The business intelligence and business analytics team should groom the staff about these concepts and the possible reasons that could result into these issues. This helps them develop a better insight.

Other measures that help you influence the value of your data are as follows:

Sharing the responsibility of data quality maintenance

The onus of maintaining data integrity does not go to a single team or a handful of team members in an organization. Though the business analysts and the IT guys are technically expert in these issues, it is essential that all the employees understand the value of data quality and the reasons that result in erroneous data. They should also take help of the expertise to understand the basic concepts of database management so as to get conversant with the mechanism of data infections and hence help to avoid them.

Applications of analytic solutions

Embedded analytics is one of the best options available today. Dirty data infections can lead you to disastrous situations where analytic tools may be of little help. In such cases you are left with no option but to set up a new environment. Therefore it is advisable that you deploy analytic tools that are embedded in the systems so as to identify the source of the errors and raise alarms to prevent incorrect data getting into the system. There are automated solutions that help you define workflows and also contribute to data cleansing. Such measures can drastically reduce the issues created by dirty data and thus prevent major disasters.

Managing the tools

Data generation and documentation is done in organizations by using a variety of tools. If the volume of the data is not too large then the conventional tools are fair enough. However, when your organization is adding loads of data and needs to compute it with various permutations and combinations, then you require tools that are stable and better suited for automation. This avoids further crisis that results from minor and major errors which can harm the system.

Awareness regarding data management

Database management is a complete domain in itself. It is usually a conception that it is the technical expertise that deals with this task. Though it is true that technical experts look into the technology part of the database management, the business guys are the one that provide the information elements as inputs to the system. There needs to be an awareness or training regarding the technical concept related to data and data quality.

Managing the balance of data sets and elements

Just as the non technical guys need an introduction to the data, it is true the other way round as well. The technical people need to take care while executing the data management at the back end so as to prevent any issues.

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