Data Attitude: A Checklist for Effective Data Management

Summary

Data is one of the most precious institutional resources of the present century. Unlike any other resources, that is greatly limited, data is available in abundance and for all to utilize, however, my observation and research demonstrate underutilization, and when utilized, it is either by wrong Data Attitude or the most accurate and relevant data captured for reporting is lacking. Even the most basic data such as the qualifications of employees within an economy is seldom utilized. For example, as early as 1987, Tsang, in a study ‘The impact of underutilization of education on productivity’ had opined that overqualification is one of the leading reasons for job dissatisfaction hence (by inference) impacting employee turnover, however, tell me a HR department that reviews qualification progression of its workforce as a strategy towards job satisfaction, yet am sure the same departments conduct job satisfaction surveys quite regularly. Therein lies a classic entry point of this article, Effective data management. Effective data management focuses on, among other constructs, the intent of maintaining data, the integrity, accuracy, completeness, and the reliability of such data against the real-world. In this article, instead of relying on the data scrapping, analysis, or presentation tools, I am interested in revealing why it's important for your organization to invest in the right talent and qualification, while at it, the right attitude. Data Attitude.

I want to enlighten a Data Professional on what mindset you need to be effective, as a bonus, I am interested in ensuring your data strategy is simple and precise, yet robust by just doing two things; telling you why and who will reduce data processing biases and demonstrating a simple data management procedure you can employ at any level. Check Out below to access the complete text.