Strategic Data Assessment Services Step by Step Measuring Of Data Quality

1. Strategic Data Assessment Services: Step- by-step Measuring Of Data Quality Experts working with data governance assessment often need to make changes in the collection, representation and maintenance of data processes to meet the market standards. Measuring data quality helps ensure accuracy and effectiveness of decision-making. Today quality data has become a foundational pillar of good business operations and strategic planning. But how do we determine the quality of the data sets being used in relation to the data quality of our competitors? This is where comparative data quality assessment comes in.

2. What is Data Quality? All data structures are not the same! Depending on how data is collected, reviewed, represented, analyzed and reported, any data set might be called highly systematic or completely faulty. Following the principles of data maturity assessment, we look into data literacy, data search, data governance and leadership. The objectives of data quality assessment are as follows: 1. Recognizing data quality problems. 2. Validating data correctness. 3. Building confidence in data usage. 4. Providing reliable insights. 5. Ensuring consistency across sources. 6. Meeting standards and compliance requirements. 5 Steps for an Integrated Data Quality Assessment Determining Indicators Usually, 1 to 3 indicators are selected for the assessment of data. These indicators serve as the foundation that defines what the quality of information might be - usually, data assessment experts make it a point to choose unique, fresh and highly relevant indicators especially those that have suspected data quality issues. Document and Dataset Review Reviewing the literature is always a very essential aspect of data research. In this case, the data assessment solutions gather information by going through previous DQA reports, narrative progress reports and project M&E plans. If any

3. existing company documents revolve around the same data set, those are also reviewed. Selecting A Data Collection Method Most companies have existing data collection tools in place. The work of the DQA expert is to assess the strengths and shortcomings of these methods. While doing so, the expert will also become aware of the flow of data in the particular organization as well as the different roles and responsibilities fulfilled by the team members. Selecting Assessment and Data Presentation Method For Data Quality Assessment (DQA) we take time to determine appropriate assessment methods (e.g., statistical analysis, data profiling) and clear data presentation formats (e.g., charts, reports) once we have a clear idea of the situation with which we are working. Clear assessment and presentation tools not only help with communication but also increase the relevance, reliability and validity of data. Reporting the Result Data assessment services do not conclude a project until they have provided the client company with a detailed and comprehensive report of the findings. Usually, at this stage a comparison is drawn between the strength and weaknesses of the client institution compared to their competitors. A DQA report will contain: ● Summary: Overview of findings. ● Methodology: Description of assessment approach. ● Results: Detailed analysis outcomes. ● Issues: Identified data quality issues.

4. ● Final Thoughts Each comparative data quality assessment procedure is indeed different. In fact, a good expert in this area is someone who knows how to customize the process according to the situational needs of the client. Not only that, reactively communicate with all different departments involved in data collection and management so that a proper audit of internal data processes can be done! Recommendations: Actionable suggestions for improvement.