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.

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. ● Recommendations: Actionable suggestions for improvement.
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!