What is a data review?
Data review is the process that leads to find data errors. It is an activity through which the correctness conditions of the data are verified. It also includes the specification of the type of the error or condition not met, and the qualification of the data and its division into the “error-free” and “erroneous” data.
Data review consists of both error detection and data analysis and can be carried out in manual or automated mode.
Why is a data review important?
Accurate data is absolutely essential for computations, record keeping, transaction processing, and online commerce.
Data analysis is important to understand problems facing an organization and to explore data in meaningful ways. Data in itself is merely facts and figures. Data analysis organizes, interprets, structures, and presents the data into useful information that provides context for the data.
Data analysis assists the organization to make an informed decision on the running of the business and providing information that could help the business avoid any occurrence of loss.
Process of Data Review
Following the data review process will allow for the fixing of these errors through data cleaning. The ultimate goal is to provide complete, accurate, and integrated data that serves as the base to draw correct conclusions.
As you interpret the results of your data review, ask yourself these key questions:
- Does the data answer your original question? How?
- Does the data help you defend against any objections? How?
- Are there any limitation on your conclusions, any angles you haven’t considered?
At the end of the Data Review, you’ll receive a document that:
- Contains a professional review of your databases and data infrastructure.
- Summarizes our findings with our recommendations on your future data strategy.
- Sets out our recommendations and a road map on how to achieve those recommendations.
