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Need Quality Data? Assessment Criteria Here!
Your company is keeping records of its sales, or its manufacturing, or its purchasing, etc. Is your data of high quality. In this blog, we discuss multiple dimensions of Data Quality.
First and typically important for analysis is how many empty fields there are. This is Data Completeness. Do we have a recipe without items? Do we have midterm grades missing? Did someone forget to enter their shift name? This is an important parameter especially if the data is not large and every record counts. The more the data is complete the more valuable it is.
Then we want to make sure that our data is accurate, Data Accuracy tests that the data is what it should be. For example, we do not want to have negative salaries, and if this is the case meaning we are receiving money from the employee it has to be clear, also negative grades are something impossible to occur unless it is a really mean teacher that gives excessive penalties. Data Accuracy assures that the data fields represent the reality of the data. It is a reality check.
A key aspect of data is to monitor progress or recess overtime. This is why Data Timeliness is a key feature of quality data. Quality Data keeps track of historical changes in order to help make sound decisions.
Another Quality Data feature is Data Consistency. This is the unification and establishment of one version of the truth feature in our datasets. If one parameter changes for example "product one" becomes "Product One" capitalized this has to happen in all the dataset or database. This is a simple illustrative example. Data Consistency makes sure that sales and manufacturing have the same values and the system doesn't mistakenly enter two fields instead of one for the same product leading to mayhem.
As we gather more and more data and become data-centric we need to work out ways we can access this data and make it usable. Data Accessibility and Usability is a key feature of Quality Data. There is no use of data confined in one system that does not communicate or export the data in a usable format. The usability of data allows us to use the data, export to Business Intelligent tools to be analyzed, and aid in decision making.
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Good Quality Data hunting!
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