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The Major Factors That Define Data Quality
In the present age of Big Data, data can be found almost everywhere. Every activity that we perform over the internet generates data of some type. In general, data can be simply defined as the collection of information that is actually translated into a computer-readable format.
Everyone must be aware of the ongoing demand for Big Data across IT, Business, Healthcare, Industrial, & several other sectors. By subjecting this data to the advanced data analytics techniques in Data Science, it becomes possible to explore the insights that are encrypted deep inside the data. These insights, when analyzed, become very crucial in transforming the present days’ global business scenario. Learn the techniques that form up the data analysis process in Data Science in real-time by joining for Data Science Training In Hyderabad program offered by Kelly Technologies.
Now, let’s take a look at what exactly Data Quality is & based on what factors data quality is defined.
What Is Exactly Data Quality?
Data quality can be interpreted as the overall utility of a dataset that has the ability to get easily processed & analyzed by subjecting it to various analytics techniques.
Factors On Which Data Quality Relies On:
- Accuracy
If the data is collected directly from the client, then it might undoubtedly be accurate. However, if the data is collected from any other source, then it should be checked for accuracy.
- Completeness
To ensure the data that is being collected is complete as a whole, it’s better to collect the same information from every single customer.
- Relevancy
You should make sure that whichever data you are collecting from multiple sources is relevant to your business model.
- Validity
Collecting timely data is very important to achieve accurate results in the analytics process. Ensure that you are collecting the latest data that is up-to-date.
- Consistency
As a part of the analytics process, you may need to store the data in multiple places & such a case, make sure that constancy is maintained everywhere.
Get a clear idea of the data collection process & work on improving your data quality in real-time through practical implementation by joining for Kelly Technologies.