Data Quality is about accuracy of data and process to define extra-essential/needless data to make correction in data to remove wrong and unnecessary data. Most of the times data comes from multiple sources and in many forms then due to this data quality task comes in a form of big challenge to maintain data quality and provide data quality and data quality is highly required for a successful business.
Means, in Data Quality process need to verify all collected and stored data for purpose of data cleaning to provide accurate data. So, during verification if all data is in one place or verification is going on at one source for data cleaning then data quality can be high but process can be executed with sources also.
Quality of data is very important to run a successful business and correct data is valuable asset for business. If wrong, missing and duplicate data are there then it can make problems to run a successful business, software and service, so it means data quality is highly required.
There are some activities for Data Quality:-
Data Accuracy is about correct data and need to provide accurate data. Where verification process and testing process contains steps to verify accurate executed data. Main thing is that Data Accuracy process is to provide correct data to users and business related persons for business growth.
Example:- There is a job portal where job seeker and job providers accounts work so, if job user use registered credential then user must get their account access with all correct related data and existing stored data which is saved by user.
Completeness is about data perfection. Complete expected data should be inserted in database. Data Perfection must be well created to get correct result by giving inputs. With this phase need to verify data perfection related test cases to know completeness of data.
Example:- Suppose a user is doing sign up with some mandatory and non-mandatory fields and after completing process need to verify complete data in database, what was executed by user and what was not. This is a simple example, execute more for more understanding.
Data Timeliness process is about to provide correct data to user who made request to get data and to provide data at correct time. Data Timeliness verification process and testing process must be executed with test cases related to get data for correct user at right time.
Example:- Suppose a registered user wants to know recent transaction history with expected detail then correct data should be visible to correct user at right time. So, it means user is expecting to get data on request time then right data to right user at right time should always be visible.
Data Reliability is about to provide consistent data on execution a process or execution same process multiple times then result should be consistent and where users can get a reliable system according to need what they are looking for. System reliability is also very important to business growth and should never be skip during testing process.
Example:- Suppose a user made a request to get last month transaction history and got a month transaction history then again make same request and get same record, means user is happy to get correct record all the times and it is a simple example so keep practicing.
Note:- There may be more challenges in Data Quality process according to requirement and need of business, this is just data quality related tips, so keep analysis and learning