What are Batch Processes?
A Batch Process is where a certain task is carried out on large volumes at once rather than in a real-time basis. The process will likely be scheduled based on time or volume.
What Batch Processes are involved in data quality?
Batch Processes are often used when cleansing data. Examples of data that can be large scale that will need to be validated are:
- Address data
- Contact data
- Employee details
Cleaning data in this way is common as these databases tend to have large amounts of data and can quickly deteriorate over time causing issues that need to be quickly solved. The batch cleaning can also be automatically run in the background without too much human intervention. A batch cleanse is also commonly implemented before a large-scale marketing campaign where clean data is needed urgently.
Why are Batch Processes useful for data cleansing?
Data can quickly decay over time even if it was accurate when first captured. By batch cleansing data on a regular basis against datasets and suppression files, you ensure the data that you hold is updated against changes such as people moving house and people passing away as well as email addresses and mobile numbers that no longer exist. These datasets include:
Regular batch data cleansing should be used in conjunction with real-time validation for an effective data strategy to guarantee the accuracy of any data entering your database, as well as your historical data.
Why should you use Batch processes to keep your data clean?
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