Data Transformation
In today's digital world, organizations generate a humongous amount of data on a day-to-day basis. This data however is of no value, unless it can be used to gather insights and drive business growth. Data Transformation is the process of converting, cleansing, and structuring raw data into a usable format by removing duplicates, converting the data types and enriching the dataset. This dataset can then be used for data analysis to provide business intelligence, or as an input for AI/ML processes. Considering the massive amounts of data coming from disparate sources, data transformation has become an essential tool.
In a data transformation job, you perform data transformation operations on data in a data lake. You can either store it back in the same data lake at a different location or into a different data lake.
A typical data transformation pipeline looks like this:
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What's next? Data Transformation using AWS Glue |