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.
The Lazsa Platform provides data transformation using templatized jobs or custom jobs depending on the code that you use. Templatized jobs include join/union/aggregate functions that can be performed to group or combine data. For complex operations to be performed on data, DPS provides the option of creating custom transformation jobs. For custom queries while the logic is written by the users, DPS UI provides an option to create SQL queries by selecting specific columns of tables. Lazsa consumes the SQL queries along with the transformation logic, to generate the code for custom transformation jobs.
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What's next? Data Transformation using AWS Glue |