Data is central to a large number of business processes like business intelligence, business analytics, predictive analytics as well as decision making. It is difficult to imagine a business process in the present times that does not depend on data. Since data is the most critical raw material for data injection process flow, it becomes necessary for organizations to pay great attention to data based processes.

Data extraction, transformation and loading

There are three important processes related to data that need to be taken proper care of. The first is related to data extraction. This involves extracting data from segregated sources so that it can be subjected to further transformation. The transformation process involves cleaning and processing of data sets to pave the way for the analytics. The transformation process is followed by the loading process. In the loading process, we store our data sets in desirable locations so that advanced analytics can be carried out with a lot of ease whenever required.

Best practices related to data ingestion

There are a lot of best practices that can be followed when it comes to the process of data ingestion. The first best practice is all about automating the process and developing different kinds of tools and technologies that do away with manual requirements. For instance, instead of manually working on the table metadata, we can automate the process so that tasks become easier when thousands of spreadsheets are involved. In addition to this, we can also make use of artificial intelligence for automating the process of data ingestion. This also avoids different kinds of errors that might be encountered during manual operations.

Footnotes

Data governance and data privacy are other important things that can't be ignored during the process of data ingestion.

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