Before any fruit and vegetables are sold in supermarkets, they are first harvested from various farms and orchards. Then, they are sorted into their respective categories, cleaned to remove any bacteria and soil, and packaged uniformly during the preparation stage. Finally, depending on store orders, they are sent out to various locations.

In the data analytics world, raw data goes through a similar process before it can be analyzed and reported on — and this is where ETL comes in. 

There are three main steps in the ETL process — Extract, Transform, and Load.  Together, they work to prepare your raw data for analysis and reporting.

Check out the video to learn more about the ETL process: https://youtu.be/kmS7nMK2_3k

ETL (Extract, Transform, Load) Part 1: https://youtu.be/CyVvglLMLew

For more info on ETL, visit: https://cubeware.com/ 

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In the food industry, quality control ensures that the meat, bread, and other edible items reaching you are of the best quality. Companies use various ways to manage this, from developing fixed product formulations to standardizing manufacturing processes. By following these procedures, the quality of food is kept consistent and reliable for the consumers.

In the same way, companies also need to manage and control the quality of their data. This has become increasingly important due to the enormous amount of data that’s become available and accessible in the recent decade.

As a company’s datasets grow, it’s critical to ensure that they are consistent and accurate for analyses and insights. After all, data-driven decisions are only as good as the data itself. With datasets regarding customers, finance, operations, and sales comprising the core of most organizations, Data Quality and Data Quality Management only become more vital.

In this three-part series, we’ll be covering what Data Quality is, what Data Quality Management is, as well as why both are important.

Check out the video to learn more about What is Data Quality? : https://youtu.be/LnEzrC0FnZc 

For more info on ETL, visit: https://www.cubeware.com

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ETL is defined as a method or process of extracting, transforming, and loading raw data from various sources into a single and centralized location. These can be data warehouses or other centralized data storage systems.

In the data analytics world, raw data goes through a similar process before it can be analyzed and reported — and this is where ETL comes in.

So, let’s take a look at what ETL means.

Check out the video to learn more about the ETL process: https://youtu.be/CyVvglLMLew

For more info on ETL, visit: https://www.cubeware.com

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