Unlocking Business Insights with ETL Process

An effective ETL process can be powerful! It can help you unlock important business insights to grow and improve your organisation over time.

By understanding how ETL works and how you can use it, you can take your business to the next level through insight and intelligence. This could be the key to modernising and developing in a future-driven industry environment.

What is the ETL process, and how can it help you learn more about your business? Here’s everything you need to know to get started.

What is the ETL process?

Extract. Transform. Load. These are the key steps in any ETL process.

You can extract data from its source through ETL and transform it through combination or deduplication. You can then load data into a target database, where you can use it to inform business insights and activities. 

An effective ETL process ensures you’re getting the most out of information. You can access multiple datasets in one place, allowing you to identify patterns and evaluate next steps for your organisation.

When you know how to use ETL processes well, they allow you to quickly and find new professional opportunities.

How to implement ETL processes

Want to learn how ETL works? Follow these steps!

Extraction

The ETL process begins with extraction. Many businesses rely on various data sources, even running a complex data strategy. The extraction stage allows you to take data from all relevant sources.

When extracting data, you’ll obtain information from existing databases, legacy systems, and the Cloud and sales applications. You may also receive information from mobile apps or devices and additional data storage and analytics tools.

Typically, the extraction process relies on a hand-coded data approach. While the process can be done manually, this is much more prone to error.

Transformation

Next, it’s time to start transforming the data that you have extracted. This is the stage where data can be altered and optimised for the best possible use to support your organisation’s goals.

During the transformation process, you may need to cleanse data, checking for missing values or inconsistencies that could compromise validity. You might need to standardise formatting or discard duplicate information.

Some data must be verified for accuracy before you sort and categorise information for optimal usability. This will help to ensure you only work with accurate, reliable data. 

Loading

Finally, it’s time to load transformed data for storage. This will allow you to store and keep track of data in a single native system.

In some cases, you may use a full loading approach. This will allow you to upload all data in a single system. While comprehensive, it can easily get out of hand and become challenging to keep track of.

Alternatively, you may use incremental loading. This is much more manageable, relying on the incremental loading of new and highly relevant data. This can improve clarity and reduce costs associated with mass data storage.

Need help with ETL for your business? Contact Attura today.