The term Extraction, Transformation and Load refers to a set of processes in companies that use a data warehouse (DW) – a database that allows advanced analysis.
The concept of ETL is based on the three-step join for handling data: extract to transform and then load.
Its importance is also related to the versatility of the process, which can be applied in simple databases, such as SQL, and in more complex databases, such as a Big Data cloud.
Want to learn more about the topic and its practical application?
Read on and discover what ETL processes and data analytics companies can do to improve data management and Business Intelligence (BI) in your business.
ETL: what is it?
Extraction, transformation, and loading (ETL) are all terms used to describe the same thing. As an approach for analysing and making use of data stored in databases, it can be used to any level of complexity. The quality of the data and the manner in which it is changed can be defined by ETL in order to transform it into understandable and dependable information.
Regardless of the size of your company, if it needs to use the generated and stored data, you should use ETL to outline a usability strategy. For this to be done, it is essential to establish rules for the standardized handling of information and, thus, guarantee its maximum use.
When it comes to putting this information to use, ETL is a vital step. Quite simply, this is the component that determines how well raw data is turned into usable, relevant, and trustworthy information.
Consequently, its primary goal is to ensure that data is used in a methodical manner. Data handling can be standardised by using a simple technique known as “process mapping,” which is nothing more than the establishment of rules.
ETL and data warehouse: what is the relationship?
ETL is essential so that, in the environment of a data warehouse, we can create and observe the structures of dimensions and facts related to the data.
After all, the DW is intended for storing data that, at some point, must be activated.
This is where the Extraction, Transformation and Load processes come in, through which, as we have seen, raw information is processed to meet specific purposes.
Therefore, ETL transforms the data that is static in a data warehouse, in a kind of standby mode.
How to apply ETL in your bi strategy?
As we highlighted before, ETL is fundamental to Business Intelligence strategies and, therefore, both are interdependent.
It is through this process that we organize all the data that will inform our business intelligence analytics initiatives.
To outline an effective BI strategy, it is essential that we have the data previously organized in order to enable the execution of the project.
Therefore, it is necessary to categorize them, create hierarchies and relationships so that they can be consulted and give the expected answers. Users can feel secure knowing that top ETL companies in India with an ever-evolving set of controls has been put in place around ETL procedures, ensuring that any problems with internal infrastructure or data will not result in incorrect reports being returned.