Not quite long ago, data warehouse systems were handcrafted to be handled manually. But, with the businesses entering the digital age where technological innovations and customer demands are evolving, data warehousing techniques have to be replaced with modern tools. One such tool is ETL. 

With the introduction of ETL software, enterprises no longer need to rely on hand-coded systems to deal with a vast amount of data. So, does it make sense to hand-code (SQL) a data warehouse or is an ETL tool a better choice?

ETL Tool Explained

Sometimes, it does not take two but three to do the tango. 

ETL, “Extract, Transform and Load”, refers to a trio of processes that allow movement of data from its source to target database or warehouse. It is a technology that enables companies to seize, transform, and load data extracted from multiple sources. This offers a multitude of opportunities, from transferring information to the cloud and optimizing sales processes with a high-speed analysis of historical records to developing fresh revenue streams and improving productivity. 

To conclude, ETL technology involves combining data gathered from multiple systems to a data repository or warehouse for either storage or analytics. 

Extract: Extraction involves the process of reading data (unstructured and structured both) from a source database to extract a subset of data. In this step, all the data can be retrieved from various sources without losing time. Data sources can be of various types, some of the most common examples are mobile devices, CRM systems, analytics tools, data warehouses, cloud, on-premise, or hybrid environment, and more. This step is designed in such a manner that the source system is not affected negatively. Once extraction is complete, ETL tools load data straight into a staging area, making it ready for the next phase i.e. transformation.

Transform: In this step, the extracted data is cleansed and prepared using rules or lookup tables or by creating combinations with other data and converted into the desired state. It includes records validation, rejection if required, and data integration. Transformation of data includes conversion, sorting, filtering, standardizing, translating, removing the duplicates, and verifying the consistency of data sources. So, in this phase, first the extracted data is cleansed followed by deduplication where redundant data is discarded, then data is sorted or organized, verified, and standardized. 

Transformation not only enhances the quality of data but also ensures that it travels to its new destination without fail. 

Load: In this last stage, resulting in data is written to a target database. In this step, tools are used to physically insert each and every record as a new row into the definite table of the target database. In doing so, the SQL insert statement is used. The transformed data is either loaded in intervals or all at once. 

ETL tool: Use cases and benefits 

Use cases

ETL software can be used to execute many activities such as:

  1. Marketing data integration: Marketing data such as web analytics, social media information or consumer data is moved into a place using ETL for further analyzation. 
  1. Database Replication: ETL tool can be used to derive data from many databases including, MySQL, PostgreSQL, and Oracle and transfer it into a cloud warehouse. 
  1. Business intelligence: ETL tool allows companies to move data from source to destination database where it can be used to derive actionable insights. Hence, the capability to make informed decisions increases. 

Benefits

ETL tools play a significant role in improving data hygiene that helps organizations give a strong revenue boost. Here are some of the most common benefits:

  1. ETL data integration software is comparatively easier to use as it involves an automatic course to extract, transform, and load data for further usage. The need for developers to rely on manual coding gets eliminated, making it more efficient. 
  1. With a robust built-in-error handling functionality, ETL empowers organizations to build resilient and well-instrumented data warehousing systems. 
  2. It improves the quality of data and frees IT from its operational role, thereby boosting IT productivity. 
  1. ETL technology provides easier access to data that helps companies drive revenue growth and innovation. 

With an ETL tool in place, companies can use data to deliver valuable insights, offer superior customer experiences, and streamline growth and productivity. 

Author bio:

Chandra Shekhar is a technology enthusiast at Adeptia Inc. As an active participant in the IT industry, he talks about data, integration, and how technology is helping businesses realize their potential.