What is ETL & Why is It Important for Business Decision Making?

What is ETL & Why is It Important for Business Decision Making?

Data, both historical and current, is vital for businesses. With more data analytic tools available, enterprises can now use insignificant data to create new relationships that uncover a new perspective. This is why data is given more importance now than ever. Data-driven business decisions are far more profitable. According to McKinsey reports, data-driven organizations are 19 times more profitable and are 23X more likely to get customers. 

The Extract Transform Load (ETL) tool handles organization-wide data effectively. It extracts data from multiple sources, transforms data into meaningful information, and loads data into a central data storage system. Understanding the importance of ETL will help businesses use data to make critical decisions.

How Does ETL Process Work?

ETL is a data automation tool that transfers unrefined raw data from disparate data systems and pushes the data into the centralized data warehouse after transformation. Analysts, developers, data scientists, and testers must collaborate to consolidate data manually from multiple sources. The ETL tool automates the entire process and presents data in a reformed manner that can be used effectively by various teams in the organization. A BARC report shows that data analytics can help optimize costs by 63%. 

ETL Process Works in Three Stages  


Data from multiple sources are extracted and stored temporarily in a staging area. The data transformation rules are applied to this staging area. Data gathered could be structured or unstructured. Data formats include text, email, images, audio files, videos, webpages, etc. As data is collected from multiple sources, their format, functionality, and context will vary significantly. Data transformation is critical to ensure that the centralized data warehouse has easy-to-access data.
Multiple transformation operations are executed at this stage to convert data into a consolidated format. At this stage, context and conceptualization happen with raw data. Data available in multiple formats will be converted into a normalized uniform format for storing in the centralized data format. This ensures that the data pulled from the data warehouse is already standardized for use by the organization.  

Once data transformation is complete, all the transformed data is loaded into the centralized database. The essential purpose of the ETL tool is to get the data ready for use in a centralized storage system. Data may be loaded in batches or bulk depending on the business needs. The time and loading speed depend on the data’s size and quality.

Why is ETL Important? 

Forrester reports show that insight-driven businesses (IDBs) are 8X more likely to grow by 20%. These data insights are useful in identifying new revenue sources and establishing a business as a market leader. Legacy data storage systems can’t provide these data analytics required for making business decisions. The ETL tools enable businesses to use Business Intelligence (BI) technology to derive data analysis.

To find answers and solutions to sophisticated business questions, organizations need ETL. The ETL tools help businesses in several ways:

  • Retrieve historical data to identify context and comprehend data usability
  • Prepares the data for use by business intelligence tools 
  • Helps to identify meaningful insights and patterns 
  • Converts assorted and scattered data into a consistent and standard format 
  • Pulls data from external sources, such as partners, suppliers, recent mergers, etc., into a business data warehouse 
  • Improves accessibility and usability of a centralized data repository 
  • Boost productivity by simply presenting the data in a ready-to-use format for multiple departments 
  • Allows businesses to create custom data reports quickly 


Benefits of ETL for Business

According to BARC research, organizations are keen on investing in master data management and improving data quality. Companies that have adopted a data-driven approach believe it can improve business decision-making by 72%. Leaders wondering why use ETL will change their minds once they understand the benefits that ETL can offer:

Improved Data Mapping

Manual data processing to collect insights is exhausting and imperfect. ETL tools accelerate data mapping with powerful transformation strategies. It helps create a meaningful correlation between multiple data models, regardless of volume. Large quantities of data can be quickly mapped to create a new context that can help decision-making.

Automated Data Processing

ETL scripts are faster than conventional data processing. Batches of data can be processed quickly using ETL tools. With batch processing, organizations can look at critical data that can influence business decisions. It will help to accelerate the decision-making process as well.

Enhanced Data Quality

Many leaders invest in ETL tools mainly to improve data quality. Raw and unstructured data consume more space and are also unusable. Data must be maintained in a standard format for the BI algorithms to work. When BI tools have the data ready, meaningful analytics and reports can be generated much more quickly.

Powerful Data Governance

Organizations can adopt strong data governance policies with accessible data. They can define security policies for data availability, usability, integrity, and security when the data warehouse has consistent data. Strong access control mechanisms can easily be implemented with structured and standardized datasets.

How to Choose ETL Tools?

The data migration process begins with choosing the right ETL tool. ETL process becomes complicated as data volume, variety, and diversity increase. Following are some of the features that must be considered while choosing an ETL tool for an organization:

  • Wide range of connectors that can extract data from legacy, modern, cloud, and on-premise data sources. The connectors should enable bi-directional dataflow between both external and internal sources.
  • An easy-to-use interface will enable data scientists to work with data more easily. The code-free platform will make it easier for the staff to complete the ETL process.
  • Customizable data transformation modules enable the definition of the data structure. The tool should simplify complex transformation tasks to increase productivity.
  • The ETL platform should ensure the best data quality because it is one of the main reasons enterprises choose an ETL tool.
  • ETL tool should simplify enterprise-wide ETL process with automatic scheduling and orchestration. It will help business users extract data quickly for time-sensitive business tasks.

Enterprises are moving forward from centralized data repositories to cloud-based data warehouse solutions. The ETL pipeline has to be upgraded and updated for cloud migration services. Using cloud-native tools will ensure that the data is loaded into the cloud in a scalable and cost-effective manner. If an organization already has implemented ETL on-premise, it should look for a service provider that can offer automatic code conversion to migrate to the cloud. 

Apptread is a comprehensive software testing company that can help any organization expedite its digital transformation journey. Contact us for cloud migration services.