ETL and modern businesses
Modern companies are undergoing a digital transformation, and data is fueling this change. Extract, Transform, Load (ETL) is at the heart of this transformation by providing a process to combine and transform data from disparate sources. This allows businesses to make better decisions faster.
Traditional methods of data transformation are no longer adequate in today’s market. Data is coming in at an ever-increasing rate and in a variety of formats. ETL provides the necessary process to quickly and easily move this data to where it needs to be. It also allows for the transformation of the data so that it is in the correct format for the downstream applications.
Data is increasingly becoming interconnected with each other through these systems, which also enables sharing across business units. By standardizing on common platforms and data models, companies can unlock a new level of insights and intelligence.
ETL is playing a leading role in this transformation by providing the necessary capabilities for data ingestion, cleansing, transformation, and loading into target systems. It enables businesses to quickly get value from their data by helping to:
- Filter out noise and redundancy in data from multiple sources
- Create a unified view of data from different systems
- Integrate data from legacy applications
ETL bridges operational, transactional data sources with big data for analytics or business intelligence. In this article, we will take a closer look at how ETL is being used to power digital transformations and the benefits that it brings.
What is ETL?
Extract, Transform, and Load (ETL) is a process for extracting data from various sources, cleaning and transforming it into a unified format, and loading it into a target system. The ETL process can move data between different systems or load data into a data warehouse or big data platform.
The three main steps in the ETL process are:
- Extract: Extracting data from source systems into a staging area.
- Transform: Cleaning and transforming the data into a unified format.
- Load: Loading the data into a target system.
Together, these three steps make up the core of an Extract-Transform-and-Load (ETL) solution.
The ETL process enables organizations to extract, cleanse, and load data across different systems. It uses a staging area as a “pre-production” environment where data is transformed and prepared for loading into a target system.
How ETL Is used in modern business
ETL enables companies to get more value out of the data assets they already have. It helps them integrate existing systems, enable analytics, and increase performance management capabilities by standardizing on common platforms and data models. By harnessing the power of ETL, businesses can:
Filter out noise and redundancy in data from multiple sources
One of the main benefits of ETL is that it helps companies to filter out noise and redundancy in data from multiple sources. This can be done by extracting data from source systems into a staging area to be cleaned and transformed.
Take, for example, a fast-food restaurant chain that wants to use historical data to perform analysis on foot traffic patterns. There are multiple data sources available for this purpose:
- POS transactions: Register transactions are the main source of information about customer behavior within a store. But these records are limited in what they can tell you–they don’t include data about customers who used a credit or debit card, for example.
- Customer loyalty cards: Loyalty cards can provide valuable insights into customer behavior, such as purchase frequency and average spending.
- Survey data: A survey of customers can give you information about why they visit the store, what they buy, and how often they visit.
The restaurant chain can extract data from all of these sources and cleanse and transform it into a unified format by using ETL. This will help them get a more complete view of customer behavior and make better business decisions.
Create a unified view of data from different systems
Another benefit of using modern data transformation (ETL) tools is that it helps to create a unified view of data from different systems. This can be done by extracting data from source systems into a staging area, where it can be transformed and loaded into the target system.
For example, let’s say that a business wants to create a view of customer data that combines information from multiple sources. These sources may include transactional systems (such as ERP software), marketing automation systems, and other internal and external sources. By using ETL, the company can get the unified view of customer data they need while still allowing access to source data systems.
Enable analytics and business intelligence
ETL enables business users to more easily perform their own analytics on the data they have access to, whether or not it is stored in a centralized location. This is because ETL provides a more unified view of data from multiple systems and sources that can be transformed into a format that is easier for people to understand.
In addition, ETL is used to support business intelligence (BI) visualizations. A leading BI application like Domo allow users to connect, transform, and visualize data, and so much more, all within a single product. Using a BI application that let’s you do all of this in one system allows businesses to get more value from their data and make better decisions based on that data.
Enable performance management
ETL can also be used to help businesses track and improve the performance of their business processes. This is done by standardizing a common data model across different systems.
By using ETL, businesses can create benchmark metrics within their datasets that can be used to compare actual performance against desired performance. This helps to identify areas where performance can be improved.
Integrating ETL into your business
To maximize the benefits of using ETL, it’s essential to find a modern BI tool that allows you to standardize on a common platform and data model for all of your internal and external systems.
Many BI tools do not include robust ETL tools, but ETL within your BI tool is critical for modern businesses. ETL tools enable businesses to benefit from their data in a number of ways: it can be used to integrate data from different systems into a single view, help users perform analytics and BI on the data that’s available to them, and enable businesses to track and improve performance.
By using ETL, businesses can get the most value from their data and make better decisions based on that data.