Formatting the data into tables or joined tables to match the dataset schema of the data warehouse.Removing, encrypting, or protecting data governed by industry or governmental regulators.Running audits to ensure data integrity and compliance.This often involves changing row and column headers for consistency, converting currencies and other measurement units, editing text strings, etc. Calculations, translations, and summarization of raw data.Filtering, cleansing, deduplication, validation, and authentication of data.The raw data is processed in the staging area, which includes data transformation and consolidation for its intended use case. This data can come from a variety of data sources, both structured and unstructured data. In other words, it enters the data pipeline. In the extraction phase, raw data is copied or exported from data source locations to a staging area. For this process to work, the data must flow freely between systems and apps. Extractĭata-driven businesses manage data from a variety of sources and use different data analysis tools to achieve business intelligence. To explain how ETL works, we need to understand what takes place in each step of the process. Load data into a target destination, such as a data warehouse.

Cleanse their data to improve its quality and make it more consistent.

However, ETL can also handle more advanced analytics, allowing teams to improve both the back-end processes and end-user experience. Using a series of rules, ETL cleans and organizes data in a way that suits specific business intelligence needs, such as monthly reporting. Over time, it has become the primary method of processing data for data warehousing workflows.ĮTL is an essential part of data analytics and machine learning processes. The ETL process has a key role in achieving business intelligence and enabling a wide range of data management strategies.Īs the popularity of databases grew in the 1970s, ETL was introduced as a way of integrating and loading data for analysis and computation.

Transform data by removing duplicates, combining similar sets, and ensuring quality.

When moving large volumes of data from different sources to a single centralized database, you need to ETL is a process that allows companies to gather data from multiple source systems and store it in a single location to analyze or visualize consolidated data.

Etl extract transform load definition