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ETL is the process used to copy, combine, and convert data from different sources and formats and load it into a new destination such as a data warehouse or data lake.
What Is ETL?
Extract, transform, load — better known as ETL — is a data integration process used to copy, combine,
and convert data from different sources and formats and load it into a new destination such as a data warehouse or
data lake. Once it’s there, the data can be analyzed to help drive business decisions.
ELT — extract, load,
transform — is similar, but data is transformed after it’s loaded to the new destination.
Why Is ETL Important?
ETL’s ability to extract and integrate data from a variety of source systems — including customer, geospatial,
and demographic data — means less of a burden on IT and more opportunity for self-service analytics.
ETL is a vital part of any
data management strategy and is often used to migrate data in the case of an acquisition or system upgrade. While it
allows businesses to react quickly, it also provides a historical view that puts data into context.
How ETL Works
ETL is an easy, accessible, and automated way to aggregate diverse data, whether in different formats or from
different systems or data sources, and make it analysis-ready.
A key part of the process,
data governance, outlines the policies and procedures surrounding data handling. This includes infrastructure and
technology as well as the people responsible for overseeing the entire process. Data governance is crucial for
businesses because it allows for more reliable data; reduced costs; a single source of truth; and regulatory, legal,
and industry compliance.
The Future of ETL
Traditional ETL tools, reliant on SQL, manual coding, and IT
experts, result in a rigid, siloed environment that prevents speed and efficiency. As business needs change, data
— and the ability to analyze it quickly and accurately — is more important than ever. Modern ETL
programs allow for analytics automation, a more efficient way to transform raw data from different
sources into valuable insights that drive decisions.
Getting Started With ETL
A finely-tuned ETL program can allow for faster, more educated decision-making. Alteryx Analytics Automation makes
the ETL process easy, auditable, and efficient, and its low-code, no-code, drag-and-drop interface means anyone can
The flexibility of the Alteryx Platform allows businesses to:
- Extract data from multiple sources such as Snowflake, Tableau, Azure, and AWS using the Input Data Tool or prebuilt connectors. The open API also allows users to build their own API connections.
- Transform messy, disparate data using a suite of drag-and-drop automation tools such as Filter, Data Cleansing, and Summarize
- Receive powerful predictive, spatial, and statistical analytics
- Load data to its target destination using the Output Data or Write Data IN-DB Tools, a process that can be easily reproduced.