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How Automated Data Pipeline Tools Can Help Speed To Market

Automated data pipeline tools can help businesses increase their speed to market, by reducing the amount of manual ETL required.

Written By
DC
David Curry
Jun 12, 2023
Automated data pipeline tools can help businesses increase their speed to market, by reducing the amount of manual ETL required.

Improving speed to market is critical for businesses to maintain a competitive edge and improve revenue generation. According to a report by consultancy firm Capgemini, businesses that focus on speeding up time to market and maintaining velocity through the use of technology solutions can also achieve immediate costs reductions and a higher return on investment.

Alongside this, businesses that focus on improving their speed to market process tend to see improvements further down the pipeline, with an increased persistence and loyalty from consumers. For patent-heavy industries such as pharmaceutical, time to market improvements can also increase the amount of time products are available commercially while their patent is active.

SEE ALSO: The Business Value of Intelligent Data Pipelines

One of the ways for businesses to speed up development and deployment is through the use of automated software, which can alleviate the need for manual input and free employee time for more demanding tasks. Data pipeline tools are one of the tools being utilized by organizations to improve time to market.

Data pipeline tools automate the extract, transform, and load (ETL) data integration process by collecting data from a wide range of sources, transforming it so it is readable by analytics and other software programs, and then loading it into a single source for truth, usually a data warehouse or lake. This process, for a lot of businesses, is still done manually and can be complicated and resource intensive.

With this tool, organizations are no longer on the back-foot when it comes to the transformation of unstructured data to actionable insights, and businesses are able to interpret data at a faster rate and use it to push development cycles at a faster rate. Like said before, it also allows employees to interpret the data, rather than simply doing the ETL process themselves.

DC

David is a technology writer with several years experience covering all aspects of IoT, from technology to networks to security.

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