Data pipeline tools are becoming more of a necessity for businesses utilizing analytics platforms, as a way to speed up the process.
Businesses are inundated with large amounts of data flowing through various systems, but without proper data pipeline tools, it is difficult to make use of all this inflow.
Data pipeline tools automate the process of transferring data from all systems to one destination, and in the process the tool will also transform data to make it ready for analytics platforms.
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Alongside automating the cleaning process of data, data pipelines also reduce the chances of data redundancy by providing an all-in-one source for data to be transferred to, usually a data lake or data warehouse.
This process of extracting data from multiple sources, transforming to be ready for analytics software, and loading it into one single source of truth, is called Extract, Transform, Load, or ETL.
The market for data pipeline tools has been growing significantly over the past decade, and this is projected to continue as more businesses look for ways to automate and improve in the areas of data storage and analytics.
According to a forecast from market researcher ReportLinker, the data pipeline tools market size is expected to reach $19 billion by 2028, growing at a compound annual growth rate of 19.4 percent during that period.
One of the key reasons for the growth in the market size include the reduced latency of the data transfer process available with data pipeline tools, which can boost efficiency for businesses. Multi-cloud data bottlenecks are becoming more common for businesses that are seeing their data usage increase, and are looking for tools to reduce these bottlenecks.
Another reason is the general growth of all cloud and data services. As more businesses move to some form of cloud, the necessity for clean and digestible data storage grows.
