How to choose the right data-integration tools

For data integration, pipelining, and wrangling data: Here are the seven types of tools you should build your data tool set from

How to choose the right data-integration tools

Data doesn’t sit in one database, file system, data lake, or repository. To service many business needs, data must be integrated from a system of record with other data sources and then used for analytics, customer-facing applications, or internal workflows.

Technologists working with or responsible for data technologies should be well versed on the types of tools available for the various data-integration needs. Here, I survey seven major types of tools. 

Because many organizations have different types, volumes, and velocities of data, with different business needs developed over time, it’s likely that there are already different methodologies and tools already in use to integrate data. It’s tempting to stick with those, and extend them to new use cases. Although anyone working with data tools might be more familiar with one approach over others, applying a one-size-fits-all data integration approach may not be optimal for organizations with multiple business and user needs.

In addition, there is a healthy market for big data solutions as more organizations are investing in data solutions. The result is that are now many new types of platforms and tools to support data integration and processing.

With so many tools available, organizations looking to make data processing a core capability should consider various tool types that can be applied depending on the business and technical needs.

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