The Modern Data Stack Is Not an End State

The finish line is an illusion

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An ongoing, iterative process

Organizations of different sizes from different industries ought to have distinct prerequisites to arrive at a solution that is considered modern enough to fulfill the needs of various teams. But as those needs are met, new ones will arise which will probably require different tools and technologies that seemed redundant earlier.

The fastest way to fulfill a need

There’s so much data being generated by organizations that their data tooling is no good unless it enables teams to get answers from data and act upon them quickly.

Going from zero to one

Technology startups need a strong foundation for customer data infrastructure — as long as they’re able to collect, store, analyze, and activate data, and do it sooner rather than later, it doesn’t matter whether they use an all-in-one solution or purpose-built ones.

Moving from one to beyond

For companies that are already reaping the benefits of a sound foundation for customer data, it becomes crucial to streamline the process of collecting new data points and making them available everywhere they are consumed.

Modern is whatever works best for you

Building a modern data stack is not an end state — it’s an iterative process with no predefined rules in terms of what tools make a data stack modern.



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