Luke Han is a Co-Founder and CEO of Kyligence, as well as co-founder and Project Management Committee member for Apache Kylin.
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When it comes to analyzing data, pulling the information from a data mart as opposed to a data warehouse or external data sources can save companies time and produce more targeted results.
The idea of data marts isn’t a new concept — they’ve been around for at least a decade — and traditionally these data marts have been built inside a company, acting as a bridge between data warehouses and analysts. But as organizations collect more and more data, being able to access smaller data sets to pull out insights becomes more important, and it’s time to start looking at how data marts can be better utilized, and, importantly, what the next generation of data marts can bring.
The Challenges Of Canned And Siloed Data
When data collection first became a tool in an organization’s strategy, a data analyst was a singular position. These days, with multiple layers of data surrounding everything a company does, everyone in a company is, in part at least, a data analyst, consuming and contributing new data. From employees in the finance department to those in marketing or sales or developers — there is no area that data does not touch.
The issue however, is that data today is often still siloed in multiple different clouds, and notoriously hard to gather in one singular platform. Harder still is creating value from these disparate clouds that do not talk to each other. It’s a technical bottleneck that often strangles or altogether halts the use of some data. Current data marts can help break this down by presenting selected, canned data; customers can only choose what already exists.
But what if the data mart was more like a customer-to-customer market, where everyone can bring what he or she has into the market, where it combines with others’ product, to become a new product. For example, what if I have a great teacup, and you have a great teapot? Combining them together not only creates an excellent tea set, it also adds more value.
That’s a next-generation data mart.
Next-generation data marts rethink the traditional structure in order to better meet the needs of companies so they can utilize more data from multiple sources in a more accessible way.
Data As A Product
With a next-generation data mart, where data is combined, everyone involved with this data can evolve and innovate to create new products and add value to existing data. But to do so, data must be easy to share, and data must be connected, rather than collected.
Data needs to be able to be spread wider so it can influence more people. Next-generation data marts offer collaboration, which in turn offers broader exposure. If data is only used within a company, the value of that data is severely limited. It needs to be shared, and by doing so through next-generation data marts that connect and collaborate, its value is limitless. When data can be converted into a product, it can be used widely inside and outside of the company, and easily shared with other teammates as well as clients or customers.
Companies across the industry are increasingly moving to next-generation data marts as a way to boost value. It’s along the same lines as the idea of data mesh, or the realization that a business unit has to be willing to implement their data as a product to gain value from it is pervasive. This data mesh means multiple domain data can be combined to create a new product. As that occurs more frequently, data becomes active and creates and compounds more value from each domain.
Leveraging next-generation data marts enables an organization to change the mindset of how it looks at data. Before this shift, data marts were used as an inside enterprise for in-house business intelligence. When you shift the mindset, data becomes a product, and the data mart becomes a new market where you can gain value from data, and increase the potential of your data, all in one place.
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