What do data analytics pros need from IT? Plenty!

Enterprises want and expect a lot from their data analytics initiatives and their data science professionals, including greater insights into customers, markets, business processes, logistics, employee performance, and much more.

If that seems like a lot to ask for, well, it is. But something that gets overlooked in the conversation regarding what data analytics can do for an enterprise is what IT can do for the data analytics team. Which is plenty, according to data analytics consultant and author Meta Brown in a new Forbes column.

Not surprisingly, most of what your big data analytics team needs centers around the accessibility and quality of data. Often that means large data sets, including raw data. Regarding the latter, Meta writes, “Never dispose of data without a good reason. …I am routinely forced to tell business people that it is not possible to perform the analysis they desire because they have not saved historic data, or have kept only aggregated data.” So in the case of data, hoarding is a good thing.

While they want raw data, your data analyst professionals also need data that are “current, complete, consistent and correct,” she says. Oh, and “organized appropriately.” These requirements may seem inconsistent with the need for raw data, but they’re not; raw data basically means all data, not data in an unkempt, messy pile.

Data are just the beginning. Your data analytics pros also need to be able to access that data as required. They’ll need sufficient computing power, of which Meta writes, “They often don’t know how to estimate their own requirements. This is [IT’s] opportunity to be a hero, by acting as a go-between with vendor sales or tech support staff to scope those requirements.”

Keeping all that raw data means ensuring your data team has plenty of storage space. Again, this probably is an area where IT can provide valuable input.

Naturally, your data analytics pros will need the tools necessary to do the analytics required for your enterprise, along with more tools (such as data visualization software) to organize and share their work.

Enterprises ask much of their data analysts. In return, your data pros must rely on IT to help them do their jobs effectively.

Is your IT department giving your data analysts what they need to succeed?

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