4 Ways to Make Data Analytics More Efficient

by Pam Baker

Widely available scalable data tools, cheap storage, and advanced analytics tend to make us think that seeing all data and knowing all outputs is the path to prosperity. But in truth the exercise leaves many organizations stuck on the informational highway somewhere between a boondoggle and a tar pit.

Finding a path forward that is profitable and sustainable in the face of rising cloud costs, economic uncertainty, and burgeoning environmental crises is still a struggle.

“It’s true, and easy to forget, that clear goals lead to more efficient analysis,” says Tim Panagos, chief technology officer and co-founder of Microshare, a smart building technology and data firm. “By establishing a clear business intent from the outset, analysts can focus their efforts on pertinent data, relevant tools, and suitable methodologies, thereby avoiding unnecessary detours and resource consumption.”

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