As midsize companies grow, they develop data flows and data lakes (repositories for both structured and unstructured data) that are too big for one person, or even a team, to manipulate and use effectively. And even if a company is currently deriving value from its data, the people doing the work might move on, leaving the business tasked with having to find, attract, and hire expensive data analysts in a hurry.
Automating Data Analysis Is a Must for Midsize Businesses
Three strategies to help you get started.
October 18, 2021
Illustration by Daniel Creel
Summary.
Midsize company leaders are right to be excited about the opportunities for harnessing the value in their large datasets. But the data in midsize companies tends to be messy — spreadsheets and plain-text files, many in different formats, are difficult (if not impossible) to integrate. It takes a lot of time and money to clean it up to make it useful. Poor-quality, disintegrated data can sabotage even the best initiatives, including AI designed to increase value and efficiency. HdL Companies, a Brea, California–headquartered government services firm, used their data strategically and has seen significant efficiency gains. The author offers three lessons for leaders to consider when getting started with automating data analysis.