New data from Alteryx (www.alteryx.com) says data professionals are wasting half of their time each week finding, protecting, or preparing data —costing organizations significant amounts of money. The study is based on a survey of 400-plus individuals performing data functions across North America and Europe.
Despite massive growth in data analytics demand globally, this new study shows that there is still much work to be done for organizations to get the most of their data assets and infrastructures, particularly when it comes to data discovery and cataloging, according to the analytics platform. Data professionals are spending more time governing, searching and preparing data than they are on extracting business value. Among the findings:
° Data professionals spend 60% of their time getting to insight, but just 27% of that time is spent on actual analysis. Instead, 37% of that “getting to insight” time is spent searching for data and 36% of that time is spent preparing data.
° These data workers waste 30% of their time—on average 14 hours per week—because they cannot find, protect or prepare data. They waste another 20% of their time—10 hours per week—building information assets that already exist. In total, they lose 50% of their time every week on unsuccessful activities or repeating efforts.
° Even though data discovery and integrity is important for business, 30% to 50% of organizations say they are not where they want to be.
° The inefficiencies of data intelligence and knowledge is costing U.S. organizations $1.7 million per year for every 100 employees, and European organizations €1.1 million per year for every 100 employees.
“It is evident that many professionals are not aware of what resources are available within data assets like data lakes, how to access the data, where it came from, or how to glean trusted insights,” said Langley Eide, chief strategy officer at Alteryx, Inc. “Unless organizations make changes to their infrastructure now, and close the gaps on data discovery, integrity and cataloging, processes will only become more inefficient as data volume and variety continues to grow.”