New Research from Sigma Computing Reveals Frustration, Embarrassment, and Insecurity Dominate the Data Conversation
SAN FRANCISCO—June 16, 2020—Sigma Computing, an innovator in cloud-native analytics and business intelligence (A&BI), released a new research report today entitled, "Breaking Down the Data Barrier". The report outlines the notable tension between data teams and business domain experts when it comes to building data-driven organizations and the barriers both teams find in generating insights that drive business outcomes. As a result, frustration, embarrassment, and job dissatisfaction are rising to the surface. The report illustrates a stark gap in data confidence and perceptions of what it means to be data-driven. The lack of data literacy and collaboration between data and domain experts may be working against the desire to build a culture around data exploration and insights. Despite this mounting pressure to be data-driven, 39 percent of business domain experts admit they are “not totally sure” how to define the term in practice. A third (34 percent) of domain experts admit they are not confident in their ability to articulate data questions or needs to their data teams, and 30 percent are embarrassed by their lack of data knowledge.
Data experts, on the other hand, feel insecure about the results they are able to deliver, compounding the tension between the teams. Nearly half (46 percent) of data experts admit that their lack of domain expertise gets in the way of delivering the most accurate or relevant reports. Domain experts agree that the deliverables data experts provide are missing the mark with a fifth (20 percent) of domain experts reporting they rarely or never feel as though their data needs are adequately met by their data team. “We can’t divorce data from people. The power that data holds for any organization is directly dependent upon the ability of analysts and domain experts alike to apply their unique expertise to the data exploration and analysis process,” said Sigma Computing CEO Mike Palmer. “In order for there to be meaningful data-driven progress and team cohesion, you can’t expect analysts to be experts in every business function - you have domain experts for that. BI tools should bring teams together - not divide them - and support a community-driven approach to discovering insights.”
More than half (55 percent) of data experts in the survey admit that the average turnaround time for a data request is between one and four weeks. Stuck waiting for data that doesn’t always address their needs, domain experts are quick to abandon their pursuit. In fact, 93 percent of domain experts use either Excel or Google Sheets to do their own data analysis and they are not alone with 88 percent of data experts doing the same. Working with company data in this way creates security and governance vulnerabilities, as well as potentially inaccurate or outdated data being used to make critical decisions. “With organizations dispersed and millions of people working from home, communication issues and a lack of shared tools for data access may be aggravating the tensions we see highlighted in the report, not to mention increasing security and governance vulnerabilities,” added Palmer. “The only way to truly get the most out of data is to enable marketers, sales ops managers, and all domain experts to work alongside the data team in a single tool, driving the data agenda and aligning it with business priorities and goals.”
Sigma Computing also unveiled the latest version of its platform today, which includes dynamic dashboards and enhanced embedded analytics capabilities that extend the value of Sigma across data ecosystems and support a community-driven approach to A&BI.
About the research
“The Data Language Barrier: Bridging the Gap between Data and Business Teams” report is based on research commissioned by Sigma Computing and conducted by Atomik Research, an independent creative market research field agency. Atomik surveyed 801 data experts and 800 lines of business employees from companies with 201-10,000 employees within the United States. The margin of error fell within +/- 3 percentage points with a confidence interval of 95 percent. The fieldwork took place between March 2 and March 9, 2020.
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