Great Expectations, a leading open-source platform for data quality, announced the results of a survey highlighting top pain points and consequences of poor data quality within organizations. Insights from 500 data practitioners (engineers, analysts, and scientists) showed that 77% have data quality issues and 91% said it’s impacting their company’s performance.
Great Expectations Study Reveals 77% of Organizations have Data Quality Issues
June 18, 2022 by Leave a Comment
The Secret to Solving the World’s Crimes Lies in Data
May 27, 2022 by Leave a Comment
In this contributed article, Chris Cardwell, Product Go-To-Market Lead for Tresata, discusses how data can help tackle the global problem that is financial crime, but there are challenges within the data itself that complicate investigations further.
insideAI News Guide to How Data Analytics is Transforming Healthcare
February 3, 2022 by Leave a Comment
This technology guide, “insideAI News Guide to How Data Analytics is Transforming Healthcare,” sponsored by Dell Technologies, provides an overview of some of the trends influencing big data in healthcare, the potential benefits, likely challenges, and recommended next steps.
Data and Analytics Leaders Report Wasting Funds on Bad Data
November 21, 2021 by Leave a Comment
As enterprises fiercely compete for data engineers, a new global poll out today by Wakefield Research and Fivetran, a leading provider of automated data integration, shows that, on average, 44 percent of their time is wasted building and rebuilding data pipelines, which connect data lakes and warehouses with databases and applications.
Almost Half of Organizations Still Struggle with the Quality of their Data
October 11, 2021 by Leave a Comment
Nearly half (48%) of organizations are still struggling to use and access quality data as underlying technology is failing to deliver on a number of critical functions. According to new research conducted by ESG in partnership with InterSystems, while organizations are looking to rapidly progress how they deliver data across the value chain, many are still faced with security (47%), complexity (38%), and performance (36%) challenges.
DataOps Dilemma: Survey Reveals Gap in the Data Supply Chain
September 22, 2021 by Leave a Comment
The survey associated with this report, commission by Immuta, focused on identifying the limiting factors in the data “supply chain” as it relates to the overall DataOps methodology of the organization. DataOps itself is the more agile and automated application of data management techniques to advance data-driven outcomes, while the data supply chain represents the technological steps and human-involved processes supporting the flow of data through the organization, from its source, through transformation and integration, all the way to the point of consumption or analysis.
DataOps Dilemma: Survey Reveals Gap in the Data Supply Chain
September 20, 2021 by Leave a Comment
The survey associated with this report, commission by Immuta, focused on identifying the limiting factors in the data “supply chain” as it relates to the overall DataOps methodology of the organization. DataOps itself is the more agile and automated application of data management techniques to advance data-driven outcomes, while the data supply chain represents the technological steps and human-involved processes supporting the flow of data through the organization, from its source, through transformation and integration, all the way to the point of consumption or analysis.
Solidifying Absolute and Relative Data Quality with Master Data Management
June 19, 2021 by Leave a Comment
In this contributed article, editorial consultant Jelani Harper highlights that contrary to popular belief, data are not the oil, fuel, energy, or life force coursing through the enterprise to inform decision-making, engender insights, and propel timely business action rooted in concrete facts. Data quality is.
2021 Trends in Data Strategy: Doing More With Less
December 22, 2020 by Leave a Comment
In this contributed article, editorial consultant Jelani Harper suggests that organizations seek technology to do more with less during today’s turbulent business conditions. Data strategy elucidates what ‘more’ entails, whether it really can be achieved with less, and the longstanding consequences of leveraging various technologies to this end. It requires companies to uncover the intricacies of proactive and reactive approaches to improve what they do poorly, enabling them to achieve what they currently can’t.
Data Quality: Fixing Typos is a $4.5 Billion Market
October 2, 2020 by Leave a Comment
In this contributed article, Kenn So, an investor at Shasta Ventures, believes that even after years of advances in data engineering and “artificial intelligence”, data quality, particularly structured tabular data, remains a big problem. In fact, it is a growing problem. But that is also why it is an exciting problem to solve.
