In this contributed article, Sridhar Bankuru, VP of Software Development at RightData, walks us through the top pain points of businesses today within their data trust journey, and looking ahead, how they can start trusting their data again.
Who Done It? 3 Possible Suspects in this Halloween’s Bad Data Horror Movie, And How Data Teams Can Make It Out Alive
October 31, 2023 by Leave a Comment
In this contributed article, Lior Gavish, CTO and Co-Founder of Monte Carlo, outlines some of the ways companies can erase themselves from ever appearing in these bad data horror stories, ranging from simple tips to bolster governance within their organization, to tools and best practices that will save data teams the time, hassle, and headache that comes with dealing with bad data.
State of Data Quality Report
June 13, 2023 by Leave a Comment
Bigeye, the data observability company, announced the results of its 2023 State of Data Quality survey. The report sheds light on the most pervasive problems in data quality today. The report, which was researched and authored by Bigeye, consisted of answers from 100 survey respondents.
The Importance of Data Quality in Benefits
June 6, 2023 by Leave a Comment
In this contributed article, Peter Nagel, VP of Engineering at Noyo, addresses the benefits/insurance industry’s roadblocks and opportunities — and why some of the most interesting data innovations will soon be happening in benefits.
Study Finds Data Quality is Still the Largest Obstacle for Successful AI and Greater Human Expertise Needed Across ML Ops Lifecycle
May 28, 2023 by Leave a Comment
iMerit, a leading artificial intelligence (AI) data solutions company, released its 2023 State of ML Ops report, which includes a study outlining the impact of data on wide-scale commercial-ready AI projects. The study surveyed AI, ML, and data practitioners across industries, and found an increasing need for better data quality and human expertise and oversight in delivering successful AI. This is especially true as powerful new generative AI tools and continuous improvements to automation are rolled out at an increasingly rapid pace.
Data Quality Should Keep You Up at Night (But There’s an Antidote to Data-Induced Insomnia)
July 21, 2022 by Leave a Comment
In this sponsored post, our friends over at Acceldata examine how integrating data observability into your business operations will create the necessary environment and feedback loop needed to improve data quality, at scale, on an ongoing basis. It will also help your enterprise make the most out of all the data quality best practices your data team adopts, and will also probably enable you to get a peaceful night’s sleep.
Great Expectations Study Reveals 77% of Organizations have Data Quality Issues
June 18, 2022 by Leave a Comment
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.
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.
insideBIGDATA Guide to How Data Analytics is Transforming Healthcare
February 3, 2022 by Leave a Comment
This technology guide, “insideBIGDATA 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.
