Remove data-culture-gap-report
article thumbnail

Generative AI in the Enterprise

O'Reilly on Data

Our survey focused on how companies use generative AI, what bottlenecks they see in adoption, and what skills gaps need to be addressed. As of November 2023: Two-thirds (67%) of our survey respondents report that their companies are using generative AI. And only 33% report that their companies aren’t using AI at all.

article thumbnail

Bridging the Gap: How ‘Data in Place’ and ‘Data in Use’ Define Complete Data Observability

DataKitchen

Bridging the Gap: How ‘Data in Place’ and ‘Data in Use’ Define Complete Data Observability In a world where 97% of data engineers report burnout and crisis mode seems to be the default setting for data teams, a Zen-like calm feels like an unattainable dream.

Testing 173
Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

DataOps Observability: Taming the Chaos (part 1)

DataKitchen

Observability is a methodology for providing visibility of every journey that data takes from source to customer value across every tool, environment, data store, team, and customer so that problems are detected and addressed immediately. to monitor your data operations. This solution sits on top of your existing infrastructure?without

Testing 173
article thumbnail

Closing Data's Last-Mile Gap: Visualizing For Impact!

Occam's Razor

I worry about data’s last-mile gap a lot. As a lover of data-influenced decision making, perhaps you worry as well. The last-mile gap is the distance between your trends and getting an influential company leader to take action. Your biggest asset in closing that last-mile gap is the way you present the data.

article thumbnail

What is a DataOps Engineer?

DataKitchen

A DataOps Engineer owns the assembly line that’s used to build a data and analytic product. We find it helpful to think of data operations as a factory. We find it helpful to think of data operations as a factory. Most organizations run the data factory using manual labor. Figure 1: Ford assembly line, 1913.

Testing 154
article thumbnail

A Guide To The Methods, Benefits & Problems of The Interpretation of Data

datapine

1) What Is Data Interpretation? 2) How To Interpret Data? 3) Why Data Interpretation Is Important? 4) Data Analysis & Interpretation Problems. 5) Data Interpretation Techniques & Methods. 6) The Use of Dashboards For Data Interpretation. Business dashboards are the digital age tools for big data.

article thumbnail

Why Company Data Strategies Are Indelibly Linked with DEI

Cloudera

About the report. The Cloudera Enterprise Data Maturity Report is a global survey of 3,150 business and IT decision makers assessing organizations’ maturity when it comes to their current capabilities and handling of data and analytics.