Precisely

SEPTEMBER 18, 2023

Author’s note: this article about data observability and its role in building trusted data has been adapted from an article originally published in Enterprise Management 360. Is your data ready to use? That’s what makes this a critical element of a robust data integrity strategy. What is Data Observability?

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Precisely

APRIL 11, 2023

It’s a common scenario across industries: a new strategic initiative is launching, and you need trustworthy, relevant data to analyze and support the best outcomes for the business. Let’s explore some of the questions you must ask as you begin the process, then dive into the solutions for common challenges you may face.

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Data Observability Cloud Data Data Quality Data Governance 52

Precisely

MAY 16, 2024

These tools help achieve a scalable and robust AI ecosystem primed for success. When you think about the potential of artificial intelligence (AI) for your business, what comes to mind? Chances are it’s not just one use case but many.

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AI AI AWS Data Quality 59

Precisely

JULY 31, 2023

Mapping data integrity maturity to priorities We asked respondents to rate the maturity of their organization’s data integrity practices as high, moderate, or low. With 52% of respondents rating data privacy and security maturity as “high” and 36% as “moderate”, this practice has by far the highest level of maturity.

Data Quality 52

Data Quality Data Governance Analytics Analytics 52

IBM Journey to AI blog

DECEMBER 16, 2022

Since her company doesn’t have a data catalog, Alex must first communicate with the shoe line-of-business and the jewelry line-of-business departments to ask what data she needs to conduct her analysis. She also wants to predict future sales of both shoes and jewelry.

Data Quality 52

Data Quality Data Governance Data Wrangling Data Scientist 52

Precisely

JUNE 29, 2023

The 2023 Survey of Data and Analytics Professionals, from the Center for Business Analytics at Drexel University’s LeBow College of Business ( LeBow ) in partnership with Precisely, asked respondents to share the goals and outcomes of their data programs and initiatives.

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The MLOps Blog

AUGUST 3, 2023

You would ask the Hamilton DAG to compute the model, you get the model out, and then the next line, you would save it or push it to your data store – you could also write a Hamilton function that kind of does that. People came in, created issues, asked questions, and which case gave us more energy to be in there and help.

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