Cloudera

SEPTEMBER 17, 2020

With growing disparate data across everything from edge devices to individual lines of business needing to be consolidated, curated, and delivered for downstream consumption, it’s no wonder that data engineering has become the most in-demand role across businesses — growing at an estimated rate of 50% year over year.

Data Engineering 104

Data Engineering Engineering Data Tools 104

Cloudera

NOVEMBER 19, 2021

As we explain in our eBook , COPML is a comprehensive approach to ML model development and operation that takes a structured approach to the “ML wrangling” problems many enterprises face. An enterprise machine learning workflow from data engineers to business users. COPML: The Glue That Holds It All Together.

Artificial Inteligence 122

Artificial Inteligence Machine Learning eBook Data Engineering 122

Cloudera

APRIL 13, 2021

We recently published a Cloudera Special Edition of Production Machine Learning For Dummies eBook. Chapter six of the eBook focuses on the 10 steps for making ML operational. Your data scientists will want a platform and tools that give them practical access to data, compute resources, and libraries. Optimize later.

Artificial Inteligence 98

Artificial Inteligence Machine Learning Enterprise eBook 98

DataRobot

NOVEMBER 12, 2021

Of the organizations surveyed, 52 percent were seeking machine learning modelers and data scientists, 49 percent needed employees with a better understanding of business use cases, and 42 percent lacked people with data engineering skills. A reduction of model development time from six weeks to just one. Download Now.

Machine Learning 98

Machine Learning Artificial Inteligence eBook Survey 98

TIBCO - Connected Intelligence

AUGUST 10, 2020

Taking action to leverage your data is a multi-step journey, outlined below: First, you have to recognize that sticking to the status quo is not an option. Your data demands, like your data itself, are outpacing your data engineering methods and teams. Data virtualization presents a compelling financial case.

Virtualization 69

Virtualization Data How To Data Engineering 69

TIBCO - Connected Intelligence

MAY 20, 2020

Organizations need to realize the value of data science and machine learning models holistically, rather than as simply a process of developing models. While data science and ML processes are focused on building models, Model Ops focuses on operationalizing the entire data science pipeline within a business system.

Data 72

Data Machine Learning Artificial Inteligence How To 72

Cloudera

NOVEMBER 16, 2022

There is a clear consensus that data teams should express their goals and results in business value terms and not in technical, tactical descriptions, such as “improving data engineering” and “better master data management.” . In another firm, the head of the data office also owns the digital channels.

Data 81

Data Insurance Metrics eBook 81