Sisense

SEPTEMBER 12, 2019

We’ve been talking a lot recently about companies needing to use their data in order to stay in business in the future. We’ve even gone as far as saying that every company is a data company , whether they know it or not. And it can do the same for you. But what is a BI strategy in today’s world?

Strategy 81

Strategy Dashboards Diagnostic Analytics Prescriptive Analytics 81

Domino Data Lab

JULY 22, 2019

Paco Nathan presented, “Data Science, Past & Future” , at Rev. At Rev’s “ Data Science, Past & Future” , Paco Nathan covered contextual insight into some common impactful themes over the decades that also provided a “lens” help data scientists, researchers, and leaders consider the future.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

O'Reilly on Data

MAY 14, 2020

In our previous article, What You Need to Know About Product Management for AI , we discussed the need for an AI Product Manager. To understand the skills that product managers need, we’ll start with the process of product development, then consider how this process differs in different kinds of organizations.

Management 363

Management Experimentation B2B Machine Learning 363

The Unofficial Google Data Science Blog

DECEMBER 14, 2021

by AMIR NAJMI & MUKUND SUNDARARAJAN Data science is about decision making under uncertainty. But there are other kinds of uncertainty, at least as important, that are not statistical in nature. Data science and uncertainty Data Science (DS) deals with data-driven decision making under uncertainty.

Uncertainty 56

Uncertainty Statistics Measurement Cost-Benefit 56

O'Reilly on Data

MARCH 18, 2020

The update sheds light on what AI adoption looks like in the enterprise— hint: deployments are shifting from prototype to production—the popularity of specific techniques and tools, the challenges experienced by adopters, and so on. Survey respondents represent 25 different industries, with “Software” (~17%) as the largest distinct vertical.

Enterprise 311

Enterprise Deep Learning Data Governance Risk 311

datapine

AUGUST 29, 2022

The saying “knowledge is power” has never been more relevant, thanks to the widespread commercial use of big data and data analytics. The rate at which data is generated has increased exponentially in recent years. Companies, both big and small, are seeking the finest ways to leverage their data into a competitive advantage.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

Domino Data Lab

JUNE 23, 2019

Pete Skomoroch ’s “ Product Management for AI ”session at Rev provided a “crash course” on what product managers and leaders need to know about shipping machine learning (ML) projects and how to navigate key challenges. for what is and isn’t possible) to address these challenges. Session Summary. It is similar to R&D. Transcript.

Management 110

Management Machine Learning Experimentation Metrics 110

Alation

APRIL 14, 2022

Moving data to the cloud can bring immense operational benefits. However, the sheer volume and complexity of today’s enterprise data can cause downstream headaches for data users. Semantics, context, and how data is tracked and used mean even more as you stretch to reach post-migration goals.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

Domino Data Lab

MARCH 3, 2019

Paco Nathan covers recent research on data infrastructure as well as adoption of machine learning and AI in the enterprise. Welcome back to our monthly series about data science! This month, the theme is not specifically about conference summaries; rather, it’s about a set of follow-up surveys from Strata Data attendees.

Data Science 49

Data Science Deep Learning Machine Learning Modeling 49

Occam's Razor

FEBRUARY 7, 2011

Hence every once in a while I flip the tables and ask you for challenges you are facing. It is a great way to stay connected to what's most important to you (and keep the blog and its content relevant!). This past Monday I asked for your questions and you were kind enough to share some awesome questions.

Analytics 94

Analytics Measurement Metrics Predictive Analytics 94

Domino Data Lab

JULY 9, 2019

Chris Wiggins , Chief Data Scientist at The New York Times, presented “Data Science at the New York Times” at Rev. Wiggins advised that data scientists ingest business problems, re-frame them as ML tasks, execute on the ML tasks, and then clearly and concisely communicate the results back to the organization.

Data Science 112

Data Science Machine Learning Advertising Modeling 112

datapine

APRIL 16, 2019

The term ‘big data’ alone has become something of a buzzword in recent times – and for good reason. By implementing the right reporting tools and understanding how to analyze as well as to measure your data accurately, you will be able to make the kind of data driven decisions that will drive your business forward.

Data-driven 287

Data-driven Dashboards Visualization Cost-Benefit 287

datapine

DECEMBER 4, 2019

Predictive Analytics: What could happen? Predictive analytics is the practice of extracting information from existing data sets in order to forecast future probabilities. Predictive analytics is the practice of extracting information from existing data sets in order to forecast future probabilities.

Business Intelligence 212

Business Intelligence Prescriptive Analytics Analytics Predictive Analytics 212