CIO Business Intelligence

JUNE 28, 2022

Some call data the new oil. Philosophers and economists may argue about the quality of the metaphor, but there’s no doubt that organizing and analyzing data is a vital endeavor for any enterprise looking to deliver on the promise of data-driven decision-making. And to do so, a solid data management strategy is key.

Management 136

Management Internet of Things Statistics Data-driven 136

The Unofficial Google Data Science Blog

DECEMBER 14, 2021

by AMIR NAJMI & MUKUND SUNDARARAJAN Data science is about decision making under uncertainty. Some of that uncertainty is the result of statistical inference, i.e., using a finite sample of observations for estimation. But there are other kinds of uncertainty, at least as important, that are not statistical in nature.

Uncertainty 56

Uncertainty Statistics Measurement Cost-Benefit 56

Cloudera

AUGUST 20, 2020

It’s been a year filled with disruption and uncertainty. Businesses had to literally switch operations, and enable better collaboration and access to data in an instant — while streamlining processes to accommodate a whole new way of doing things. One day we were all going to the office, and the next we were working from home.

Enterprise 120

Enterprise Experimentation Uncertainty Deep Learning 120

O'Reilly on Data

SEPTEMBER 15, 2021

In June 2021, we asked the recipients of our Data & AI Newsletter to respond to a survey about compensation. There was a lot of uncertainty about stability, particularly at smaller companies: Would the company’s business model continue to be effective? Would your job still be there in a year? Executive Summary. Demographics.

Machine Learning 363

Machine Learning Statistics Reporting Consulting 363

CIO Business Intelligence

APRIL 28, 2022

Its success is one of many instances illustrating how the financial services industry is quickly recognizing the benefits of data analytics and what it can offer, especially in terms of risk management automation, customized experiences, and personalization. . compounded annual growth from 2019 to 2024. .

Analytics 90

Analytics Insurance Big Data Uncertainty 90

Srividya Sridharan

SEPTEMBER 3, 2020

And data, analytics, and AI are going to drive this future. These capabilities are becoming more crucial to stay ahead of uncertainty and change and get smarter about every aspect of your business: your customers, your suppliers and partners, your competitors, your employees, your processes, your operations, and your markets.

Data Strategy 108

Data Strategy Strategy Uncertainty Marketing 108

Sisense

SEPTEMBER 9, 2019

Mark’s team is constantly adapting to and meeting the challenges of a rapidly evolving business using cloud technologies, real-time analytics, data warehousing, and virtualization. What if we could use this data to focus our resources and deliver better products? Using Sentiment Analytics to Inform New Product Design Decisions.

Predictive Analytics 75

Predictive Analytics Predictive Modeling Forecasting Data-driven 75

CIO Business Intelligence

JANUARY 4, 2023

Cloud, sustainability, scale, and exponential data growth—these major factors that set the tone for high performance computing (HPC) in 2022 will also be key in driving innovation for 2023. As leaders in the HPC industry, we are worried about how to cool these data centers. Another big focus is on liquid cooling. [2]

Cost-Benefit 59

Cost-Benefit Machine Learning Modeling Uncertainty 59

Insight

MAY 15, 2020

However, recent hiring trends show that many tech companies are still actively hiring, especially for data-driven roles! In this time of terrifying uncertainty, some might focus on their own career journey over others. Are you hiring in data science, AI, or engineering? As unemployment in the U.S.

Uncertainty 76

Uncertainty Data Science Statistics Marketing 76

Srividya Sridharan

SEPTEMBER 3, 2020

And data, analytics, and AI are going to drive this future. These capabilities are becoming more crucial to stay ahead of uncertainty and change and get smarter about every aspect of your business: your customers, your suppliers and partners, your competitors, your employees, your processes, your operations, and your markets.

Data Strategy 40

Data Strategy Strategy Uncertainty Marketing 40

Domino Data Lab

JUNE 2, 2019

Co-chair Paco Nathan provides highlights of Rev 2 , a data science leaders summit. We held Rev 2 May 23-24 in NYC, as the place where “data science leaders and their teams come to learn from each other.” Nick Elprin, CEO and co-founder of Domino Data Lab. Introduction. Leadership. In many, many ways.

Data-driven 110

Data-driven Data Science Machine Learning Modeling 110

The Unofficial Google Data Science Blog

DECEMBER 4, 2019

by THOMAS OLAVSON Thomas leads a team at Google called "Operations Data Science" that helps Google scale its infrastructure capacity optimally. Others argue that there will still be a unique role for the data scientist to deal with ambiguous objectives, messy data, and knowing the limits of any given model.

Forecasting 113

Forecasting Data Science Statistics Uncertainty 113

The Unofficial Google Data Science Blog

APRIL 23, 2024

Crucially, it takes into account the uncertainty inherent in our experiments. Experiments, Parameters and Models At Youtube, the relationships between system parameters and metrics often seem simple — straight-line models sometimes fit our data well. The data showed us that metrics are not exactly straight-line functions of parameters.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

Cloudera

NOVEMBER 18, 2021

With so many impactful and innovative projects being carried out by our customers using the Cloudera platform, selecting the winners of our annual Data Impact Awards (DIA) is never an easy task. So, without further ado, it is with great delight that we officially publish the 2021 Data Impact Award winners! Data Lifecycle Connection.

Data Lake 73

Data Lake Cost-Benefit Digital Transformation Risk 73

O'Reilly on Data

FEBRUARY 11, 2020

We suspected that data quality was a topic brimming with interest. The responses show a surfeit of concerns around data quality and some uncertainty about how best to address those concerns. Key survey results: The C-suite is engaged with data quality. Data quality might get worse before it gets better.

Data Quality 304

Data Quality Metadata Data Governance Publishing 304

O'Reilly on Data

OCTOBER 13, 2020

From a technical perspective, it is entirely possible for ML systems to function on wildly different data. For example, you can ask an ML model to make an inference on data taken from a distribution very different from what it was trained on—but that, of course, results in unpredictable and often undesired performance. I/O validation.

Management 244

Management Metrics Machine Learning Modeling 244

Domino Data Lab

JUNE 23, 2019

Skomoroch advocates that organizations consider installing product leaders with data expertise and ML-oriented intuition (i.e., Companies with successful ML projects are often companies that already have an experimental culture in place as well as analytics that enable them to learn from data. A few highlights from the session include.

Management 110

Management Machine Learning Experimentation Metrics 110

The Unofficial Google Data Science Blog

OCTOBER 21, 2015

by NIALL CARDIN, OMKAR MURALIDHARAN, and AMIR NAJMI When working with complex systems or phenomena, the data scientist must often operate with incomplete and provisional understanding, even as she works to advance the state of knowledge. There has been debate as to whether the term “data science” is necessary.

Slice and Dice 45

Slice and Dice Experimentation Data-driven Data Science 45

O'Reilly on Data

SEPTEMBER 11, 2019

Machine learning, artificial intelligence, data engineering, and architecture are driving the data space. The Strata Data Conferences helped chronicle the birth of big data, as well as the emergence of data science, streaming, and machine learning (ML) as disruptive phenomena.

IoT 20

IoT Big Data Data Warehouse Uncertainty 20

Peter James Thomas

AUGUST 12, 2018

These normally appear at the end of an article, but it seemed to make sense to start with them in this case: Recently I published Building Momentum – How to begin becoming a Data-driven Organisation. A number of factors can play into the accuracy of data capture. Honesty of Data that is captured. Timing issues with Data.

Metrics 49

Metrics Statistics Data Quality Measurement 49

CIO Business Intelligence

FEBRUARY 14, 2024

While the past few years have left us with a business landscape scarred by the impact of economic and geopolitical uncertainties, the current AI movement has become a rocket ship for significant transformative changes set to accelerate new opportunities. That’s why business and tech leaders must build for the future now.

Data-driven 72

Data-driven Uncertainty Enterprise Business Objectives 72

Jen Stirrup

NOVEMBER 15, 2022

Why do organizations get stuck with their data? Often, this problem can be due to the organization concentrating solely on technology and data. However, organizations can be supported by a synergistic approach by integrating systems thinking with the data strategy and technical perspective. It is such a fundamental question.

Data Science 145

Data Science Digital Transformation Data-driven Measurement 145