datapine

JANUARY 31, 2022

Because things are changing and becoming more competitive in every sector of business, the benefits of business intelligence and proper use of data analytics are key to outperforming the competition. Everything is being tested, and then the campaigns that succeed get more money put into them, while the others aren’t repeated.

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

CIO Business Intelligence

MARCH 7, 2023

Some IT organizations elected to lift and shift apps to the cloud and get out of the data center faster, hoping that a second phase of funding for modernization would come. Devops teams now look to shift left security and implement continuous testing to develop more innovative, secure, and reliable features from the start.

Digital Transformation 140

Digital Transformation Data Governance Experimentation Machine Learning 140

CIO Business Intelligence

FEBRUARY 21, 2024

One is knowledge of the emerging mega trends in technology — data, AI, and machine learning — and the other is understanding organizational culture needed to advance the technology goals and to inspire contributors,” he says. We’ve done a lot of experimentation on these adaptive tools that use AI,” says Ventimiglia.

Recreation/Entertainment 119

Recreation/Entertainment Experimentation Modeling Data-driven 119

Occam's Razor

JANUARY 7, 2014

First… it is important to realize that big data's big imperative is driving big action. 7: 25% of all analytical effort is dedicated to data visualization/enhancing data's communicative power. #6: Reporting Squirrels spend 75% or more of their time in data production activities.

Data-driven 140

Data-driven Consulting Reporting Marketing 140

CIO Business Intelligence

JUNE 28, 2023

These circumstances have induced uncertainty across our entire business value chain,” says Venkat Gopalan, chief digital, data and technology officer, Belcorp. “As The R&D laboratories produced large volumes of unstructured data, which were stored in various formats, making it difficult to access and trace.

Digital Transformation 78

Digital Transformation Cost-Benefit Informatics Data mining 78

Domino Data Lab

OCTOBER 14, 2020

Guest post by Jeff Melching, Distinguished Engineer / Chief Architect Data & Analytics. We’ve developed a model-driven software platform, called Climate FieldView , that captures, visualizes, and analyzes a vast array of data for farmers and provides new insight and personalized recommendations to maximize crop yield.

Experimentation 99

Experimentation Modeling Deep Learning Testing 99

Octopai

OCTOBER 26, 2022

Data-driven organizations are a bad idea. Using data to drive your organization is wonderful. But data, at best, can only be a powerful vehicle, or a reliable GPS system. Except sometimes we call organizations “data-driven” when really the data is driving them up the wall. And it should be.

Data Quality 52

Data Quality Data Analytics Analytics Manufacturing 52

DataRobot

APRIL 19, 2021

Data Scientists Are AI Experts. But for more complex business decisions, including those that use less structured data, we have artificial intelligence systems. Data scientists train the algorithms using datasets that contain curated learning examples. They need data assembly, data science, integration, and visualization skills.

Machine Learning 52

Machine Learning Visualization Data-driven Data Science 52

DataRobot

SEPTEMBER 14, 2021

Becoming AI-driven is no longer really optional. And for those that do make it past the experimental stage, it typically takes over 18 months for the value to be realized. At the same time, business and data analysts want to access intuitive, point-and-click tools that use automated best practices.

Machine Learning 94

Machine Learning Modeling Experimentation Visualization 94

Cloudera

APRIL 9, 2021

This blog series follows the manufacturing and operations data lifecycle stages of an electric car manufacturer – typically experienced in large, data-driven manufacturing companies. The first blog introduced a mock vehicle manufacturing company, The Electric Car Company (ECC) and focused on Data Collection.

Machine Learning 98

Machine Learning Forecasting Manufacturing Predictive Analytics 98

Cloudera

JANUARY 30, 2019

It’s official – Cloudera and Hortonworks have merged , and today I’m excited to announce the availability of Cloudera Data Science Workbench (CDSW) for Hortonworks Data Platform (HDP). Trusted by large data science teams across hundreds of enterprises —. Sound familiar? What is CDSW? Install any library or framework (e.g.

Data Science 74

Data Science Machine Learning Experimentation Cost-Benefit 74

Sisense

MAY 18, 2021

If marketing were an apple pie, data would be the apples — without data supporting your marketing program, it might look good from the outside, but inside it’s hollow. In a recent survey from Villanova University, 100% of marketers said data analytics has an essential role in marketing’s future.

Marketing 52

Marketing Data Analytics Analytics Metrics 52

Occam's Razor

OCTOBER 23, 2006

The title of my presentation at the Washington DC Emetrics summit was: Creating a Data Driven Web Decision Making Culture – Lessons, Tips, Insights from a Practitioner. Seven Steps to Creating a Data Driven Decision Making Culture…… Slide 1: Decision Making Landscape. 2 Solve for the Trinity. #

Data-driven 117

Data-driven Metrics KPI Reporting 117

Domino Data Lab

JUNE 23, 2019

Skomoroch proposes that managing ML projects are challenging for organizations because shipping ML projects requires an experimental culture that fundamentally changes how many companies approach building and shipping software. Without large amounts of labeled training data solving most AI problems is not possible. Transcript.

Management 110

Management Machine Learning Experimentation Metrics 110

Domino Data Lab

MAY 8, 2019

For example, common practices for collecting data to build training datasets tend to throw away valuable information along the way. The lens of reductionism and an overemphasis on engineering becomes an Achilles heel for data science work. ML model interpretability and data visualization.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Occam's Razor

AUGUST 22, 2011

Be data driven?" Six Rules For Creating A Data Driven Boss! Be data driven?" Slay The Analytics Data Quality Dragon & Win Your HiPPO's Love! Web Data Quality: A 6 Step Process To Evolve Your Mental Model. The Ultimate Web Analytics Data Reconciliation Checklist.

KPI 124

KPI Metrics Measurement ROI 124

Alation

SEPTEMBER 28, 2022

The term has been used a lot more of late, especially in the data analytics industry, as we’ve seen it expand over the past few years to keep pace with new regulations, like the GDPR and CCPA. In essence, DataOps is a practice that helps organizations manage and govern data more effectively. What exactly is DataOps ?

Cost-Benefit 52

Cost-Benefit Data Quality Manufacturing Testing 52

Domino Data Lab

NOVEMBER 14, 2019

This Domino Data Science Field Note covers a proposed definition of interpretability and distilled overview of the PDR framework. Yet, despite the complexity (or because of it), data scientists and researchers curate and use different languages, tools, packages, techniques, and frameworks to tackle the problem they are trying to solve.

Modeling 71

Modeling Machine Learning Data Science Experimentation 71

datapine

FEBRUARY 4, 2020

Today’s digital data has given the power to an average Internet user a massive amount of information that helps him or her to choose between brands, products or offers, making the market a highly competitive arena for the best ones to survive. First things first – organizing and prioritizing your marketing data.

Reporting 280

Reporting Marketing Advertising Metrics 280

Occam's Razor

JULY 6, 2016

Analysts, honestly, make the world go round when it comes to any successful business – yes, data is that important. Today's post is an adjacent mistake: The cardinal sin of spending too much time with data and in reports! But, perhaps I'm at fault for creating the problem of you spending all your time with data.

Testing 86

Testing Marketing Experimentation Cost-Benefit 86

Occam's Razor

AUGUST 12, 2013

There are few things more complicated in analytics (all analytics, big data and huge data!) There is lots of missing data. And as if that were not enough, there is lots of unknowable data. You can visualize the impact of applying three models at one time. than multi-channel attribution modeling. " low.

Modeling 161

Modeling Optimization Marketing Interactive 161

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. Some don’t see the point.

Slice and Dice 45

Slice and Dice Experimentation Data-driven Data Science 45