AWS Big Data

NOVEMBER 2, 2023

GoDaddy is a data-driven company, and getting meaningful insights from data helps us drive business decisions to delight our customers. As a part of this vision, GoDaddy’s Data & ML Platform team plans to use EMR Serverless as one of the compute solutions under the hood.

Cost-Benefit 84

Cost-Benefit Big Data Testing Optimization 84

CIO Business Intelligence

JUNE 28, 2023

For all of generative AI’s allure, large enterprises are taking their time, many outright banning tools like ChatGPT over concerns of accuracy, data protection, and the risk of regulatory backlash. Experimentation with a use case driven approach. By that measure, you will indeed have done better than you thought.

Enterprise 52

Enterprise Experimentation Risk Data-driven 52

Ontotext

NOVEMBER 2, 2023

Achieving this advantage is dependent on their ability to capture, connect, integrate, and convert data into insight for business decisions and processes. This is the goal of a “data-driven” organization. We call this the “ Bad Data Tax ”. This is partly because integrating and moving data is not the only problem.

IT 69

IT Cost-Benefit Data-driven Technology 69

Domino Data Lab

AUGUST 6, 2021

An enterprise starts by using a framework to formalize its processes and procedures, which gets increasingly difficult as data science programs grow. With a framework and Enterprise MLOps, organizations can manage data science at scale and realize the benefits of Model Risk Management that are received by a wide range of industry verticals.

Risk Management 64

Risk Management Risk Modeling Enterprise 64

Sisense

JANUARY 21, 2020

Everyone wants to get more out of their data, but how exactly to do that can leave you scratching your head. One of the simplest ways to start exploring your data is to aggregate the metrics you are interested in by their relevant dimensions. How can good data lead to faulty conclusions? How does this happen? 9/10 = 90%.

Testing 104

Testing Risk Data-driven Statistics 104

Ontotext

APRIL 3, 2024

In this post we present you with insight gathered at the Knowledge Graph Forum during the panel on Financial Services. Joseph Hilger : People are starting to understand that knowledge graphs are not just a tool for storing data and information. I need something that defines what those entities are and can align them with the data.”

Technology 59

Technology Risk Digital Transformation Measurement 59

Occam's Razor

AUGUST 22, 2011

Be data driven?" Key To Your Digital Success: Web Analytics Measurement Model. Six Rules For Creating A Data Driven Boss! Be data driven?" " Measuring Incrementality: Controlled Experiments to the Rescue! Barriers To An Effective Web Measurement Strategy [+ Solutions!].

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

O'Reilly on Data

OCTOBER 19, 2021

As with many burgeoning fields and disciplines, we don’t yet have a shared canonical infrastructure stack or best practices for developing and deploying data-intensive applications. Why: Data Makes It Different. Not only is data larger, but models—deep learning models in particular—are much larger than before.

IT 346

IT Testing Experimentation Software 346

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

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

FEBRUARY 4, 2019

In Paco Nathan ‘s latest column, he explores the role of curiosity in data science work as well as Rev 2 , an upcoming summit for data science leaders. Welcome back to our monthly series about data science. and dig into details about where science meets rhetoric in data science. Introduction. This is not that.

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66

The Unofficial Google Data Science Blog

DECEMBER 14, 2021

by AMIR NAJMI & MUKUND SUNDARARAJAN Data science is about decision making under uncertainty. This blog post introduces the notions of representational uncertainty and interventional uncertainty to paint a fuller picture of what the practicing data scientist is up against. Vignette: Data Science at fluff.ai

Uncertainty 56

Uncertainty Statistics Measurement Cost-Benefit 56

Domino Data Lab

JUNE 23, 2019

Pete Skomoroch presented “ Product Management for AI ” at Rev. 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. Session Summary. It is similar to R&D.

Management 110

Management Machine Learning Experimentation Metrics 110

AWS Big Data

NOVEMBER 14, 2023

Data is a key strategic asset for every organization, and every company is a data business at its core. However, in many organizations, data is typically spread across a number of different systems such as software as a service (SaaS) applications, operational databases, and data warehouses.

IoT 55

IoT Data-driven Data Lake Data Strategy 55

Occam's Razor

DECEMBER 12, 2016

There is, almost literally, an unlimited number of things you could focus on to create a high impact data-influenced organization. In a world when your work will never be done, how do you assess that the core things necessary are present? What guarantees that agility and innovation are present in your analytics practice?

Analytics 141

Analytics Data-driven Strategy Consulting 141

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. Hope you find it useful.

Data-driven 117

Data-driven Metrics KPI Reporting 117

O'Reilly on Data

MARCH 23, 2023

But Transformers have some other important advantages: Transformers don’t require training data to be labeled; that is, you don’t need metadata that specifies what each sentence in the training data means. Unlike labels, embeddings are learned from the training data, not produced by humans.

IT 262

IT Modeling Testing Risk 262

Occam's Razor

JUNE 6, 2007

Bonus: Interactive CD: Contains six podcasts, one video, two web analytics metrics definitions documents and five insightful powerpoint presentations. Experimentation & Testing (A/B, Multivariate, you name it). In 480 pages the book goes from from beginner's basics to a advanced analytics concepts. Clicks and outcomes.

Analytics 60

Analytics Metrics Marketing Dashboards 60

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. back to the structure of the dataset.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

Occam's Razor

JULY 26, 2010

Suggestions that might increase the probability that you'll bump into things that might be insightful, and communicate data more effectively. The data is easily available in the web analytics tool so why not. Get the data out of the crm / erp / "backend" system. Here we go. #1: 1: Go as deep as you can.

Metrics 96

Metrics Measurement Dashboards Reporting 96

Occam's Razor

SEPTEMBER 15, 2014

But why blame others, in this post let's focus on one important reason whose responsibility can be squarely put on your shoulders and mine: Measurement. Create a distinct mobile website and mobile app measurement strategies. Media-Mix Modeling/Experimentation. Framing the Opportunity. Tag your mobile website. Everything.

Metrics 141

Metrics Reporting Analytics Marketing 141

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. If you see a value greater than one, that channel has a propensity to be present earlier in the conversion cycle. " low.

Modeling 161

Modeling Optimization Marketing Interactive 161

Occam's Razor

JANUARY 9, 2012

It is a lot easier to predict the present. Rather, I'm going to share a clump of realities/rules garnered from the present to help ready you for the predictable near future. Now here's another surprise: These rules/insights/mind shifts are not about data! The problem, it turns out, is not data.

Marketing 140

Marketing B2B Measurement Risk 140

Occam's Razor

MARCH 23, 2010

Too many new things are happening too fast and those of us charged with measuring it have to change the wheels while the bicycle is moving at 30 miles per hour (and this bicycle will become a car before we know it – all while it keeps moving, ever faster). You'll have no time for data analysis, certainly not for data actioning. ~

Analytics 118

Analytics Consulting Metrics Experimentation 118

Occam's Razor

MAY 27, 2015

Because, I'm sure like you, I'm humbled by the immense opportunity digital presents. A data-first strategy is a winning formula. Apps are the past, present, future. The content of the letter could be customized to Stephanie's data/behavior. A data-first strategy is a winning formula. The web is dead.

Marketing Analytics 153

Marketing Analytics Marketing Analytics Advertising 153

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: The organization functions off a clearly defined Digital Marketing & Measurement Model. #1.

Data-driven 140

Data-driven Consulting Reporting Marketing 140

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. BI software uses algorithms to extract actionable insights from a company’s data and guide its strategic decisions.

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

Domino Data Lab

AUGUST 26, 2019

Data scientists, machine learning (ML) researchers, and business stakeholders have a high-stakes investment in the predictive accuracy of models. Data scientists and researchers ascertain predictive accuracy of models using different techniques, methodologies, and settings, including model parameters and hyperparameters. Introduction.

Testing 79

Testing Modeling Machine Learning Metrics 79

Sisense

NOVEMBER 23, 2020

The global pandemic has driven home the fact that data is vital to the success of every organization. Sisense recently surveyed over 460 companies across Australia and New Zealand to dig into their data and analytics usage and future plans. Who is leading the way?

Analytics 98

Analytics Data-driven Marketing Reporting 98

Occam's Razor

OCTOBER 12, 2017

The tiny downside of this is that our parents likely never had to invest as much in constant education, experimentation and self-driven investment in core skills. Years and years of practice with R or "Big Data." The brilliant Jeffrey Sachs systematically presents context you'll be glad you've heard.

Marketing 136

Marketing Analytics Machine Learning Strategy 136