CIO Business Intelligence

JUNE 14, 2023

Data and big data analytics are the lifeblood of any successful business. Getting the technology right can be challenging but building the right team with the right skills to undertake data initiatives can be even harder — a challenge reflected in the rising demand for big data and analytics skills and certifications.

Big Data 126

Big Data Data Analytics Analytics Predictive Modeling 126

CIO Business Intelligence

JANUARY 9, 2024

Many organizations know that commercially available, “off-the-shelf” generative AI models don’t work well in enterprise settings because of significant data access and security risks. We’re using our own databases, testing against our own needs, and building around specific problem sets. million in compute alone 2.

Enterprise 119

Enterprise Experimentation Modeling Data-driven 119

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

Insight

APRIL 28, 2020

Originally posted on Open Data Science (ODSC). In this article, we share some data-driven advice on how to get started on the right foot with an effective and appropriate screening process. Designing a Data Science Interview Onsite interviews are indispensable, but they are time-consuming.

Data-driven 53

Data-driven Data Science Experimentation Measurement 53

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

CIO Business Intelligence

FEBRUARY 21, 2023

The firm’s connected brewery IoT platform, for instance, is being used for data ingestion and edge computing in breweries, enabling local teams to analyze, adjust, test and optimize production processes, with this in-turn allowing operations to leverage real-time and historical data to support the workers on the shop floor.

Digital Transformation 105

Digital Transformation Sales Experimentation Optimization 105

CIO Business Intelligence

MARCH 7, 2023

Ready for the right applications Generative AI is ready for use in coding, administrative workflows, data refinement, and simple use cases such as pre-filling forms, says Oliver Wittmaier, CIO and product owner at DB SYSTEL GmbH, the wholly owned subsidiary of DB AG and digital partner for all group companies. Mitre Corp.

Enterprise 116

Enterprise IT Experimentation Unstructured Data 116

DataRobot

JUNE 8, 2021

The proposed cognitive benefit of personas is that humans are better at thinking in narratives than abstract data about customers. Unlike personas, however, cluster analysis is data-driven. But despite the allure of a data-driven approach, cluster analysis is arbitrary. Personas are subjectively constructed.

Data-driven 98

Data-driven Testing Marketing Experimentation 98

O'Reilly on Data

MARCH 31, 2020

AI products are automated systems that collect and learn from data to make user-facing decisions. All you need to know for now is that machine learning uses statistical techniques to give computer systems the ability to “learn” by being trained on existing data. Why AI software development is different.

Management 332

Management Machine Learning Experimentation Metrics 332

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

Occam's Razor

APRIL 8, 2013

We are far too enamored with data collection and reporting the standard metrics we love because others love them because someone else said they were nice so many years ago. Sometimes, we escape the clutches of this sub optimal existence and do pick good metrics or engage in simple A/B testing. Testing out a new feature.

Metrics 156

Metrics KPI Analytics Key Performance Indicator 156

Occam's Razor

SEPTEMBER 19, 2011

We have to do Search Engine Optimization. Then they isolated regions of the country (by city, zip, state, dma pick your fave) into test and control regions. People in the test regions will participate in our hypothesis testing. Here's the outcomes data for the control version of the experiment. None of that.

Measurement 119

Measurement Advertising Testing Marketing 119

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

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

DataKitchen

APRIL 13, 2021

This is not surprising given that DataOps enables enterprise data teams to generate significant business value from their data. Companies that implement DataOps find that they are able to reduce cycle times from weeks (or months) to days, virtually eliminate data errors, increase collaboration, and dramatically improve productivity.

Testing 307

Testing Machine Learning Consulting Data Quality 307

CIO Business Intelligence

APRIL 24, 2024

Sales and marketing departments have long been at the forefront of embracing new technologies, and according to data provided by the Alexander Group, a revenue consultancy, 80% of hundreds of survey responses detailed that CROs have formally invested in AI for their marketing teams.

Sales 128

Sales Finance Experimentation Cost-Benefit 128

Occam's Razor

DECEMBER 9, 2009

It is rare for me to work with a organization where the root cause for their faith based decision making (rather than data driven) was not the org structure. Surprisingly it is often not their will to use data, that is there in many cases. Chapter 14: HiPPOs, Ninjas, and the Masses: Creating a Data-Driven Culture.

Analytics 95

Analytics Data-driven Marketing Sales 95

datapine

MAY 20, 2020

With a powerful dashboard maker , each point of your customer relations can be optimized to maximize your performance while bringing various additional benefits to the picture. When using a CRM dashboard tool , all these benefits will come under a single data-roof, where you can access and share your data across the board.

Dashboards 265

Dashboards Reporting KPI Visualization 265

O'Reilly on Data

MAY 14, 2020

AI PMs should enter feature development and experimentation phases only after deciding what problem they want to solve as precisely as possible, and placing the problem into one of these categories. Experimentation: It’s just not possible to create a product by building, evaluating, and deploying a single model.

Management 363

Management Experimentation B2B Machine Learning 363

Occam's Razor

NOVEMBER 13, 2009

No dragging of the feet, the book starts with a bang by laying out the framework that will be the center of every company that will leverage data (qualitative, quantitative, competitive) on the web. Chapter 2 The Optimal Strategy for Choosing Your Web Analytics Soul Mate. Chapter 6 Solving the “Why” Puzzle: Leveraging Qualitative Data.

Analytics 71

Analytics Metrics Measurement Testing 71

The Unofficial Google Data Science Blog

JUNE 30, 2016

By IVAN DIAZ & JOSEPH KELLY Determining the causal effects of an action—which we call treatment—on an outcome of interest is at the heart of many data analysis efforts. In an ideal world, experimentation through randomization of the treatment assignment allows the identification and consistent estimation of causal effects.

Statistics 44

Statistics Optimization Modeling Experimentation 44

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 145

Digital Transformation Data Governance Experimentation Machine Learning 145

O'Reilly on Data

MARCH 23, 2023

Many of these go slightly (but not very far) beyond your initial expectations: you can ask it to generate a list of terms for search engine optimization, you can ask it to generate a reading list on topics that you’re interested in. Unlike labels, embeddings are learned from the training data, not produced by humans.

IT 262

IT Modeling Testing Risk 262

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

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

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 only have to think about it for five seconds to realize it passes the ultimate test for everything: Common sense.

Modeling 161

Modeling Optimization Marketing Interactive 161

Occam's Razor

JUNE 6, 2007

Experimentation & Testing (A/B, Multivariate, you name it). What's the optimal organization structure (and who should own web analytics!)? What ideas to test first on your site? The book takes a stand on issues, makes choices and cuts through the fog/FUD, in an attempt to make your life a tiny bit easier.

Analytics 60

Analytics Metrics Marketing Dashboards 60

Domino Data Lab

JULY 2, 2019

Paco Nathan ‘s latest article covers program synthesis, AutoPandas, model-driven data queries, and more. In other words, using metadata about data science work to generate code. In this case, code gets generated for data preparation, where so much of the “time and labor” in data science work is concentrated.

Metadata 105

Metadata Machine Learning Data Science Data-driven 105

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

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

AUGUST 13, 2012

The questions reveal a bunch of things we used to worry about, and continue to, like data quality and creating data driven cultures. Then you build a massive data store that you can query for data to analyze. They also reveal things that starting to become scary (Privacy! EU Cookies!)

Modeling 124

Modeling Metrics Data Quality Data-driven 124

Occam's Razor

MARCH 23, 2010

My problem with these mistruths and FUD is that they result in a ton of practitioners and companies making profoundly sub optimal choices, which in turn results in not just much longer slogs but also spectacular career implosions and the entire web analytics industry suffering. This is sad. Even a little frustrating. This instant.

Analytics 118

Analytics Consulting Metrics Experimentation 118

Occam's Razor

SEPTEMBER 15, 2014

Company UX leaders are happy to stink less by taking the sub-optimal path of responsive design, rather than create a mobile-unique experience (your customers tend to do different things on your desktop site than your mobile site!). In this post we will look mobile sites first, both data collection and analysis, and then mobile applications.

Metrics 141

Metrics Reporting Analytics Marketing 141

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

Occam's Razor

JANUARY 9, 2012

Now here's another surprise: These rules/insights/mind shifts are not about data! Here's important context (before we get into the rules for revolutionaries)… The Fundamental Web Analytics Problem Is Not Data! Most companies are astonishingly blasé about data and possibilities of measurement.

Marketing 140

Marketing B2B Measurement Risk 140

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

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