Rocket-Powered Data Science

JULY 7, 2019

AGI (Artificial General Intelligence): AI (Artificial Intelligence): Application of Machine Learning algorithms to robotics and machines (including bots), focused on taking actions based on sensory inputs (data). Analytics: The products of Machine Learning and Data Science (such as predictive analytics, health analytics, cyber analytics).

Internet of Things 157

Internet of Things Machine Learning Manufacturing IoT 157

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

DECEMBER 12, 2016

There is, almost literally, an unlimited number of things you could focus on to create a high impact data-influenced organization. I was asked a few weeks back: " What companies should we proactively help with analytics, for free, so that they can make smarter data-influenced decisions ?" Data quality plays a role into this.

Analytics 142

Analytics Data-driven Strategy Consulting 142

CIO Business Intelligence

MAY 16, 2023

It surpasses blockchain and metaverse projects, which are viewed as experimental or in the pilot stage, especially by established enterprises. The inherent capabilities of AI–to process vast amounts of data and use learned intelligence to make decisions with extraordinary speed–enable opportunities uncovered through digital listening.

Advertising 105

Advertising Recreation/Entertainment Experimentation Data Collection 105

Smart Data Collective

JUNE 21, 2023

We also talked about some of the best AI-driven video editing applications. This frees up time for experimentation and achieving superior results. The Power of Data: How Snappic’s Software Helps Capture Valuable Insights In today’s data-driven world, understanding your customers is key to long-term success.

Software 104

Software Technology Experimentation Data-driven 104

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. It helps you to amplify what’s proven to work, throw away what isn’t, and tweak the goal-posts when data indicates that they may be in the wrong place.

Metrics 157

Metrics KPI Analytics Key Performance Indicator 157

Occam's Razor

MARCH 23, 2010

Javascript tag driven click data processed in the cloud provided through a web based front end that allows you to segment and create meaningful views of the data unique to you. Having two tools guarantees you are going to be data collection, data processing and data reconciliation organization.

Analytics 119

Analytics Consulting Metrics Experimentation 119

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. That's simply because this model is unique to my business and my understand of our data.

Modeling 125

Modeling Metrics Data Quality Data-driven 125

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.

Management 110

Management Machine Learning Experimentation Metrics 110

Ontotext

MAY 18, 2020

Ever since Hippocrates founded his school of medicine in ancient Greece some 2,500 years ago, writes Hannah Fry in her book Hello World: Being Human in the Age of Algorithms , what has been fundamental to healthcare (as she calls it “the fight to keep us healthy”) was observation, experimentation and the analysis of data.

Knowledge Discovery 72

Knowledge Discovery Experimentation Data-driven Metadata 72

Occam's Razor

SEPTEMBER 15, 2014

In this post we will look mobile sites first, both data collection and analysis, and then mobile applications. Media-Mix Modeling/Experimentation. When you analyze the data in Google Analytics (or Adobe or WebTrends or Webtrekk), this data will be in your Campaigns folder waiting for you to some pretty magnificent analysis.

Metrics 143

Metrics Reporting Analytics Marketing 143

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. St Paul’s from Madison London.

Machine Learning 105

Machine Learning Data Science Modeling Visualization 105

IBM Big Data Hub

MARCH 27, 2024

This article explores an innovative way to streamline the estimation of Scope 3 GHG emissions leveraging AI and Large Language Models (LLMs) to help categorize financial transaction data to align with spend-based emissions factors. Why are Scope 3 emissions difficult to calculate?

Experimentation 73

Experimentation Deep Learning Modeling Data-driven 73

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.

Data Science 66

Data Science Experimentation Machine Learning Data-driven 66

Occam's Razor

MAY 27, 2015

A data-first strategy is a winning formula. The content of the letter could be customized to Stephanie's data/behavior. even if you've never visited the site) has access to tons of intent signals from you right now, tons of third-party cookies that litter your browser right now, and immense Big Data and algorithms.

Marketing Analytics 155

Marketing Analytics Marketing Analytics Advertising 155

DataRobot Blog

OCTOBER 4, 2022

The shift in consumer habits and geopolitical crises have rendered data patterns collected pre-COVID obsolete. This has prompted AI/ML model owners to retrain their legacy models using data from the post-COVID era, while adapting to continually fluctuating market trends and thinking creatively about forecasting.

Forecasting 59

Forecasting Sales Data-driven Modeling 59

Occam's Razor

JUNE 6, 2007

Experimentation & Testing (A/B, Multivariate, you name it). Benchmarking (exactly how you can do it), impactful actionable executive dashboards (what they should contain), creating a data driven organization. It is a book about Web Analytics 2.0. Qualitative and quantitative. Clicks and outcomes. RSS and RIA's.

Analytics 60

Analytics Metrics Marketing Dashboards 60

CIO Business Intelligence

JANUARY 14, 2025

Experimentation: The innovation zone Progressive cities designate innovation districts where new ideas can be tested safely. This shift from traditional SOA (where services align with technical functions) to domain-oriented services represents a fundamental change in how we structure systems.

Enterprise 119

Enterprise Technology Metrics Measurement 119

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

CIO Business Intelligence

FEBRUARY 5, 2025

Being strategic about AI and measuring whether those investments are paying off requires clear goals, reliable data, and collaboration challenges many organizations struggle to overcome. Organizations already generate large volumes of high-quality data in some areas and have well-defined pain points.

Cost-Benefit 117

Cost-Benefit ROI Metrics Measurement 117

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." There is never a boring moment, there is never time when you can’t do something faster or smarter.

Marketing 138

Marketing Analytics Machine Learning Strategy 138