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 105

Digital Transformation Cost-Benefit Informatics Data mining 105

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. Machine learning adds uncertainty.

Management 332

Management Machine Learning Experimentation Metrics 332

DataRobot

JANUARY 13, 2022

Many companies find that they have a treasure trove of data but lack the expertise to use it to improve ROI. AI can help them wrangle the data that’s collected and quickly answer important questions. But they often don’t have enough data scientists with the full range of domain expertise to realize its full value.

ROI 52

ROI Machine Learning Experimentation Data Science 52

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

Domino Data Lab

JANUARY 24, 2019

In 2018 we saw the “data science platform” market rapidly crystallize into three distinct product segments. Over the last couple years, it would be hard to blame anyone for being overwhelmed looking at the data science platform market landscape. Proprietary (often GUI-driven) data science platforms. Automation Tools.

Data Science 65

Data Science Marketing Data-driven Statistics 65

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

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. Online, offline or nonline.

Metrics 156

Metrics KPI Analytics Key Performance Indicator 156

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

Occam's Razor

SEPTEMBER 19, 2011

We have to do Search Engine Optimization. You need people with deep skills in Scientific Method , Design of Experiments , and Statistical Analysis. It is also important to point out that I am keeping the data simple purely to keep communication of the story straightforward. We have to do Email Marketing. ask for a raise.

Measurement 119

Measurement Advertising Testing Marketing 119

Occam's Razor

JULY 24, 2018

The result is analytical strategies that are uninformed by reality, and driven new tool features, random expert recommendations and shiny objects ( OMG we have to get offline attribution! ). Diving a bit deeper into the x-axis… While most data can be collected in real-time now, not all metrics are useful in real-time.

Analytics 93

Analytics Metrics Strategy Measurement 93

Corinium

APRIL 25, 2019

Ahead of the Chief Data Analytics Officers & Influencers, Insurance event we caught up with Dominic Sartorio, Senior Vice President for Products & Development, Protegrity to discuss how the industry is evolving. The last 10+ years or so have seen Insurance become as data-driven as any vertical industry.

Insurance 150

Insurance Risk IoT Cost-Benefit 150

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

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!)? Benchmarking (exactly how you can do it), impactful actionable executive dashboards (what they should contain), creating a data driven organization. Clicks and outcomes.

Analytics 60

Analytics Metrics Marketing Dashboards 60

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

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

Cloudera

NOVEMBER 25, 2020

The challenges Matthew and his team are facing are mainly about access to a multitude of data sets, of various types and sources, with ease and ad-hoc, and their ability to deliver data-driven and confident outcomes. . Most of their research data is unstructured and has a lot of variety. Challenges Ahead.

Data Warehouse 57

Data Warehouse Unstructured Data Analytics Visualization 57

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

MARCH 23, 2010

Part of it is fueled by a vocal minority genuinely upset that 10 years on we are still not a statistically powered bunch doing complicated analysis that is shifting paradigms. Having two tools guarantees you are going to be data collection, data processing and data reconciliation organization. This is sad. This instant.

Analytics 118

Analytics Consulting Metrics Experimentation 118

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

IBM Big Data Hub

SEPTEMBER 25, 2023

The magic behind Uber’s data-driven success Uber, the ride-hailing giant, is a household name worldwide. But what most people don’t realize is that behind the scenes, Uber is not just a transportation service; it’s a data and analytics powerhouse. But the simplicity ends there. What is Presto?

OLAP 96

OLAP Data Lake Data-driven Snapshot 96