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

IBM Big Data Hub

DECEMBER 5, 2023

With the rise of highly personalized online shopping, direct-to-consumer models, and delivery services, generative AI can help retailers further unlock a host of benefits that can improve customer care, talent transformation and the performance of their applications. The impact of these investments will become evident in the coming years.

Unstructured Data 96

Unstructured Data Cost-Benefit Experimentation Machine Learning 96

CIO Business Intelligence

FEBRUARY 7, 2024

Stephen Franchetti, CIO of Samsara, a fleet management SaaS provider that went public in 2021, believes the only way to optimize your AI strategy (or any emerging technology strategy, in fact) is with a bottoms-up approach. We’ve seen an ongoing iteration of experimentation with a number of promising pilots in production,” he says.

KPI 105

KPI Measurement Experimentation Finance 105

CIO Business Intelligence

MAY 12, 2022

The tools include sophisticated pipelines for gathering data from across the enterprise, add layers of statistical analysis and machine learning to make projections about the future, and distill these insights into useful summaries so that business users can act on them. Visual IDE for data pipelines; RPA for rote tasks. Highlights.

Predictive Analytics 137

Predictive Analytics Analytics Statistics Machine Learning 137

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

OCTOBER 18, 2023

In fact, some of the insights presented in this blog have been assisted by the power of large language models (LLMs), highlighting the synergy between human expertise and AI-driven insights. Portfolio Optimization Analyze a portfolio of investments and identify opportunities to optimize returns while managing risk.

Cost-Benefit 75

Cost-Benefit Testing Machine Learning Optimization 75

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 Belcorp operates under a direct sales model in 14 countries. The team leaned on data scientists and bio scientists for expert support.

Digital Transformation 105

Digital Transformation Cost-Benefit Informatics Data mining 105

CIO Business Intelligence

OCTOBER 1, 2022

The partners say they will create the future of digital manufacturing by leveraging the industrial internet of things (IIoT), digital twin , data, and AI to bring products to consumers faster and increase customer satisfaction, all while improving productivity and reducing costs. Smart manufacturing at scale is a challenge.

Manufacturing 145

Manufacturing Digital Transformation IoT Internet of Things 145

CIO Business Intelligence

FEBRUARY 14, 2024

Fundamentals like security, cost control, identity management, container sprawl, data management, and hardware refreshes remain key strategic areas for CIOs to deal with. Data due diligence Generative AI especially has particular implications for data security, Mann says.

IT 143

IT Metadata Data-driven Management 143

CIO Business Intelligence

MARCH 7, 2023

OpenAI’s text-generating ChatGPT, along with its image generation cousin DALL-E, are the most prominent among a series of large language models, also known as generative language models or generative AI, that have captured the public’s imagination over the last year. And, he says, using generative AI for coding has worked well.

Enterprise 116

Enterprise IT Experimentation Unstructured Data 116

CIO Business Intelligence

DECEMBER 29, 2023

The most pressing responsibilities for CIOs in 2024 will include security, cost containment, and cultivating a data-first mindset.” Adaptability and useability of AI tools For CIOs, 2023 was the year of cautious experimentation for AI tools. Here, we detail those and others that comprise eight of the top priorities for CIOs in 2024.

Cost-Benefit 139

Cost-Benefit Digital Transformation Consulting Strategy 139

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

SEPTEMBER 17, 2020

Today’s data tool challenges. By enabling their event analysts to monitor and analyze events in real time, as well as directly in their data visualization tool, and also rate and give feedback to the system interactively, they increased their data to insight productivity by a factor of 10. .

Experimentation 80

Experimentation Data Warehouse Dashboards Visualization 80

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

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

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

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. Likely, you’re doing better than you think. Caution is king. Looking forward.

Enterprise 52

Enterprise Experimentation Risk Data-driven 52

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

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

IBM Big Data Hub

JANUARY 17, 2023

Due to the convergence of events in the data analytics and AI landscape, many organizations are at an inflection point. Furthermore, a global effort to create new data privacy laws, and the increased attention on biases in AI models, has resulted in convoluted business processes for getting data to users. Data governance.

Data-driven 58

Data-driven Enterprise Data Governance Prescriptive Analytics 58

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

CIO Business Intelligence

APRIL 24, 2024

But to find ways it can help grow a company’s bottom line, CIOs have to do more to understand a company’s business model and identify opportunities where gen AI can change the playing field. We’re mostly still optimizing our sales and marketing processes with CRM tools,” he says. And hyper-personalization at scale.”

Sales 128

Sales Finance Experimentation Cost-Benefit 128

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?" Slay The Analytics Data Quality Dragon & Win Your HiPPO's Love! Web Data Quality: A 6 Step Process To Evolve Your Mental Model.

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

Occam's Razor

JULY 24, 2018

work (collection, processing, reporting, analysis), processes, org structure, governance models, last-mile gaps , metrics ladders of awesomeness , and… so… much… more. Remember, tools, work, processes, org structure, governance models, last-mile gaps, metrics ladders of awesomeness, and… so… much… more. The Implications of Complexity.

Analytics 93

Analytics Metrics Strategy Measurement 93

Occam's Razor

SEPTEMBER 19, 2011

How do you get over the frustration of having done attribution modeling and realizing that it is not even remotely the solution to your challenge of using multiple media channels? We have to do Search Engine Optimization. Here's the outcomes data for the control version of the experiment. We have to do Email Marketing.

Measurement 119

Measurement Advertising Testing Marketing 119

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

Occam's Razor

AUGUST 12, 2013

There are few things more complicated in analytics (all analytics, big data and huge data!) than multi-channel attribution modeling. There is lots of missing data. And as if that were not enough, there is lots of unknowable data. You'll know how to use the good model, even if it is far from perfect.

Modeling 161

Modeling Optimization Marketing Interactive 161

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

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. It’s important to understand that ChatGPT is not actually a language model. with specialized training.

IT 262

IT Modeling Testing Risk 262

IBM Big Data Hub

OCTOBER 20, 2023

Artificial intelligence platforms enable individuals to create, evaluate, implement and update machine learning (ML) and deep learning models in a more scalable way. AI platform tools enable knowledge workers to analyze data, formulate predictions and execute tasks with greater speed and precision than they can manually.

Machine Learning 83

Machine Learning Manufacturing Cost-Benefit Deep Learning 83

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

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. CIOs should consider technologies that promote their hybrid working models to replace in-person meetings.

Digital Transformation 145

Digital Transformation Data Governance Experimentation Machine Learning 145

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. Yehoshua I've covered this topic in detail in this blog post: Multi-Channel Attribution: Definitions, Models and a Reality Check. EU Cookies!) What's possible to measure.

Modeling 124

Modeling Metrics Data Quality Data-driven 124

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 Data-driven Machine Learning 66

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

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