CIO Business Intelligence

OCTOBER 5, 2023

Sandeep Davé knows the value of experimentation as well as anyone. As chief digital and technology officer at CBRE, Davé recognized early that the commercial real estate industry was ripe for AI and machine learning enhancements, and he and his team have tested countless use cases across the enterprise ever since.

Experimentation 128

Experimentation Strategy Machine Learning Interactive 128

O'Reilly on Data

JULY 28, 2020

It’s often difficult for businesses without a mature data or machine learning practice to define and agree on metrics. Without clarity in metrics, it’s impossible to do meaningful experimentation. Experimentation should show you how your customers use your site, and whether a recommendation engine would help the business.

Marketing 362

Marketing Experimentation Metrics Testing 362

O'Reilly on Data

MARCH 31, 2020

If you’re already a software product manager (PM), you have a head start on becoming a PM for artificial intelligence (AI) or machine learning (ML). AI products are automated systems that collect and learn from data to make user-facing decisions. We won’t go into the mathematics or engineering of modern machine learning here.

Management 333

Management Machine Learning Experimentation Metrics 333

Cloudera

OCTOBER 4, 2023

In telecommunications, fast-moving data is essential when we’re looking to optimize the network, improving quality, user satisfaction, and overall efficiency. This also achieves workload isolation, so we can run mission critical workloads independent from experimental and exploratory ones and nobody steps on anyone’s toes by accident.

Data Warehouse 91

Data Warehouse Experimentation Cost-Benefit Dashboards 91

CIO Business Intelligence

NOVEMBER 7, 2022

CIOs seeking big wins in high business-impacting areas where there’s significant room to improve performance should review their data science, machine learning (ML), and AI projects. Have business leaders defined realistic success criteria and areas of low-risk experimentation? Are data science teams set up for success?

Machine Learning 127

Machine Learning Data Science Experimentation IoT 127

The Unofficial Google Data Science Blog

APRIL 23, 2024

If the relationship of $X$ to $Y$ can be approximated as quadratic (or any polynomial), the objective and constraints as linear in $Y$, then there is a way to express the optimization as a quadratically constrained quadratic program (QCQP). However, joint optimization is possible by increasing both $x_1$ and $x_2$ at the same time.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

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. On premises or in SAP cloud. Per user, per month. Free tier.

Predictive Analytics 137

Predictive Analytics Analytics Statistics Machine Learning 137

CIO Business Intelligence

JUNE 14, 2023

Candidates are required to complete a minimum of 12 credits, including four required courses: Algorithms for Data Science, Probability and Statistics for Data Science, Machine Learning for Data Science, and Exploratory Data Analysis and Visualization. The exam consists of 40 questions and the candidate has 120 minutes to complete it.

Big Data 125

Big Data Data Analytics Analytics Predictive Modeling 125

Cloudera

OCTOBER 18, 2023

Historically, firms have relied on high-cost, third-party solutions to help identify savings opportunities, however, the landscape is rapidly changing, and the emergence of AI and machine learning (ML) has ushered in a new era of possibilities.

Cost-Benefit 82

Cost-Benefit Testing Machine Learning Optimization 82

DataRobot

MARCH 10, 2021

The current generation of AI systems is powered by machine learning , a technology that involves learning by example rather than waiting for humans to manually code rules into a computer system. Set the goal to be achieved or optimized. Deploy the machine learning model into production.

Experimentation 145

Experimentation Machine Learning Key Performance Indicator Reporting 145

CIO Business Intelligence

FEBRUARY 22, 2024

With the aim to accelerate innovation and transform its digital infrastructures and services, Ferrovial created its Digital Hub to serve as a meeting point where research and experimentation with digital strategies could, for example, provide new sources of income and improve company operations.

IT 104

IT Digital Transformation IoT Cost-Benefit 104

CIO Business Intelligence

DECEMBER 19, 2023

This year’s technology darling and other machine learning investments have already impacted digital transformation strategies in 2023 , and boards will expect CIOs to update their AI transformation strategies frequently. Luckily, many are expanding budgets to do so. “94%

Digital Transformation 143

Digital Transformation Unstructured Data Machine Learning Risk Management 143

IBM Big Data Hub

DECEMBER 5, 2023

According to IBM’s latest CEO study , industry leaders are increasingly focusing on AI technologies to drive revenue growth, with 42% of retail CEOs surveyed banking on AI technologies like generative AI, deep learning, and machine learning to deliver results over the next three years.

Unstructured Data 91

Unstructured Data Cost-Benefit Experimentation Machine Learning 91

CIO Business Intelligence

APRIL 25, 2023

It is simply unaware of truthfulness, as it is optimized to predict the most likely response based on the context of the current conversation, the prompt provided, and the data set it is trained on. It’s hard to achieve a deep, experiential understanding of new technology without experimentation.

Experimentation 113

Experimentation Enterprise Deep Learning Modeling 113

Smart Data Collective

OCTOBER 13, 2022

These patterns could then be used as the basis for additional experimentation by scientists or engineers. Assembly Line Optimization. Assembly line optimization is a process that allows companies to identify and optimize their production processes, from the design phase to the assembly line. Generative Design.

Testing 112

Testing Cost-Benefit Experimentation Optimization 112

CIO Business Intelligence

OCTOBER 1, 2022

The digital transformation of P&G’s manufacturing platform will enable the company to check product quality in real-time directly on the production line, maximize the resiliency of equipment while avoiding waste, and optimize the use of energy and water in manufacturing plants. Data and AI as digital fundamentals.

Manufacturing 145

Manufacturing Digital Transformation IoT Internet of Things 145

Business Over Broadway

MAY 22, 2019

According to Gartner, companies need to adopt these practices: build culture of collaboration and experimentation; start with a 3-way partnership among executives leading digital initiative, line of business and IT. Also, loyalty leaders infuse analytics into CX programs, including machine learning, data science and data integration.

Machine Learning 40

Machine Learning Technology Digital Transformation Data Science 40

CIO Business Intelligence

MAY 30, 2024

I’ve given colleagues the freedom to do research and experimentation together with our automation partner Mauden,” says Ciuccarelli. “We In fact, machine learning models and generative AI, being based on neural networks, risk greater drifts and need exact prompts,” he says.

Cost-Benefit 117

Cost-Benefit Sales Modeling Experimentation 117

CIO Business Intelligence

JANUARY 9, 2024

Retrieval Augmented Generation (RAG), which provides a way to optimize LLM output without altering the underlying LLM model, seems to be the best and most practical framework to do so. Much of the LLM development and deployment work includes experimentation and creative use of prompts.

Enterprise 117

Enterprise Experimentation Modeling Data-driven 117

DataRobot Blog

JULY 28, 2022

Rapid advances in machine learning in recent years have begun to lower the technical hurdles to implementing AI, and various companies have begun to actively use machine learning. The accuracy of machine learning models is highly dependent on the quality of the training data. Sensor Data Analysis Examples.

Data Science 72

Data Science Machine Learning Statistics Modeling 72

CIO Business Intelligence

JUNE 12, 2023

It can be about anything from classic data analysis and advanced data analysis, to robotics or machine learning. The vast majority of companies already have a structure for analytics and machine learning, so we’re already there; it doesn’t add much,” she adds. It’s all called AI, she says.

Sales 52

Sales Machine Learning Experimentation Deep Learning 52

CIO Business Intelligence

SEPTEMBER 12, 2022

Prioritize time for experimentation. A sure-fire formula for driving innovative growth is to “try something new, learn fast, pivot as needed, and scale success,’’ says Mike Crowe, CIO of Colgate-Palmolive. The team was given time to gather and clean data and experiment with machine learning models,’’ Crowe says.

Experimentation 133

Experimentation Consulting Technology Machine Learning 133

DataRobot

JANUARY 13, 2022

To move from experimental AI to production-level, trustworthy, and ROI-driven AI, it’s vital to align data scientists, business analysts, domain experts, and business leaders to leverage overlapping expertise from these groups. DataRobot combines traditional data science approaches and the best in emerging machine learning.

ROI 52

ROI Machine Learning Experimentation Data Science 52

CIO Business Intelligence

FEBRUARY 14, 2024

Introduce gen AI capabilities without thinking about data hygiene, he warns, and people will be disillusioned when they haven’t done the pre work to get it to perform optimally. At the beginning of 2023, Gartner reported only 15% of organizations already have data storage management solutions that classify and optimize data.

IT 143

IT Metadata Data-driven Management 143

CIO Business Intelligence

MARCH 21, 2022

Data scientists are becoming increasingly important in business, as organizations rely more heavily on data analytics to drive decision-making and lean on automation and machine learning as core components of their IT strategies. Data scientist job description. Get the latest insights by signing up for our newsletters. ]

Unstructured Data 136

Unstructured Data Data Analytics Analytics Structured Data 136

CIO Business Intelligence

JUNE 28, 2023

Many CIOs have become the de facto generative AI professor and spent ample time developing 101 materials and conducting roadshows to build awareness, explain how generative AI differs from machine learning, and discuss the inherent risks. Experimentation with a use case driven approach.

Enterprise 52

Enterprise Experimentation Risk Data-driven 52

Occam's Razor

MARCH 23, 2021

A key part of how this manifested in our work was doing truly super-advanced machine-learning powered analysis to answer hard questions that few can successfully. You have the start of a fabulous in-flight optimization engine. This is of course exciting and very cool. More shouting is not really better – and it is expensive!

Analytics 131

Analytics Scorecard Strategy Testing 131

DataRobot Blog

JANUARY 10, 2023

Most, if not all, machine learning (ML) models in production today were born in notebooks before they were put into production. Data science teams of all sizes need a productive, collaborative method for rapid AI experimentation. Capabilities Beyond Classic Jupyter for End-to-end Experimentation. Auto-scale compute.

Experimentation 52

Experimentation Machine Learning Data Science Modeling 52

CIO Business Intelligence

OCTOBER 9, 2023

Hyatt’s experimental mindset and listen-first approach are heavily applied to IT’s pursuit of innovation, he says. I think of it almost like a machine learning algorithm called ‘multi-armed bandit,’” that has two axes: exploit and explore, he says. I have to close the gaps,” he says.

Strategy 136

Strategy Technology Experimentation Testing 136

DataRobot

JUNE 8, 2021

Because cluster analysis is an unsupervised algorithm, it does not attempt to select groups that optimize business goals. Modern machine learning algorithms use the exact attributes and historical behavior sequences of individual consumers to predict the next best action you can take that will build their engagement with your brand.

Data-driven 98

Data-driven Testing Marketing Experimentation 98

Cloudera

APRIL 13, 2021

You’ve probably heard it more than once: Machine learning (ML) can take your digital transformation to another level. Unfortunately, most organizations run into trouble when it comes to bridging the gap that exists between experimentation and full-scale ML production. Optimize later. Step 4: Iterate quickly.

Machine Learning 98

Machine Learning Enterprise Experimentation Modeling 98

Insight

MARCH 27, 2019

It utilizes Bayesian optimization for discovering data augmentation strategies tailored to your image dataset. To address this problem, Google published AutoAugment last year, which discovers optimized augmentations for the given dataset using reinforcement learning. DeepAugment is an AutoML tool focusing on data augmentation.

Optimization 75

Optimization Cost-Benefit Modeling Strategy 75

IBM Big Data Hub

APRIL 18, 2024

While leaders have some reservations about the benefits of current AI, organizations are actively investing in gen AI deployment, significantly increasing budgets, expanding use cases, and transitioning projects from experimentation to production. AGI wouldn’t just perceive its surroundings; it would understand them.

Cost-Benefit 90

Cost-Benefit Modeling Manufacturing Interactive 90

FineReport

DECEMBER 19, 2019

When it comes to data analysis, from database operations, data cleaning, data visualization , to machine learning, batch processing, script writing, model optimization, and deep learning, all these functions can be implemented with Python, and different libraries are provided for you to choose. From Google.

Knowledge Discovery 98

Knowledge Discovery Visualization Experimentation Reporting 98

Domino Data Lab

JANUARY 24, 2019

These “automated machine learning” solutions help spread data science work by getting non-expert data scientists in to the model building process, offering drag-and-drop interfaces. These data scientists require the flexibility to use a constantly-evolving software and hardware stack to optimize each step of their model lifecycle.

Data Science 65

Data Science Marketing Data-driven Statistics 65

CIO Business Intelligence

MAY 9, 2024

Experimentation drives momentum: How do we maximize the value of a given technology? Via experimentation. This can be as simple as a Google Sheet or sharing examples at weekly all-hands meetings Many enterprises do “blameless postmortems” to encourage experimentation without fear of making mistakes and reprisal.

Enterprise 120

Enterprise Experimentation Sales Optimization 120

O'Reilly on Data

MAY 14, 2020

This role includes everything a traditional PM does, but also requires an operational understanding of machine learning software development, along with a realistic view of its capabilities and limitations. 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