CIO Business Intelligence

NOVEMBER 11, 2024

Nate Melby, CIO of Dairyland Power Cooperative, says the Midwestern utility has been churning out large language models (LLMs) that not only automate document summarization but also help manage power grids during storms, for example. Enterprises are also choosing cloud for AI to leverage the ecosystem of partnerships,” McCarthy notes.

ROI 137

ROI Cost-Benefit Risk Experimentation 137

CIO Business Intelligence

JANUARY 2, 2025

Generative AI playtime may be over, as organizations cut down on experimentation and pivot toward achieving business value, with a focus on fewer, more targeted use cases. Either you didnt have the right data to be able to do it, the technology wasnt there yet, or the models just werent there, Wells says of the rash of early pilot failures.

Experimentation 144

Experimentation Digital Transformation Technology Finance 144

CIO Business Intelligence

DECEMBER 20, 2024

With the core architectural backbone of the airlines gen AI roadmap in place, including United Data Hub and an AI and ML platform dubbed Mars, Birnbaum has released a handful of models into production use for employees and customers alike. That number has increased to 21% in just 18 months.

IT 131

IT Unstructured Data Experimentation Data Lake 131

CIO Business Intelligence

DECEMBER 17, 2024

While genAI has been a hot topic for the past couple of years, organizations have largely focused on experimentation. Like any new technology, organizations typically need to upskill existing talent or work with trusted technology partners to continuously tune and integrate their AI foundation models. In 2025, thats going to change.

Experimentation 98

Experimentation ROI Risk Data Quality 98

O'Reilly on Data

OCTOBER 19, 2021

This is both frustrating for companies that would prefer making ML an ordinary, fuss-free value-generating function like software engineering, as well as exciting for vendors who see the opportunity to create buzz around a new category of enterprise software. The new category is often called MLOps. This approach is not novel.

IT 364

IT Testing Experimentation Software 364

CIO Business Intelligence

OCTOBER 24, 2024

As they look to operationalize lessons learned through experimentation, they will deliver short-term wins and successfully play the gen AI — and other emerging tech — long game,” Leaver said. Their top predictions include: Most enterprises fixated on AI ROI will scale back their efforts prematurely.

ROI 127

ROI Data-driven Enterprise Experimentation 127

O'Reilly on Data

MARCH 31, 2020

Instead of writing code with hard-coded algorithms and rules that always behave in a predictable manner, ML engineers collect a large number of examples of input and output pairs and use them as training data for their models. The model is produced by code, but it isn’t code; it’s an artifact of the code and the training data.

Management 363

Management Machine Learning Experimentation Metrics 363

Rocket-Powered Data Science

FEBRUARY 15, 2023

While generative AI has been around for several years , the arrival of ChatGPT (a conversational AI tool for all business occasions, built and trained from large language models) has been like a brilliant torch brought into a dark room, illuminating many previously unseen opportunities.

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Strategy Experimentation Uncertainty Machine Learning 290

CIO Business Intelligence

JANUARY 21, 2025

We may look back at 2024 as the year when LLMs became mainstream, every enterprise SaaS added copilot or virtual assistant capabilities, and many organizations got their first taste of agentic AI. AI at Wharton reports enterprises increased their gen AI investments in 2024 by 2.3

Cost-Benefit 142

Cost-Benefit Data-driven Strategy Marketing 142

CIO Business Intelligence

OCTOBER 24, 2024

In some cases, the AI add-ons will be subscription models, like Microsoft Copilot, and sometimes, they will be free, like Salesforce Einstein, he says. While AI projects will continue beyond 2025, many organizations’ software spending will be driven more by other enterprise needs like CRM and cloud computing, Lovelock says.

IT 133

IT Data-driven Recreation/Entertainment Experimentation 133

CIO Business Intelligence

AUGUST 14, 2024

Between building gen AI features into almost every enterprise tool it offers, adding the most popular gen AI developer tool to GitHub — GitHub Copilot is already bigger than GitHub when Microsoft bought it — and running the cloud powering OpenAI, Microsoft has taken a commanding lead in enterprise gen AI. That’s risky.”

Enterprise 136

Enterprise Cost-Benefit Experimentation Modeling 136

CIO Business Intelligence

OCTOBER 15, 2024

Driven by the development community’s desire for more capabilities and controls when deploying applications, DevOps gained momentum in 2011 in the enterprise with a positive outlook from Gartner and in 2015 when the Scaled Agile Framework (SAFe) incorporated DevOps. It may surprise you, but DevOps has been around for nearly two decades.

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Enterprise Testing Business Objectives Experimentation 143

DataKitchen

APRIL 13, 2021

This is not surprising given that DataOps enables enterprise data teams to generate significant business value from their data. DataOps needs a directed graph-based workflow that contains all the data access, integration, model and visualization steps in the data analytic production process. DataOps is a hot topic in 2021.

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Testing Machine Learning Consulting Data Science 300

Cloudera

JULY 27, 2021

Here in the virtual Fast Forward Lab at Cloudera , we do a lot of experimentation to support our applied machine learning research, and Cloudera Machine Learning product development. Only through hands-on experimentation can we discern truly useful new algorithmic capabilities from hype.

Data Science 117

Data Science Enterprise Experimentation Machine Learning 117

Rocket-Powered Data Science

JULY 6, 2021

MLOps takes the modeling, algorithms, and data wrangling out of the experimental “one off” phase and moves the best models into deployment and sustained operational phase. the monitoring of very important operational ML characteristics: data drift, concept drift, and model security). will look like).

Machine Learning 279

Machine Learning Data-driven Deep Learning IoT 279

DataKitchen

JANUARY 20, 2021

As DataOps activity takes root within an enterprise, managers face the question of whether to build centralized or decentralized DataOps capabilities. Centralizing analytics helps the organization standardize enterprise-wide measurements and metrics. They also can provide education and training enterprise-wide. DataOps Dojo .

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Metrics Experimentation Measurement Testing 243

CIO Business Intelligence

MAY 9, 2024

How AI solves two problems in every company Every company, from “two people in a garage” startups to SMBs to large enterprises, faces two key challenges when it comes to their people and processes: thought scarcity and time scarcity. Experimentation drives momentum: How do we maximize the value of a given technology?

Enterprise 122

Enterprise Experimentation Sales Manufacturing 122

DataRobot Blog

MARCH 8, 2023

Every modern enterprise has a unique set of business data collected as part of their sales, operations, and management processes. SAP AI Solutions: Making Business Applications More Intelligent AI is at the heart of the SAP strategy to help customers become intelligent, sustainable enterprises.

Enterprise 105

Enterprise Experimentation Machine Learning Data Science 105

Cloudera

NOVEMBER 19, 2021

We recognise that experimentation is an important component of any enterprise machine learning practice. But, we also know that experimentation alone doesn’t yield business value. Organizations need to usher their ML models out of the lab (i.e., Organizations must think about an ML model in terms of its entire life cycle.

Machine Learning 122

Machine Learning Modeling Experimentation IT 122

CIO Business Intelligence

JANUARY 9, 2024

That quote aptly describes what Dell Technologies and Intel are doing to help our enterprise customers quickly, effectively, and securely deploy generative AI and large language models (LLMs).Many Here’s a quick read about how enterprises put generative AI to work). These are notable investments of time, data, and money.

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Enterprise Experimentation Modeling Data-driven 119

CIO Business Intelligence

NOVEMBER 7, 2024

It’s federated, so they sit in the different business units and come together as a data community to harness our full enterprise capabilities. We bring those two together in executive data councils, at the individual business unit level, and at the enterprise level. We’ve structured our approach into phases.

Insurance 120

Insurance Experimentation Testing Technology 120

Cloudera

APRIL 13, 2021

Unfortunately, most organizations run into trouble when it comes to bridging the gap that exists between experimentation and full-scale ML production. At Cloudera, we spend countless hours with the world’s largest enterprises understanding where the barriers to successful ML adoption are. Still, at its core, ML is about science.

Machine Learning 98

Machine Learning Enterprise Experimentation Modeling 98

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 Unstructured Data Experimentation 116

O'Reilly on Data

OCTOBER 13, 2020

Similarly, in “ Building Machine Learning Powered Applications: Going from Idea to Product ,” Emmanuel Ameisen states: “Indeed, exposing a model to users in production comes with a set of challenges that mirrors the ones that come with debugging a model.”.

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Management Machine Learning Metrics Modeling 314

Cloudera

AUGUST 20, 2020

But out of disruption, we’ve seen incredible innovation born into the enterprise. The imperative to deliver meaningful change and value through innovation is why the Data for Enterprise AI category at the Data Impact Awards has never been more of the moment than it is today. But UOB didn’t stop there. That’s really important.

Enterprise 121

Enterprise Experimentation Uncertainty Deep Learning 121

AWS Big Data

DECEMBER 12, 2024

One-time and complex queries are two common scenarios in enterprise data analytics. In this post, we use dbt for data modeling on both Amazon Athena and Amazon Redshift. In this post, we use dbt for data modeling on both Amazon Athena and Amazon Redshift. Here, data modeling uses dbt on Amazon Redshift.

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Snapshot Recreation/Entertainment Experimentation Data Lake 79

CIO Business Intelligence

MARCH 5, 2025

Two years of experimentation may have given rise to several valuable use cases for gen AI , but during the same period, IT leaders have also learned that the new, fast-evolving technology isnt something to jump into blindly. Test every vendors knowledge of AI The large enterprise application vendors are not AI companies, Helmer says.

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Testing Measurement Technology Experimentation 99

CIO Business Intelligence

JULY 18, 2024

The early bills for generative AI experimentation are coming in, and many CIOs are finding them more hefty than they’d like — some with only themselves to blame. According to IDC’s “ Generative AI Pricing Models: A Strategic Buying Guide ,” the pricing landscape for generative AI is complicated by “interdependencies across the tech stack.”

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Cost-Benefit Experimentation Consulting Modeling 136

CIO Business Intelligence

MARCH 19, 2025

When I joined RGA, there was already a recognition that we could grow the business by building an enterprise data strategy. We were already talking about data as a product with some early building blocks of an enterprise data product program. Enterprise gen AI is where the true value is. Thats gen AI driving revenue.

Metrics 64

Metrics Enterprise Cost-Benefit Experimentation 64

IBM Big Data Hub

MARCH 4, 2024

This requires a holistic enterprise transformation. We refer to this transformation as becoming an AI+ enterprise. Figure 1: Transforming into an AI+ enterprise is at the core of what our team at IBM does An AI+ enterprise integrates AI as a first-class function across the business. times higher ROI. times higher ROI.

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Enterprise ROI Risk Strategy 96

CIO Business Intelligence

AUGUST 2, 2023

Generative AI is already making deep inroads into the enterprise, but not always under IT department control, according to a recent survey of business and IT leaders by Foundry, publisher of CIO.com. Enterprises with 5,000 or more employees were more likely (69%) to be trying the technology than smaller ones (57%).

Enterprise 98

Enterprise Experimentation Manufacturing Risk 98

CIO Business Intelligence

OCTOBER 3, 2024

CIOs have been moving workloads from legacy platforms to the cloud for more than a decade but the rush to AI may breathe new life into an old enterprise friend: the mainframe. IBM’s current z16 mainframe has baseline AI infusion for machine learning models. At least IBM believes so. There is not one way to do AI.”

Machine Learning 140

Machine Learning Experimentation Insurance Modeling 140

CIO Business Intelligence

MAY 23, 2022

Enterprises moving their artificial intelligence projects into full scale development are discovering escalating costs based on initial infrastructure choices. Many companies whose AI model training infrastructure is not proximal to their data lake incur steeper costs as the data sets grow larger and AI models become more complex.

Experimentation 137

Experimentation Cost-Benefit Data Lake Data Science 137

CIO Business Intelligence

MAY 21, 2024

With the generative AI gold rush in full swing, some IT leaders are finding generative AI’s first-wave darlings — large language models (LLMs) — may not be up to snuff for their more promising use cases. With this model, patients get results almost 80% faster than before. It’s fabulous.”

IT 131

IT Cost-Benefit Experimentation Forecasting 131

Corinium

JUNE 6, 2019

Lack of clear, unified, and scaled data engineering expertise to enable the power of AI at enterprise scale. Some of the work is very foundational, such as building an enterprise data lake and migrating it to the cloud, which enables other more direct value-added activities such as self-service. What differentiates Fractal Analytics?

Insurance 250

Insurance Analytics Forecasting Deep Learning 250

Domino Data Lab

AUGUST 6, 2021

Model Risk Management is about reducing bad consequences of decisions caused by trusting incorrect or misused model outputs. An enterprise starts by using a framework to formalize its processes and procedures, which gets increasingly difficult as data science programs grow. What Is Model Risk? Types of Model Risk.

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Risk Management Risk Modeling Enterprise 64

CIO Business Intelligence

AUGUST 29, 2024

Google has updated its Gemini large language model (LLM) with a new feature, dubbed Gems, that allows users to train Gemini on any topic of their choice and use it as a customized AI assistant for various use cases. Gems, previewed at Google I/O this year, is currently available for Gemini Advanced, Business, and Enterprise users.

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Experimentation Modeling Enterprise Marketing 128