O'Reilly on Data

JUNE 11, 2024

It is important to be careful when deploying an AI application, but it’s also important to realize that all AI is experimental. It would have been very difficult to develop the expertise to build and train a model, and much more effective to work with a company that already has that expertise. What are your specific use cases?

Modeling 339

Modeling Experimentation Interactive Data-driven 339

CIO Business Intelligence

OCTOBER 24, 2024

Noting that companies pursued bold experiments in 2024 driven by generative AI and other emerging technologies, the research and advisory firm predicts a pivot to realizing value. Forrester predicts a reset is looming despite the enthusiasm for AI-driven transformations.

ROI 127

ROI Data-driven Enterprise Experimentation 127

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 363

Management Machine Learning Experimentation Metrics 363

David Menninger's Analyst Perspectives

MAY 17, 2023

First, the amount of data they can collect and store has increased dramatically while the cost of analyzing these large amounts of data has decreased dramatically. Data-driven organizations need to process data in real time which requires AI. Nearly 9 in 10 organizations use or plan to adopt AI technology.

Modeling 147

Modeling Experimentation Data-driven Business Intelligence 147

CIO Business Intelligence

JANUARY 21, 2025

Whereas robotic process automation (RPA) aims to automate tasks and improve process orchestration, AI agents backed by the companys proprietary data may rewire workflows, scale operations, and improve contextually specific decision-making.

Cost-Benefit 142

Cost-Benefit Data-driven Strategy Marketing 142

AWS Big Data

JANUARY 15, 2025

For container terminal operators, data-driven decision-making and efficient data sharing are vital to optimizing operations and boosting supply chain efficiency. Together, these capabilities enable terminal operators to enhance efficiency and competitiveness in an industry that is increasingly data driven.

IoT 111

IoT Machine Learning Metadata Data-driven 111

Rocket-Powered Data Science

JULY 6, 2021

In at least one way, it was not different, and that was in the continued development of innovations that are inspired by data. This steady march of data-driven innovation has been a consistent characteristic of each year for at least the past decade.

Machine Learning 279

Machine Learning Data-driven Deep Learning IoT 279

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 162

Modeling Optimization Marketing Interactive 162

O'Reilly on Data

MARCH 19, 2020

We use it as a data source for our annual platform analysis , and we’re using it as the basis for this report, where we take a close look at the most-used and most-searched topics in machine learning (ML) and artificial intelligence (AI) on O’Reilly [1]. The chatbot was one of the first applications of AI in experimental and production usage.

Deep Learning 339

Deep Learning Machine Learning Data-driven Modeling 339

Occam's Razor

JANUARY 7, 2014

First… it is important to realize that big data's big imperative is driving big action. 7: 25% of all analytical effort is dedicated to data visualization/enhancing data's communicative power. #6: The organization functions off a clearly defined Digital Marketing & Measurement Model. #1.

Data-driven 142

Data-driven Consulting Reporting Marketing 142

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 300

Testing Machine Learning Consulting Data Science 300

Cloudera

SEPTEMBER 18, 2024

According to recent survey data from Cloudera, 88% of companies are already utilizing AI for the tasks of enhancing efficiency in IT processes, improving customer support with chatbots, and leveraging analytics for better decision-making.

Data-driven 91

Data-driven Optimization Experimentation Testing 91

DataRobot Blog

DECEMBER 6, 2022

Savvy data scientists are already applying artificial intelligence and machine learning to accelerate the scope and scale of data-driven decisions in strategic organizations. Other organizations are just discovering how to apply AI to accelerate experimentation time frames and find the best models to produce results.

Experimentation 145

Experimentation Forecasting Data-driven Machine Learning 145

DataKitchen

JANUARY 20, 2021

We’ll also discuss building DataOps expertise around the data organization, in a decentralized fashion, using DataOps centers of excellence (COE) or DataOps Dojos. Test data management and other functions provided ‘as a service’ . The center of excellence (COE) model leverages the DataOps team to solve real-world challenges.

Metrics 243

Metrics Experimentation Measurement Testing 243

O'Reilly on Data

APRIL 19, 2021

During the first weeks of February, we asked recipients of our Data & AI Newsletter to participate in a survey on AI adoption in the enterprise. The second-most significant barrier was the availability of quality data. Relatively few respondents are using version control for data and models. Respondents.

Enterprise 364

Enterprise Risk Modeling Manufacturing 364

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.”.

Management 313

Management Machine Learning Metrics Modeling 313

O'Reilly on Data

APRIL 4, 2024

The race to the top is no longer driven by who has the best product or the best business model, but by who has the blessing of the venture capitalists with the deepest pockets—a blessing that will allow them to acquire the most customers the most quickly, often by providing services below cost. That is true product-market fit.

Marketing 226

Marketing Finance Modeling Experimentation 226

CIO Business Intelligence

OCTOBER 4, 2022

Business leaders, recognizing the importance of elevated customer experiences, are looking to the CIO and their IT teams to help harness the power of data, predictive analytics, and cloud resources to create more engaging, seamless experiences for customers. Embed CX into your data strategy. Consider three key areas of focus: 1.

Data-driven 111

Data-driven Machine Learning Interactive Predictive Analytics 111

O'Reilly on Data

MARCH 23, 2023

It’s important to understand that ChatGPT is not actually a language model. It’s a convenient user interface built around one specific language model, GPT-3.5, is one of a class of language models that are sometimes called “large language models” (LLMs)—though that term isn’t very helpful. with specialized training.

IT 344

IT Modeling Testing Risk 344

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 125

Modeling Metrics Data Quality Data-driven 125

Corinium

JUNE 6, 2019

Are you seeing currently any specific issues in the Insurance industry that should concern Chief Data & Analytics Officers? Lack of clear, unified, and scaled data engineering expertise to enable the power of AI at enterprise scale. The data will enable companies to provide more personalized services and product choices.

Analytics 250

Analytics Insurance Forecasting Deep Learning 250

Smart Data Collective

MAY 22, 2022

Since the decisions are data-driven, you have a lower likelihood of falling victim to attacks. The decisions are based on extensive experimentation and research to improve effectiveness without altering customer experience. AI-driven protection assesses your device when a new signal is detected.

Data-driven 145

Data-driven Risk Experimentation Technology 145

CIO Business Intelligence

NOVEMBER 4, 2022

Rigid requirements to ensure the accuracy of data and veracity of scientific formulas as well as machine learning algorithms and data tools are common in modern laboratories. When Bob McCowan was promoted to CIO at Regeneron Pharmaceuticals in 2018, he had previously run the data center infrastructure for the $81.5

Data Lake 124

Data Lake IT Experimentation Data-driven 124

CIO Business Intelligence

AUGUST 20, 2024

Our mental models of what constitutes a high-performance team have evolved considerably over the past five years. Pre-pandemic, high-performance teams were co-located, multidisciplinary, self-organizing, agile, and data-driven.

IT 141

IT Digital Transformation Experimentation Risk 141

CIO Business Intelligence

SEPTEMBER 23, 2024

From the rise of value-based payment models to the upheaval caused by the pandemic to the transformation of technology used in everything from risk stratification to payment integrity, radical change has been the only constant for health plans. It is still the data. The culprit keeping these aspirations in check?

Management 115

Management Experimentation Data-driven Strategy 115

CIO Business Intelligence

SEPTEMBER 18, 2024

Even as it designs 3D generative AI models for future customer deployment, CAD/CAM design giant Autodesk is “leaning” into generative AI for its customer service operations, deploying Salesforce’s Einstein for Service with plans to use Agentforce in the future, CIO Prakash Kota says.

Digital Transformation 119

Digital Transformation Experimentation Sales Software 119

The Unofficial Google Data Science Blog

APRIL 23, 2024

Experiments, Parameters and Models At Youtube, the relationships between system parameters and metrics often seem simple — straight-line models sometimes fit our data well. That is true generally, not just in these experiments — spreading measurements out is generally better, if the straight-line model is a priori correct.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

CIO Business Intelligence

JANUARY 28, 2025

This transition represents more than just a shift from traditional systemsit marks a significant pivot from experimentation and proof-of-concept to scaled adoption and measurable value. Data sovereignty and local cloud infrastructure are expected to remain high on the agenda, particularly within the GCC countries.

Digital Transformation 52

Digital Transformation Data-driven Experimentation Strategy 52

CIO Business Intelligence

MAY 9, 2024

Its ability to automate routine processes and provide data-driven insights helps create a conducive environment for deep work. Experimentation drives momentum: How do we maximize the value of a given technology? Via experimentation. AI changes the game. It’s like “fail fast” for genAI projects.

Enterprise 122

Enterprise Experimentation Sales Manufacturing 122

CIO Business Intelligence

JUNE 16, 2022

By George Trujillo, Principal Data Strategist, DataStax. Any enterprise data management strategy has to begin with addressing the 800-pound gorilla in the corner: the “innovation gap” that exists between IT and business teams. This scarcity of quality data might feel akin to dying of thirst in the middle of the ocean.

IT 135

IT Experimentation IoT Data-driven 135

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

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

DataRobot Blog

MARCH 16, 2023

To deliver on this new approach, one that we are calling Value-Driven AI , we set out to design new and enhanced platform capabilities that enable customers to realize value faster. Best-Practice Compliance and Governance: Businesses need to know that their Data Scientists are delivering models that they can trust and defend over time.

Experimentation 98

Experimentation Data-driven Modeling Metadata 98

CIO Business Intelligence

OCTOBER 3, 2024

From budget allocations to model preferences and testing methodologies, the survey unearths the areas that matter most to large, medium, and small companies, respectively. Medium companies Medium-sized companies—501 to 5,000 employees—were characterized by agility and a strong focus on GenAI experimentation.

Testing 129

Testing Cost-Benefit Experimentation Risk 129

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 Machine Learning Experimentation 145

DataKitchen

DECEMBER 1, 2022

Data Team members, have you ever felt overwhelmed? At DataKitchen, we’re trying to give people the tools and best practices to help them succeed with data and keep their job enjoyable and rewarding. With DataOps, data teams can ship data analytics systems faster and more confidently. So don’t wait any longer.

Experimentation 130

Experimentation Data-driven Risk Optimization 130

CIO Business Intelligence

AUGUST 15, 2024

Many of those gen AI projects will fail because of poor data quality, inadequate risk controls, unclear business value , or escalating costs , Gartner predicts. In the enterprise, huge expectations have been partly driven by the major consumer reaction following the release of ChatGPT in late 2022, Stephenson suggests.

ROI 143

ROI Cost-Benefit Experimentation Deep Learning 143