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 264

Modeling Experimentation Interactive Data-driven 264

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

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 108

Data-driven Machine Learning Interactive Predictive Analytics 108

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 56

Data-driven Enterprise Data Governance Prescriptive Analytics 56

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. Fair warning: if the business lacks metrics, it probably also lacks discipline about data infrastructure, collection, governance, and much more.) Agreeing on metrics. Don’t expect agreement to come simply.

Marketing 363

Marketing Experimentation Metrics Testing 363

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 112

Management Experimentation Strategy Data-driven 112

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 108

Digital Transformation Experimentation Sales Software 108

CIO Business Intelligence

OCTOBER 31, 2024

When IT leaders consider generative AI, they should create separate strategies when rolling out productivity-enhancing AI tools than when deploying business-case-driven AI solutions, according to new research from the Massachusetts Institute of Technology. One reason may be because they have taken a one-size-fits-all approach to AI.

Data-driven 139

Data-driven Unstructured Data Experimentation Consulting 139

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 351

IT Testing Experimentation Software 351

CIO Business Intelligence

SEPTEMBER 12, 2024

Frustrated by the lack of generative AI tools, he discovers a free online tool that analyzes his data and generates the report he needs in a fraction of the usual time. A routine audit uncovers severe compliance issues with how the tool accesses and stores data. Models can produce material that may infringe on copyrights.

Experimentation 111

Experimentation Risk Cost-Benefit Strategy 111

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 140

IT Digital Transformation Experimentation Risk 140

DataRobot Blog

MARCH 16, 2023

Data scientists run experiments. To work effectively, data scientists need agility in the form of access to enterprise data, streamlined tooling, and infrastructure that just works. We’ve tightened the loop between ML data prep , experimentation and testing all the way through to putting models into production.

Modeling 52

Modeling Experimentation Machine Learning Data-driven 52

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 124

Testing Cost-Benefit Experimentation Risk 124

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 IoT Deep Learning 279

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

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.

Risk Management 64

Risk Management Risk Modeling Enterprise 64

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 120

Data Lake IT Experimentation Data-driven 120

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 108

ROI Data-driven Enterprise Experimentation 108

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 109

Enterprise Experimentation Sales Manufacturing 109

CIO Business Intelligence

AUGUST 5, 2024

This is evident in the rigorous training required for providers, the stringent safety protocols for life sciences professionals, and the stringent data and privacy requirements for healthcare analytics software. Concerns about data security, privacy, and accuracy have been at the forefront of these discussions.

Experimentation 117

Experimentation Risk Metadata Data-driven 117

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 142

ROI Cost-Benefit Experimentation Deep Learning 142

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 156

Marketing Modeling Finance Experimentation 156

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 338

Management Machine Learning Experimentation Metrics 338

CIO Business Intelligence

OCTOBER 14, 2024

Some CIOs are reluctant to invest in emerging technologies such as AI or machine learning, viewing them as experimental rather than tools for gaining competitive advantage. They avoid investing in new technologies that could disrupt existing business models. You’re not exploiting data It’s all about the data.

Digital Transformation 130

Digital Transformation Experimentation Cost-Benefit Risk 130

CIO Business Intelligence

JULY 24, 2024

Key strategies for exploration: Experimentation: Conduct small-scale experiments. Data-driven decisions: Leverage data and analytics to assess new technologies’ potential impact and ROI. Implement agile funding models for swift resource reallocation as priorities change.

Technology 96

Technology Experimentation Cost-Benefit ROI 96

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

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

CIO Business Intelligence

FEBRUARY 16, 2024

ADP remains the 500-pound gorilla in payroll and, with its rich data, can literally tell you what’s really moving the economy,” said Pete A. ADP Data Cloud is one of the “richest datasets in the world,” and this enables the company to anonymize, customize, and monetize its data stockpile in many new ways for its client base, Nagrath claims.

Digital Transformation 115

Digital Transformation Experimentation Cost-Benefit Machine Learning 115

DataRobot Blog

NOVEMBER 15, 2022

Organizations are looking to deliver more business value from their AI investments, a hot topic at Big Data & AI World Asia. At the well-attended data science event, a DataRobot customer panel highlighted innovation with AI that challenges the status quo. Automate with Rapid Iteration to Get to Scale and Compliance.

Big Data 52

Big Data Experimentation Machine Learning Data-driven 52

Domino Data Lab

NOVEMBER 14, 2019

This Domino Data Science Field Note covers a proposed definition of interpretability and distilled overview of the PDR framework. Model interpretability continues to spark public discourse among industry. Model interpretability continues to spark public discourse among industry. Insights are drawn from Bin Yu, W. Yet, Bin Yu, W.

Modeling 71

Modeling Machine Learning Data Science Experimentation 71

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 135

Data-driven Risk Experimentation IT 135

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.

Enterprise 142

Enterprise Testing Business Objectives Experimentation 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 304

Testing Machine Learning Consulting Data Quality 304

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 Lesson 1: Don’t start from scratch to train your LLM model Massive amounts of data and computational resources are needed to train an LLM.

Enterprise 116

Enterprise Experimentation Modeling Data-driven 116

CIO Business Intelligence

MAY 14, 2024

In past years, reporting fatal drug overdoses has largely been a paper- and human-driven process in King County, which shares the information with state and federal agencies. During the second phase, NLP and ML models created and trained by the King County Department of IT extract the pertinent information from these digitized reports.

Deep Learning 89

Deep Learning Machine Learning Reporting Experimentation 89

CIO Business Intelligence

DECEMBER 19, 2023

After all, every department is pressured to drive efficiencies and is clamoring for automation, data capabilities, and improvements in employee experiences, some of which could be addressed with generative AI. As every CIO can attest, the aggregate demand for IT and data capabilities is straining their IT leadership teams.

Digital Transformation 142

Digital Transformation Unstructured Data Machine Learning Risk Management 142

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