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

O'Reilly on Data

OCTOBER 13, 2020

From a technical perspective, it is entirely possible for ML systems to function on wildly different data. For example, you can ask an ML model to make an inference on data taken from a distribution very different from what it was trained on—but that, of course, results in unpredictable and often undesired performance. I/O validation.

Management 314

Management Machine Learning Metrics Modeling 314

CIO Business Intelligence

AUGUST 20, 2024

Pre-pandemic, high-performance teams were co-located, multidisciplinary, self-organizing, agile, and data-driven. These teams focused on delivering reliable technology capabilities, improving end-user experiences, and establishing data and analytics capabilities.

IT 141

IT Digital Transformation Experimentation Risk 141

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

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 143

Digital Transformation Unstructured Data Machine Learning Risk Management 143

DataRobot Blog

MARCH 7, 2023

DataRobot on Azure accelerates the machine learning lifecycle with advanced capabilities for rapid experimentation across new data sources and multiple problem types. This generates reliable business insights and sustains AI-driven value across the enterprise.

Data-driven 59

Data-driven Machine Learning Experimentation Data Lake 59

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

CIO Business Intelligence

NOVEMBER 21, 2023

After all, 41% of employees acquire, modify, or create technology outside of IT’s visibility , and 52% of respondents to EY’s Global Third-Party Risk Management Survey had an outage — and 38% reported a data breach — caused by third parties over the past two years. There may be times when department-specific data needs and tools are required.

IT 137

IT Risk Cost-Benefit Data Science 137

CIO Business Intelligence

FEBRUARY 7, 2024

Franchetti acknowledges that a KPI- and outcome-driven method is still appropriate for many technology rollouts, but “the organic approach is better for AI, so our deep software development subject matter experts can innovate without a targeted business outcome,” he says. “Of

KPI 105

KPI Measurement Experimentation Finance 105

O'Reilly on Data

MARCH 23, 2023

But Transformers have some other important advantages: Transformers don’t require training data to be labeled; that is, you don’t need metadata that specifies what each sentence in the training data means. Unlike labels, embeddings are learned from the training data, not produced by humans.

IT 348

IT Modeling Testing Risk 348

CIO Business Intelligence

MARCH 7, 2023

Vince Kellen understands the well-documented limitations of ChatGPT, DALL-E and other generative AI technologies — that answers may not be truthful, generated images may lack compositional integrity, and outputs may be biased — but he’s moving ahead anyway.

Enterprise 116

Enterprise IT Unstructured Data Experimentation 116

CIO Business Intelligence

DECEMBER 10, 2024

As a data-driven company, InnoGames GmbH has been exploring the opportunities (but also the legal and ethical issues) that the technology brings with it for some time. Both were created to address a fundamental problem in two respects: Data that remains unused: InnoGames collects more than 1.7 The games industry is no exception.

Data-driven 98

Data-driven Metadata Interactive KPI 98

Domino Data Lab

FEBRUARY 12, 2020

This post is for people making technology decisions, by which I mean data science team leads, architects, dev team leads, even managers who are involved in strategic decisions about the technology used in their organizations. Suppose you have an “expensive” function to run repeatedly over data records. Introduction. by adding the ?@ray.remote?

Experimentation 137

Experimentation Modeling Data Science Machine Learning 137

CIO Business Intelligence

APRIL 24, 2024

Sales and marketing departments have long been at the forefront of embracing new technologies, and according to data provided by the Alexander Group, a revenue consultancy, 80% of hundreds of survey responses detailed that CROs have formally invested in AI for their marketing teams.

Sales 128

Sales Finance Experimentation Cost-Benefit 128

CIO Business Intelligence

SEPTEMBER 27, 2023

The decision to launch this pilot phase was driven by a desire to stay ahead in the field, assess the potential applications of gen AI, and subsequently transition into targeted proof-of-concept projects,” says Vlad-George Iacob, vice president of engineering at Hackajob.

Strategy 126

Strategy Data-driven Risk Technology 126

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. It helps you to amplify what’s proven to work, throw away what isn’t, and tweak the goal-posts when data indicates that they may be in the wrong place.

Metrics 157

Metrics KPI Analytics Key Performance Indicator 157

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. Detect patterns and indicators of potential fraudulent activities using transaction data, customer profiles, and other relevant information.

Cost-Benefit 79

Cost-Benefit Testing Machine Learning Optimization 79

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

CIO Business Intelligence

MAY 30, 2024

Case in point is its new conversational assistant copilot, AlpiGPT an internal search engine of corporate data that can personalize travel packages and quickly answer questions, says company CIO, Francesco Ciuccarelli. After this project, we’ll constantly introduce AI on other sectors and services like control of travel documentation.”

Cost-Benefit 119

Cost-Benefit Sales Modeling Experimentation 119

CIO Business Intelligence

AUGUST 1, 2023

But with all the excitement and hype, it’s easy for employees to invest time in AI tools that compromise confidential data or for managers to select shadow AI tools that haven’t been through security, data governance, and other vendor compliance reviews.

Digital Transformation 98

Digital Transformation Unstructured Data Strategy Data Science 98

Domino Data Lab

AUGUST 6, 2021

An enterprise starts by using a framework to formalize its processes and procedures, which gets increasingly difficult as data science programs grow. With a framework and Enterprise MLOps, organizations can manage data science at scale and realize the benefits of Model Risk Management that are received by a wide range of industry verticals.

Risk Management 64

Risk Management Risk Modeling Enterprise 64

DataRobot

SEPTEMBER 14, 2021

Becoming AI-driven is no longer really optional. And for those that do make it past the experimental stage, it typically takes over 18 months for the value to be realized. At the same time, business and data analysts want to access intuitive, point-and-click tools that use automated best practices.

Machine Learning 94

Machine Learning Experimentation Modeling Visualization 94

AWS Big Data

SEPTEMBER 13, 2024

In recent years, driven by the commoditization of data storage and processing solutions, the industry has seen a growing number of systematic investment management firms switch to alternative data sources to drive their investment decisions. Each team is the sole owner of its AWS account.

Interactive 87

Interactive Strategy Cost-Benefit Data Governance 87

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

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 Data Science Machine Learning Data-driven 105

DataRobot Blog

JANUARY 12, 2023

By outsourcing the day-to-day management of the data science platform to the team who created the product, AI builders can see results quicker and meet market demands faster, and IT leaders can maintain rigorous security and data isolation requirements. Delivering more than 1.4 Sudhir Hasbe.

Management 59

Management Data-driven ROI Data Science 59

IBM Big Data Hub

OCTOBER 20, 2023

AI platform tools enable knowledge workers to analyze data, formulate predictions and execute tasks with greater speed and precision than they can manually. AI platforms assist with a multitude of tasks ranging from enforcing data governance to better workload distribution to the accelerated construction of machine learning models.

Machine Learning 71

Machine Learning Manufacturing Deep Learning Cost-Benefit 71

IBM Big Data Hub

MARCH 27, 2024

This article explores an innovative way to streamline the estimation of Scope 3 GHG emissions leveraging AI and Large Language Models (LLMs) to help categorize financial transaction data to align with spend-based emissions factors. Why are Scope 3 emissions difficult to calculate?

Experimentation 73

Experimentation Deep Learning Modeling Data-driven 73

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

Sisense

JULY 15, 2020

Healthy Data is your window into how data can help organizations address this crisis. COVID-19 required a worldwide coordinated response of medical professionals, data teams, logistics organizations, and a whole host of other experts to try to flatten the curve, improve treatments, and ultimately develop lasting remedies.

Analytics 90

Analytics Modeling Visualization Dashboards 90

CIO Business Intelligence

JULY 31, 2023

To allow or not According to various news reports, some big-name companies initially blocked generative AI tools such as ChatGPT for various reasons, including concerns about protecting proprietary data. 1 question now is to allow or not allow,” says Mir Kashifuddin, data risk and privacy leader with the professional services firm PwC US.

Strategy 98

Strategy Risk Enterprise Risk Management 98

DataRobot Blog

OCTOBER 4, 2022

The shift in consumer habits and geopolitical crises have rendered data patterns collected pre-COVID obsolete. This has prompted AI/ML model owners to retrain their legacy models using data from the post-COVID era, while adapting to continually fluctuating market trends and thinking creatively about forecasting.

Forecasting 59

Forecasting Sales Data-driven Modeling 59

Cloudera

NOVEMBER 25, 2020

The challenges Matthew and his team are facing are mainly about access to a multitude of data sets, of various types and sources, with ease and ad-hoc, and their ability to deliver data-driven and confident outcomes. . Most of their research data is unstructured and has a lot of variety. Challenges Ahead.

Data Warehouse 59

Data Warehouse Unstructured Data Analytics Visualization 59

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

Occam's Razor

JUNE 6, 2007

Bonus: Interactive CD: Contains six podcasts, one video, two web analytics metrics definitions documents and five insightful powerpoint presentations. Experimentation & Testing (A/B, Multivariate, you name it). In 480 pages the book goes from from beginner's basics to a advanced analytics concepts. Clicks and outcomes.

Analytics 60

Analytics Metrics Marketing Dashboards 60

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 364

Marketing Experimentation Metrics Testing 364

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 45

Statistics Optimization Modeling Experimentation 45