CIO Business Intelligence

DECEMBER 11, 2024

If 2023 was the year of AI discovery and 2024 was that of AI experimentation, then 2025 will be the year that organisations seek to maximise AI-driven efficiencies and leverage AI for competitive advantage. Primary among these is the need to ensure the data that will power their AI strategies is fit for purpose.

Risk 111

Risk Data Strategy Strategy Data Governance 111

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

Rocket-Powered Data Science

FEBRUARY 15, 2023

Third, any commitment to a disruptive technology (including data-intensive and AI implementations) must start with a business strategy. These changes may include requirements drift, data drift, model drift, or concept drift. encouraging and rewarding) a culture of experimentation across the organization.

Strategy 290

Strategy Experimentation Uncertainty Machine Learning 290

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

Smart Data Collective

JUNE 29, 2022

Big data technology is leading to a lot of changes in the field of marketing. A growing number of marketers are exploring the benefits of big data as they strive to improve their branding and outreach strategies. Email marketing is one of the disciplines that has been heavily touched by big data. Always Provide Value.

B2B 124

B2B Data-driven Marketing Strategy 124

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 364

IT Testing Experimentation Software 364

Occam's Razor

OCTOBER 23, 2006

The title of my presentation at the Washington DC Emetrics summit was: Creating a Data Driven Web Decision Making Culture – Lessons, Tips, Insights from a Practitioner. Seven Steps to Creating a Data Driven Decision Making Culture…… Slide 1: Decision Making Landscape. 2 Solve for the Trinity. #

Data-driven 118

Data-driven Metrics KPI Reporting 118

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

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. Unlike many AI-driven products, Answers will tell you when it genuinely doesn’t have an answer. This data goes to our compensation model, which is designed to be revenue-neutral.

Modeling 337

Modeling Experimentation Interactive Data-driven 337

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: Reporting Squirrels spend 75% or more of their time in data production activities.

Data-driven 142

Data-driven Consulting Reporting 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 110

IoT Machine Learning Metadata Data-driven 110

Smart Data Collective

DECEMBER 30, 2020

Big data is playing an important role in many facets of modern business. One of the most important applications of big data technology lies with inventory management and optimization. Understanding the Best Data-Driven Inventory Optimization Applications for the Coming Year. Core $59, Pro $199, and Pro-Plus $359.

Data-driven 99

Data-driven Software Optimization Big Data 99

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

datapine

MAY 20, 2020

A CRM dashboard is a centralized hub of information that presents customer relationship management data in a way that is dynamic, interactive, and offers access to a wealth of insights that can improve your consumer-facing strategies and communications. Let’s look at this in more detail. What Is A CRM Report? Follow-Up Contact Rate.

Dashboards 265

Dashboards Reporting KPI Visualization 265

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

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’ . DataOps Technical Services. Agile ticketing/Kanban tools. Deploy to production. Product monitoring.

Metrics 243

Metrics Experimentation Measurement Testing 243

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 356

Deep Learning Machine Learning Data-driven Modeling 356

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

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

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

MARCH 4, 2025

The Block ecosystem of brands including Square, Cash App, Spiral and TIDAL is driven by more than 4,000 engineers and thousands of interconnected software systems. Setting the roadmap Blocks developer experience team determines its roadmap using quantitative and qualitative data to identify opportunities and measure impact.

Experimentation 69

Experimentation Metrics Data-driven Measurement 69

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

CIO Business Intelligence

JANUARY 10, 2025

The report underscores a growing commitment to AI-driven innovation, with 67% of business leaders predicting that gen AI will transform their organizations by 2025. The data also shows growing momentum around AI agents, with over half of organizations exploring their use. However, only 12% have deployed such tools to date.

ROI 81

ROI Enterprise Broadcasting Metrics 81

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

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 IT 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

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. This has led to lawsuits and settlements.

Marketing 232

Marketing Finance Modeling Experimentation 232

CIO Business Intelligence

SEPTEMBER 23, 2024

In fact, a new report from Forrester Research found that most healthcare organizations are focused more on short-term experimentation than implementing a broader strategic vision for GenAI. It is still the data. That’s what it’s like to find a GenAI strategy on top of a poor data infrastructure.

Management 115

Management Experimentation Data-driven Strategy 115

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

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. To find optimal values of two parameters experimentally, the obvious strategy would be to experiment with and update them in separate, sequential stages.

Experimentation 52

Experimentation Optimization Uncertainty Metrics 52

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

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

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

CIO Business Intelligence

SEPTEMBER 18, 2024

Einstein for Service — Autodesk’s first use of Salesforce’s gen AI platform — has driven sizable efficiencies for Autodesk customer agents, says Kota, singling out AI-generated summaries of case issues and resolutions as a key productivity gain.

Digital Transformation 119

Digital Transformation Experimentation Sales Software 119

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

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 Data Science 56

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 308

Management Machine Learning Metrics Modeling 308