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. Their top predictions include: Most enterprises fixated on AI ROI will scale back their efforts prematurely.

ROI 127

ROI Data-driven Enterprise Experimentation 127

CIO Business Intelligence

JANUARY 10, 2025

A sharp rise in enterprise investments in generative AI is poised to reshape business operations, with 68% of companies planning to invest between $50 million and $250 million over the next year, according to KPMGs latest AI Quarterly Pulse Survey. However, only 12% have deployed such tools to date.

ROI 81

ROI Enterprise Broadcasting Metrics 81

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

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

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

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. We’ll also discuss building DataOps expertise around the data organization, in a decentralized fashion, using DataOps centers of excellence (COE) or DataOps Dojos. Deploy to production.

Metrics 243

Metrics Experimentation Measurement Testing 243

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

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.

Enterprise 143

Enterprise Testing Business Objectives Experimentation 143

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 363

IT Testing Experimentation Software 363

DataKitchen

APRIL 13, 2021

This is not surprising given that DataOps enables enterprise data teams to generate significant business value from their data. Testing and Data Observability. It orchestrates complex pipelines, toolchains, and tests across teams, locations, and data centers. DataOps is a hot topic in 2021. Meta-Orchestration.

Testing 300

Testing Machine Learning Consulting Data Science 300

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

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

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

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.

Insurance 250

Insurance Analytics Forecasting Deep Learning 250

Cloudera

AUGUST 20, 2020

Businesses had to literally switch operations, and enable better collaboration and access to data in an instant — while streamlining processes to accommodate a whole new way of doing things. But out of disruption, we’ve seen incredible innovation born into the enterprise. The organisation also wanted to ensure better customer s ervice.

Enterprise 121

Enterprise Experimentation Uncertainty Deep Learning 121

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

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.

Enterprise 119

Enterprise Experimentation Modeling Data-driven 119

CIO Business Intelligence

MARCH 7, 2023

While the technology is still in its early stages, for some enterprise applications, such as those that are content and workflow-intensive, its undeniable influence is here now — but proceed with caution. Some people are even using these large language models as a way to clean unstructured data,” he says. Mitre Corp.

Enterprise 116

Enterprise IT Unstructured Data Experimentation 116

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

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. It is also exploring SaaS offerings to further modernize its infrastructure. “We

Digital Transformation 119

Digital Transformation Experimentation Sales Software 119

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

datapine

JANUARY 31, 2022

Because things are changing and becoming more competitive in every sector of business, the benefits of business intelligence and proper use of data analytics are key to outperforming the competition. BI software uses algorithms to extract actionable insights from a company’s data and guide its strategic decisions.

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

CIO Business Intelligence

MAY 12, 2022

But sometimes can often be more than enough if the prediction can help your enterprise plan better, spend more wisely, and deliver more prescient service for your customers. Most tools offer visual programming interfaces that enable users to drag and drop various icons optimized for data analysis. For enterprise support, cloud options.

Predictive Analytics 137

Predictive Analytics Analytics Statistics Machine Learning 137

CIO Business Intelligence

DECEMBER 23, 2024

A new survey of SAP customer organizations shows that, despite AI experimentation, few have implemented AI and generative AI technologies across their enterprises. When it comes to data analyses, AI can help support data-driven decision making.

Experimentation 59

Experimentation Optimization Digital Transformation Manufacturing 59

Domino Data Lab

JUNE 10, 2020

Today, we announced the latest release of Domino’s data science platform which represents a big step forward for enterprise data science teams. You can identify data drift, missing information, and other issues, and take corrective action before bigger problems occur.

Data Science 82

Data Science Enterprise Experimentation Modeling 82

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

JANUARY 20, 2022

The following is a summary list of the key data-related priorities facing ICSs during 2022 and how we believe the combined Snowflake & DataRobot AI Cloud Platform stack can empower the ICS teams to deliver on these priorities. Key Data Challenges for Integrated Care Systems in 2022. Building data communities.

Data-driven 145

Data-driven Experimentation Predictive Modeling Data Warehouse 145

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. The accolades are short-lived.

Experimentation 111

Experimentation Risk Cost-Benefit Strategy 111

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

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

CIO Business Intelligence

OCTOBER 8, 2024

An IBM report based on the survey, “6 blind spots tech leaders must reveal,” describes the huge expectations that modern IT leaders face: “For technology to deliver enterprise-wide business outcomes, tech leaders must be part mastermind, part maestro,” the report says. The value is not seen in keeping the wheels on the bus,” he says.

IT 140

IT Strategy Experimentation Technology 140

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

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

An enterprise starts by using a framework to formalize its processes and procedures, which gets increasingly difficult as data science programs grow. As a business becomes model driven, Model Risk Management can help limit risks for sustainable growth in almost any industry vertical. What Is Model Risk? Types of Model Risk.

Risk Management 64

Risk Management Risk Modeling Enterprise 64

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. There are similar concerns for CIOs looking to build data and analytics capabilities. Release an updated data viz, then automate a regression test.

Digital Transformation 145

Digital Transformation Data Governance Machine Learning Experimentation 145

Smart Data Collective

JULY 9, 2023

E-commerce businesses around the world are focusing more heavily on data analytics. There are many ways that data analytics can help e-commerce companies succeed. Understanding E-commerce Conversion Rates There are a number of metrics that data-driven e-commerce companies need to focus on. billion on analytics last year.

Optimization 97

Optimization Data Analytics Analytics Data-driven 97

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