CIO Business Intelligence

NOVEMBER 21, 2023

Ask IT leaders about their challenges with shadow IT, and most will cite the kinds of security, operational, and integration risks that give shadow IT its bad rep. That’s not to downplay the inherent risks of shadow IT. There may be times when department-specific data needs and tools are required.

IT 137

IT Risk Cost-Benefit Risk Management 137

CIO Business Intelligence

NOVEMBER 15, 2022

Experiment with the “highly visible and highly hyped”: Gartner repeatedly pointed out that organisations that innovate during tough economic times “stay ahead of the pack”, with Mesaglio in particular calling for such experimentation to be public and visible.

Digital Transformation 143

Digital Transformation Experimentation Risk Metrics 143

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 Data-driven Machine Learning 52

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 74

Optimization Data Analytics Analytics Data-driven 74

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 154

Marketing Modeling Finance Experimentation 154

CIO Business Intelligence

JANUARY 9, 2024

Many organizations know that commercially available, “off-the-shelf” generative AI models don’t work well in enterprise settings because of significant data access and security risks. Knowing these lessons before generative AI adoption will likely save time, improve outcomes, and reduce risks and potential costs.

Enterprise 119

Enterprise Experimentation Modeling Data-driven 119

DataRobot Blog

MARCH 16, 2023

DataRobot was built by data scientists for data scientists, and for more than a decade we have been the only technology company solely-focused on AI and ML. We are offering customers rapid experimentation and value identification, with both code-first and no-code approaches. DataRobot is on a mission to change that.

Experimentation 52

Experimentation Data-driven Measurement Enterprise 52

Smart Data Collective

OCTOBER 13, 2021

AI technology moves innovation forward by boosting tinkering and experimentation, accelerating the innovation process. Take advantage of data analytics. One of the biggest reasons AI has become so valuable is that it is so tightly integrated with data analytics. Here’s how to stay competitive as technology evolves.

Technology 123

Technology Cost-Benefit Experimentation Machine Learning 123

CIO Business Intelligence

FEBRUARY 14, 2024

Fundamentals like security, cost control, identity management, container sprawl, data management, and hardware refreshes remain key strategic areas for CIOs to deal with. Data due diligence Generative AI especially has particular implications for data security, Mann says.

IT 143

IT Metadata Data-driven Management 143

CIO Business Intelligence

MAY 14, 2024

Like many public health agencies across the US, the King County Medical Examiner’s Office tracks drug overdose deaths to target interventions for populations at risk and save lives. Azure Databricks is also employed for data analytics as part of the solution.

Deep Learning 52

Deep Learning Machine Learning Reporting Experimentation 52

CIO Business Intelligence

FEBRUARY 21, 2024

One is knowledge of the emerging mega trends in technology — data, AI, and machine learning — and the other is understanding organizational culture needed to advance the technology goals and to inspire contributors,” he says. We now use AI to help faculty understand some of those risk factors,” says Fozard.

Recreation/Entertainment 135

Recreation/Entertainment Experimentation Modeling Data-driven 135

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 332

Management Machine Learning Experimentation Metrics 332

Cloudera

OCTOBER 18, 2023

In the ever-evolving landscape of the financial services Industry, change is a constant and transformation is a requirement — to stay at pace with new regulations, risk mitigation, and the technological developments that support transformation. Quick wins!

Cost-Benefit 79

Cost-Benefit Testing Machine Learning Optimization 79

Ontotext

JULY 6, 2023

In today’s fast changing environment, enterprises that have transitioned from being focused on applications to becoming data-driven gain a significant competitive edge. There are four groups of data that are naturally siloed: Structured data (e.g., Transaction and pricing data (e.g.,

Cost-Benefit 52

Cost-Benefit Metadata Experimentation Risk 52

CIO Business Intelligence

DECEMBER 29, 2023

The most pressing responsibilities for CIOs in 2024 will include security, cost containment, and cultivating a data-first mindset.” Adaptability and useability of AI tools For CIOs, 2023 was the year of cautious experimentation for AI tools. Here, we detail those and others that comprise eight of the top priorities for CIOs in 2024.

Cost-Benefit 139

Cost-Benefit Digital Transformation Consulting Strategy 139

IBM Big Data Hub

DECEMBER 5, 2023

Generative AI excels at handling diverse data sources such as emails, images, videos, audio files and social media content. This unstructured data forms the backbone for creating models and the ongoing training of generative AI, so it can stay effective over time. The impact of these investments will become evident in the coming years.

Unstructured Data 95

Unstructured Data Cost-Benefit Experimentation Machine Learning 95

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 356

Enterprise Modeling Risk Manufacturing 356

DataRobot Blog

JANUARY 17, 2023

As a data scientist, one of the best things about working with DataRobot customers is the sheer variety of highly interesting questions that come up. For counterparty behavior prediction: some form of structured data which contains not only won trades but also unsuccessful requests/responses. For price discovery (e.g.,

Machine Learning 87

Machine Learning Marketing Experimentation Modeling 87

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. Regulations and compliance requirements, especially around pricing, risk selection, etc.,

Insurance 250

Insurance Analytics Forecasting Deep Learning 250

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

CIO Business Intelligence

JUNE 28, 2023

These circumstances have induced uncertainty across our entire business value chain,” says Venkat Gopalan, chief digital, data and technology officer, Belcorp. “As The R&D laboratories produced large volumes of unstructured data, which were stored in various formats, making it difficult to access and trace.

Digital Transformation 104

Digital Transformation Cost-Benefit Informatics Data mining 104

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

CIO Business Intelligence

MARCH 7, 2023

Ready for the right applications Generative AI is ready for use in coding, administrative workflows, data refinement, and simple use cases such as pre-filling forms, says Oliver Wittmaier, CIO and product owner at DB SYSTEL GmbH, the wholly owned subsidiary of DB AG and digital partner for all group companies. Mitre Corp.

Enterprise 116

Enterprise IT Experimentation Unstructured Data 116

CIO Business Intelligence

MAY 16, 2023

It surpasses blockchain and metaverse projects, which are viewed as experimental or in the pilot stage, especially by established enterprises. The inherent capabilities of AI–to process vast amounts of data and use learned intelligence to make decisions with extraordinary speed–enable opportunities uncovered through digital listening.

Advertising 104

Advertising Recreation/Entertainment Experimentation Enterprise 104

CIO Business Intelligence

OCTOBER 1, 2022

The partners say they will create the future of digital manufacturing by leveraging the industrial internet of things (IIoT), digital twin , data, and AI to bring products to consumers faster and increase customer satisfaction, all while improving productivity and reducing costs. Data and AI as digital fundamentals.

Manufacturing 145

Manufacturing Digital Transformation IoT Internet of Things 145

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. Caution is king. Looking forward.

Enterprise 52

Enterprise Experimentation Risk Data-driven 52

DataRobot Blog

OCTOBER 18, 2022

Organizations are looking for AI platforms that drive efficiency, scalability, and best practices, trends that were very clear at Big Data & AI Toronto. DataRobot Booth at Big Data & AI Toronto 2022. Monitoring and Managing AI Projects with Model Observability. Accelerating Value-Realization with Industry Specific Use Cases.

Big Data 96

Big Data Forecasting Experimentation Metrics 96

DataRobot Blog

AUGUST 10, 2022

Change is happening fast across the NHS with the focus squarely on harnessing the huge amount of data the NHS generates — to drive forward the transformation programmes needed to address the backlog for elective care and growing demands for services. Resetting urgent care performance and delivery.

Forecasting 52

Forecasting Experimentation Data-driven Risk 52

CIO Business Intelligence

APRIL 6, 2022

Our world today is experiencing an extremely social, connected, competitive and technology-driven business environment. Infosys Living labs is a set of well-orchestrated innovation services for future-proofing customer businesses and de-risking their emerging technology transformations.

Experimentation 101

Experimentation Data Lake Uncertainty Enterprise 101

Sisense

JANUARY 21, 2020

Everyone wants to get more out of their data, but how exactly to do that can leave you scratching your head. One of the simplest ways to start exploring your data is to aggregate the metrics you are interested in by their relevant dimensions. How can good data lead to faulty conclusions? How does this happen? 9/10 = 90%.

Testing 104

Testing Risk Data-driven Statistics 104

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

Ontotext

APRIL 3, 2024

Joseph Hilger : People are starting to understand that knowledge graphs are not just a tool for storing data and information. I need something that defines what those entities are and can align them with the data.” The other use case where graphs are exploding is what Gartner calls a data fabric. What are your thoughts about it?

Technology 59

Technology Risk Digital Transformation Measurement 59

CIO Business Intelligence

MAY 10, 2023

Sundararajan has redefined the company’s purpose of reimagining global agriculture and food systems, and this is buoyed by his beliefs in good leadership: the ability to manage ambiguity and look at things through an experimental framework, which can open doors to more possibilities for the business.

Enterprise 52

Enterprise Digital Transformation Internet of Things B2B 52

Jet Global

DECEMBER 31, 2019

You help companies adapt to a changing, tech-driven economy. If there is no advantage to taking a risk—knowing that failure is a possibility—an individual will assume business as normal. How quickly do companies need to become “data-driven”? If a data strategy is not being executed today, you’re already late.

Digital Transformation 59

Digital Transformation Finance Experimentation Data-driven 59

Domino Data Lab

JANUARY 24, 2019

In 2018 we saw the “data science platform” market rapidly crystallize into three distinct product segments. Over the last couple years, it would be hard to blame anyone for being overwhelmed looking at the data science platform market landscape. Proprietary (often GUI-driven) data science platforms. Automation Tools.

Data Science 65

Data Science Marketing Data-driven Statistics 65

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 57

Data-driven Enterprise Data Governance Prescriptive Analytics 57

O'Reilly on Data

MAY 14, 2020

AI PMs should enter feature development and experimentation phases only after deciding what problem they want to solve as precisely as possible, and placing the problem into one of these categories. Experimentation: It’s just not possible to create a product by building, evaluating, and deploying a single model.

Management 363

Management Experimentation B2B Machine Learning 363