IBM Big Data Hub

APRIL 11, 2023

Learn more about the IBM Sustainability Accelerator Sustainability as a consistent practice While setting ambitious goals is important, we emphasize goals that are transparent and authentic, with near-term targets that help support present-day execution and accountability.

Snapshot 64

Snapshot Reporting Business Objectives Software 64

IBM Big Data Hub

APRIL 18, 2024

While AGI remains theoretical, organizations can take proactive steps to prepare for its arrival by building a robust data infrastructure and fostering a collaborative environment where humans and AI work together seamlessly. How can organizations prepare for AGI? Regardless, these are examples of narrow AI.

Cost-Benefit 90

Cost-Benefit Modeling Manufacturing Interactive 90

IBM Big Data Hub

MAY 26, 2023

Cloud is transforming the way life sciences organizations are doing business. Leading life science companies are leveraging cloud for innovation around operational, revenue and business models. In 2017, 94% of hospitals used electronic clinical data from their EHR.

Consulting 80

Consulting Cost-Benefit Optimization Machine Learning 80

CIO Business Intelligence

APRIL 29, 2022

Launching a data-first transformation means more than simply putting new hardware, software, and services into operation. True transformation can emerge only when an organization learns how to optimally acquire and act on data and use that data to architect new processes. Key features of data-first leaders.

Digital Transformation 132

Digital Transformation Strategy Data-driven Data Strategy 132

Domino Data Lab

AUGUST 5, 2019

This Domino Data Science Field Note covers Chris Wiggins ‘s recent data ethics seminar at Berkeley. Data Scientists, Tradeoffs, and Data Ethics. As more companies become model-driven , data scientists are uniquely positioned to drive innovation and to help their companies remain economically strong.

Data Science 93

Data Science Data-driven Modeling Machine Learning 93

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. The complexity of models, and general limitations of expertise with data science among business leaders, creates an environment ripe for risk. Types of Model Risk.

Risk Management 64

Risk Management Risk Modeling Enterprise 64

bridgei2i

FEBRUARY 6, 2020

This push for an enterprise-wide radical change in vision, process, technology stack and most importantly culture has pushed executives to think about “Digital transformation” more seriously, not only as initiatives but as a means to drive key business outcomes such as: Contextualizing Customer Experience.

IoT 69

IoT Internet of Things Digital Transformation ROI 69

IBM Big Data Hub

JANUARY 10, 2023

Without a doubt, there is exponential growth in the access to and volume of process data we all, as individuals, have at our fingertips. Not only can data support a more compelling change management strategy, but it’s also able to identify, accelerate and embed change faster, all of which is critical in our continuously changing world.

Management 52

Management Data-driven Data mining Business Objectives 52

IBM Big Data Hub

FEBRUARY 22, 2024

A recent IBM survey found that the top barriers preventing successful AI deployment include limited AI skills and expertise, data complexity, and ethical concerns. AI tools are now utilized in national security and to help protect against data breaches and cyberattacks. These are table stakes for the DoD or any government agency.

Metadata 102

Metadata Measurement Risk Modeling 102

erwin

FEBRUARY 19, 2021

Metadata management is key to wringing all the value possible from data assets. However, most organizations don’t use all the data at their disposal to reach deeper conclusions about how to drive revenue, achieve regulatory compliance or accomplish other strategic objectives. Quite simply, metadata is data about data.

Metadata 110

Metadata Management Data Quality Cost-Benefit 110

DataRobot Blog

SEPTEMBER 13, 2022

According to IDC , 83% of CEOs want their organizations to be more data-driven. Data scientists could be your key to unlocking the potential of the Information Revolution—but what do data scientists do? What Do Data Scientists Do? Data scientists drive business outcomes. Awareness and Activation.

Forecasting 52

Forecasting Data-driven Machine Learning Optimization 52

Cloudera

SEPTEMBER 17, 2020

For enterprise organizations, managing and operationalizing increasingly complex data across the business has presented a significant challenge for staying competitive in analytic and data science driven markets. CDP data lifecycle integration and SDX security and governance.

Visualization 101

Visualization Metrics Statistics Optimization 101

Domino Data Lab

JULY 28, 2021

For companies investing in data science, the stakes have never been so high. According to a recent survey from New Vantage Partners (NVP), 62 percent of firms have invested over $50 million in big data and AI, with 17 percent investing more than $500 million. The Challenges of Scaling Data Science.

Data Science 59

Data Science Enterprise Cost-Benefit Data-driven 59

Andrew White

JANUARY 9, 2022

On Thursday January 6th I hosted Gartner’s 2022 Leadership Vision for Data and Analytics webinar. – In the webinar and Leadership Vision deck for Data and Analytics we called out AI engineering as a big trend. I would take a look at our Top Trends for Data and Analytics 2021 for additional AI, ML and related trends.

Analytics 64

Analytics Measurement Modeling Data-driven 64

Decision Management Solutions

AUGUST 13, 2020

In our experience, however, technology does not get sufficient attention on the executive agenda. Many of the projects we do these days involve helping clients operationalize machine learning (ML) or artificial intelligence (AI). Technology has a crucial role in enabling this faster and more flexible approach.

Technology 80

Technology Digital Transformation Machine Learning Modeling 80

AWS Big Data

MARCH 26, 2024

This view is used to identify patterns and trends in customer behavior, which can inform data-driven decisions to improve business outcomes. In this post, we discuss how you can use purpose-built AWS services to create an end-to-end data strategy for C360 to unify and govern customer data that address these challenges.

Data Strategy 67

Data Strategy Strategy Data Warehouse Prescriptive Analytics 67

bridgei2i

MARCH 3, 2021

Episode 4: Unlocking the Value of Enterprise AI with Data Engineering Capabilities. Unlocking the Value of Enterprise AI with Data Engineering Capabilities. They discuss how the data engineering team is instrumental in easing collaboration between analysts, data scientists and ML engineers to build enterprise AI solutions.

Enterprise 98

Enterprise Digital Transformation Data-driven Interactive 98