erwin

JUNE 11, 2020

Transforming Industries with Data Intelligence. Data intelligence has provided useful and insightful information to numerous markets and industries. With tools such as Artificial Intelligence, Machine Learning, and Data Mining, businesses and organizations can collate and analyze large amounts of data reliably and more efficiently.

Analytics 103

Analytics Blockchain Artificial Intelligence Big data 103

IBM Big Data Hub

NOVEMBER 30, 2022

So, it’s crucial for companies that want to add specific AI capabilities to their applications or workflows to do so without expanding their technology stack, hiring more data science talent, or investing in expensive supercomputing resources. Users can then mine the data using simple keyword searches to find the information they need.

Libraries 90

Libraries Data science Cloud Mining 90

Bill Schmarzo - Dell EMC

FEBRUARY 14, 2018

Organizations use accounting, auditing, investigative, data and analytic skills to “follow the money” and determine their financial value. Figure 3: Customer Analytic Profile. See “ Analytic Profiles: Key to Data Monetization ” for more details on Analytic Profiles. Follow the Customer Summary.

Artificial Intelligence 102

Artificial Intelligence Analytics Customer Experience Big data 102

Information is Currency

FEBRUARY 17, 2017

Risk of personal data loss. The Conflict between Data Science and Cybersecurity. Cybersecurity is in direct conflict with the basis tenants of data analysis, especially big data analysis, predictive analytics and data mining. Poor User Experience. Restrict core device functionality.

MDM 40

MDM Big data Information governance Analytics 40

Information Management Resources

FEBRUARY 28, 2018

Several top colleges and universities are offering courses and concentrations in applying data to the sector.

Analytics 29

Analytics Insurance Unstructured data Data science 29

Bill Schmarzo - Dell EMC

FEBRUARY 14, 2018

Organizations use accounting, auditing, investigative, data and analytic skills to “follow the money” and determine their financial value. Figure 3: Customer Analytic Profile. See “ Analytic Profiles: Key to Data Monetization ” for more details on Analytic Profiles. Follow the Customer Summary.

Analytics 40

Analytics Artificial Intelligence Customer Experience Big data 40

Information Management Resources

APRIL 6, 2018

Analytics skills are in short supply, but demands for data-driven results are not. Here are Forrester’s top tips on how chief data officers can drive business strategy.

Analytics 49

Analytics Data science Mining 49

ARMA International

SEPTEMBER 13, 2021

Some technology trends such as real-time data analytics are on-going, while others are more recent, such as blockchain. AI using machine learning (ML) involves processing samples of data to learn. Then using what was learnt learning to run data analytics on vast amounts of content from many sources. Data Analytics.

Digital transformation 59

Digital transformation Blockchain IT Computer and Electronics 59

Bill Schmarzo - Dell EMC

MARCH 5, 2018

The conversation is simple because the objective is simple: How do I become more effective at leveraging (big) data and analytics (artificial intelligence) to power my business? If success is simply adopting and deploying advanced analytics technologies, then you don’t need strategic guidance to chart that journey. It’s simple.

Artificial Intelligence 111

Artificial Intelligence Analytics Big data Mining 111

IBM Big Data Hub

JULY 17, 2023

By supporting open-source frameworks and tools for code-based, automated and visual data science capabilities — all in a secure, trusted studio environment — we’re already seeing excitement from companies ready to use both foundation models and machine learning to accomplish key tasks.

Analytics 66

Analytics Data science Cloud Metadata 66

Bill Schmarzo - Dell EMC

MARCH 5, 2018

The conversation is simple because the objective is simple: How do I become more effective at leveraging (big) data and analytics (artificial intelligence) to power my business? If success is simply adopting and deploying advanced analytics technologies, then you don’t need strategic guidance to chart that journey. It’s simple.

Artificial Intelligence 40

Artificial Intelligence Analytics Mining Big data 40

IBM Big Data Hub

SEPTEMBER 11, 2023

Built on decades of innovation in data security, scalability and availability, IBM Db2 keeps business applications and analytics protected, highly performant, and resilient, anywhere. enhances data management through automated insights generation, self-tuning performance optimization and predictive analytics.

Analytics 90

Analytics Cloud IoT Paper 90

Collibra

NOVEMBER 18, 2021

Data collection is what we do. Today, we think of Big Data as a modern concept. Cloud storage, text mining and social network analytics are vital 21 st century tools. That invention turned languishing data into useful data. The dilemma of how to best store and analyze data, however, continued. .

IT 52

IT Data collection Analytics Military 52

Information Management Resources

JANUARY 26, 2018

When it comes to digital transformation, many organizations either don’t know where to start or they’re jumping off the wrong diving board.

Digital transformation 39

Digital transformation IT Data science Mining 39

Information Management Resources

NOVEMBER 30, 2017

The insurer partners with California-based insurtech Carpe Data to further investigate incoming claims.

Insurance 29

Insurance Data science Mining Analytics 29

Bill Schmarzo - Dell EMC

JANUARY 29, 2018

As a standard operating practice, football front offices should apply Machine Learning to mine the large body of football game data to identify those “known unknowns” and “unknown unknowns” relationships buried in the data. Basing analytics models on flawed variables can lead to sub-optimal and even wrong decisions.

Analytics 40

Analytics Risk Data science Big data 40

Bill Schmarzo - Dell EMC

JANUARY 29, 2018

As a standard operating practice, football front offices should apply Machine Learning to mine the large body of football game data to identify those “known unknowns” and “unknown unknowns” relationships buried in the data. Basing analytics models on flawed variables can lead to sub-optimal and even wrong decisions.

Analytics 40

Analytics Risk Data science Big data 40