Smart Data Collective

JUNE 19, 2019

As such, you should concentrate your efforts in positioning your organization to mine the data and use it for predictive analytics and proper planning. The Relationship between Big Data and Risk Management. Tips for Improving Risk Management When Handling Big Data. Vendor Risk Management (VRM).

Risk Management 92

Risk Management Risk Management Big Data 92

IBM Big Data Hub

FEBRUARY 19, 2024

Big data and predictive analytics are increasingly being used to improve forecasting accuracy, allowing businesses to respond more effectively to changes in customer needs. Real-time tracking systems, often enabled by Internet of Things (IoT) devices, help companies monitor their supply chain accurately and immediately.

Strategy 81

Strategy Management Forecasting Internet of Things 81

IBM Big Data Hub

JULY 27, 2023

EAM systems can include functions like maintenance management, asset lifecycle management , inventory management and work order management, among others. Access to asset/system simulations can enable more proactive maintenance planning, improved decision-making and better risk management.

Cost-Benefit 55

Cost-Benefit IoT Internet of Things Enterprise 55

Cloudera

JANUARY 22, 2019

It enables orchestration of data flow and curation of data across various big data platforms (such as data lakes, Hadoop, and NoSQL) to support a single version of the truth, customer personalization, and advanced big data analytics. Cloudera Enterprise Platform as Big Data Fabric. Flexible/Location-agnostic Infrastructure.

Big Data 44

Big Data Data Lake Internet of Things Enterprise 44

Corinium

APRIL 25, 2019

And more recently, we have also seen innovation with IOT (Internet Of Things). Machine learning can keep up, by continually looking for trends and anomalies, or predictive analytics, that are interesting for the given use case. You can protect individual fields, or even subsets of fields (e.g.

Insurance 150

Insurance Risk IoT Data-driven 150

datapine

AUGUST 29, 2022

7) Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die by Eric Siegel. Best for: someone who has heard a lot of buzz about predictive analytics, but doesn’t have a firm grasp on the subject. – Eric Siegel, author, and founder of Predictive Analytics World.

Big Data 263

Big Data Data Analytics Analytics Data mining 263