Cloudera

JUNE 6, 2024

With Cloudera, OCBC’s Next Best Conversation platform was able to analyze real-time contextual data from customer conversations, resulting in a revenue increase. While these are great proof points to demonstrate how business value can be driven by AI/ML, this was only made possible with trusted data.

Contextual Data 83

Contextual Data Data Lake Data-driven Risk 83

Cloudera

JUNE 13, 2024

Cloudera’s true hybrid approach ensures you can leverage any deployment, from virtual private cloud to on-premises data centers, to maximize the use of AI. Reliability – Can you trust that your data quality will yield useful AI results? Responsibility – Can you trust your AI models will give meaningful insight?

Big Data 103

Big Data Machine Learning Contextual Data Data Lake 103

Cloudera

JANUARY 30, 2024

Here are some of the key use cases: Predictive maintenance: With time series data (sensor data) coming from the equipment, historical maintenance logs, and other contextual data, you can predict how the equipment will behave and when the equipment or a component will fail. Eliminate data silos.

Manufacturing 81

Manufacturing Contextual Data IoT Internet of Things 81

IBM Big Data Hub

SEPTEMBER 19, 2023

How effectively and efficiently an organization can conduct data analytics is determined by its data strategy and data architecture , which allows an organization, its users and its applications to access different types of data regardless of where that data resides.

Data Science 76

Data Science Data Analytics Prescriptive Analytics Analytics 76

Ontotext

JANUARY 11, 2023

The implications of consumer behavior for retailers range from the need to ensure relevant customer service and quick delivery to serving personalized content and managing data from disparate systems. Of course, there are various platforms and data architectures for managing customer and product data.

Contextual Data 52

Contextual Data Interactive Data-driven Data Integration 52

Cloudera

JULY 29, 2024

Democratized stream processing is the ability of non-coder domain experts to apply transformations, rules, or business logic to streaming data to identify complex events in real time and trigger automated workflows and/or deliver decision-ready data to users.

Enterprise 69

Enterprise Data Architecture Manufacturing Key Performance Indicator 69