O'Reilly on Data

OCTOBER 19, 2021

Similarly, it would be pointless to pretend that a data-intensive application resembles a run-off-the-mill microservice which can be built with the usual software toolchain consisting of, say, GitHub, Docker, and Kubernetes. Adapted from the book Effective Data Science Infrastructure. Data Science Layers.

IT 364

IT Testing Experimentation Software 364

IBM Big Data Hub

SEPTEMBER 19, 2023

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.

Data Science 76

Data Science Data Analytics Prescriptive Analytics Analytics 76

Cloudera

JUNE 6, 2024

To keep pace as banking becomes increasingly digitized in Southeast Asia, OCBC was looking to utilize AI/ML to make more data-driven decisions to improve customer experience and mitigate risks. 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

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

Cloudera

DECEMBER 14, 2022

OCBC identified the need to upgrade its data lake technology as part of an enterprise data science initiative to introduce a more resilient infrastructure and platform capable of managing projects with increasing volume, variety and velocity of data, while also enabling real-time analytics. .

Data Strategy 81

Data Strategy Strategy IT Contextual Data 81