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 77

Data Science Data Analytics Prescriptive Analytics Analytics 77

CIO Business Intelligence

OCTOBER 13, 2023

Solutions data architect: These individuals design and implement data solutions for specific business needs, including data warehouses, data marts, and data lakes. Application data architect: The application data architect designs and implements data models for specific software applications.

Data Architecture 131

Data Architecture Data Warehouse Statistics Visualization 131

CIO Business Intelligence

JULY 26, 2023

The only thing we have on premise, I believe, is a data server with a bunch of unstructured data on it for our legal team,” says Grady Ligon, who was named Re/Max’s first CIO in October 2022.

Data Lake 98

Data Lake Digital Transformation Machine Learning Data Architecture 98

Cloudera

JUNE 25, 2021

Many Cloudera customers are making the transition from being completely on-prem to cloud by either backing up their data in the cloud, or running multi-functional analytics on CDP Public cloud in AWS or Azure. The Replication Manager service facilitates both disaster recovery and data migration across different environments.

Data Lake 73

Data Lake Metadata Unstructured Data Management 73

Sisense

OCTOBER 6, 2020

Let’s consider the differences between the two, and why they’re both important to the success of data-driven organizations. Digging into quantitative data. This is quantitative data. It’s “hard,” structured data that answers questions such as “how many?” The challenge comes when the data becomes huge and fast-changing.

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

CIO Business Intelligence

JUNE 28, 2023

The R&D laboratories produced large volumes of unstructured data, which were stored in various formats, making it difficult to access and trace. The team leaned on data scientists and bio scientists for expert support. That, in turn, led to a slew of manual processes to make descriptive analysis of the test results. “We

Digital Transformation 103

Digital Transformation Cost-Benefit Informatics Data mining 103

Cloudera

SEPTEMBER 15, 2022

The gathering in 2022 marked the sixteenth year for top data and analytics professionals to come to the MIT campus to explore current and future trends. A key area of focus for the symposium this year was the design and deployment of modern data platforms. Are there things they should keep in mind?

Data Lake 85

Data Lake Data Architecture Data-driven Data Warehouse 85