AWS Big Data

NOVEMBER 26, 2024

Initially, data warehouses were the go-to solution for structured data and analytical workloads but were limited by proprietary storage formats and their inability to handle unstructured data. In practice, OTFs are used in a broad range of analytical workloads, from business intelligence to machine learning.

Metadata 105

Metadata Data Lake Snapshot Data Warehouse 105

CIO Business Intelligence

OCTOBER 25, 2023

Enterprise use of AI tools will only grow, with industries like manufacturing leading the charge Our research shows that mirroring the broader AI trend, enterprises across industry verticals sharply increased their use of AI from May 2023 to June 2023, with sustained growth through August 2023.

Enterprise 133

Enterprise Manufacturing Risk Data-driven 133

Cloudera

DECEMBER 11, 2020

Without meeting GxP compliance, the Merck KGaA team could not run the enterprise data lake needed to store, curate, or process the data required to inform business decisions. It established a data governance framework within its enterprise data lake. Driving innovation with secure and governed data .

Data Lake 98

Data Lake Cost-Benefit Unstructured Data Data Governance 98

CIO Business Intelligence

FEBRUARY 16, 2023

My vision is that I can give the keys to my businesses to manage their data and run their data on their own, as opposed to the Data & Tech team being at the center and helping them out,” says Iyengar, director of Data & Tech at Straumann Group North America.

Unstructured Data 105

Unstructured Data Data Lake Prescriptive Analytics Data Warehouse 105

AWS Big Data

MARCH 25, 2024

You can find similar use cases in other industries such as retail, car manufacturing, energy, and the financial industry. In this post, we discuss why data streaming is a crucial component of generative AI applications due to its real-time nature.

Data Lake 122

Data Lake Unstructured Data Management Snapshot 122

Sisense

OCTOBER 6, 2020

Most commonly, we think of data as numbers that show information such as sales figures, marketing data, payroll totals, financial statistics, and other data that can be counted and measured objectively. This is quantitative data. It’s “hard,” structured data that answers questions such as “how many?”

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

IBM Big Data Hub

SEPTEMBER 19, 2023

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

Data Science 76

Data Science Data Analytics Prescriptive Analytics Analytics 76