AWS Big Data

OCTOBER 23, 2024

Amazon Redshift enables data warehousing by seamlessly integrating with other data stores and services in the modern data organization through features such as Zero-ETL , data sharing , streaming ingestion , data lake integration , and Redshift ML.

Data Warehouse 96

Data Warehouse Cost-Benefit Data Lake Data-driven 96

AWS Big Data

DECEMBER 19, 2024

Data has become an invaluable asset for businesses, offering critical insights to drive strategic decision-making and operational optimization. Delta tables technical metadata is stored in the Data Catalog, which is a native source for creating assets in the Amazon DataZone business catalog.

Data Governance 52

Data Governance Publishing Data-driven Metadata 52

Cloudera

MAY 12, 2021

Use cases could include but are not limited to: predictive maintenance, log data pipeline optimization, connected vehicles, industrial IoT, fraud detection, patient monitoring, network monitoring, and more. DATA FOR ENTERPRISE AI. Nominations for the 2021 Cloudera Data Impact Awards are open from now until July 23.

Digital Transformation 70

Digital Transformation Machine Learning Optimization Data Lake 70

AWS Big Data

MARCH 7, 2023

Flexible and easy to use – The solutions should provide less restrictive, easy-to-access, and ready-to-use data. They should also provide optimal performance with low or no tuning. A data hub contains data at multiple levels of granularity and is often not integrated. Data repositories represent the hub.

Analytics 78

Analytics Data Warehouse Data Lake Metadata 78

AWS Big Data

JULY 28, 2023

Amazon Redshift now makes it easier for you to run queries in AWS data lakes by automatically mounting the AWS Glue Data Catalog. You no longer have to create an external schema in Amazon Redshift to use the data lake tables cataloged in the Data Catalog.

Data Lake 73

Data Lake Data Governance Data Warehouse Data-driven 73

Cloudera

FEBRUARY 16, 2022

In the case of CDP Public Cloud, this includes virtual networking constructs and the data lake as provided by a combination of a Cloudera Shared Data Experience (SDX) and the underlying cloud storage. Each project consists of a declarative series of steps or operations that define the data science workflow.

Machine Learning 85

Machine Learning Modeling Metadata Recreation/Entertainment 85

IBM Big Data Hub

OCTOBER 16, 2023

Foundation models can use language, vision and more to affect the real world. GPT-3, OpenAI’s language prediction model that can process and generate human-like text, is an example of a foundation model. They are used in everything from robotics to tools that reason and interact with humans.

Risk 70

Risk Modeling Management Metadata 70

AWS Big Data

NOVEMBER 14, 2023

Ten years ago, we launched Amazon Kinesis Data Streams , the first cloud-native serverless streaming data service, to serve as the backbone for companies, to move data across system boundaries, breaking data silos. Another integration launched in 2023 is with Amazon Monitron to power predictive maintenance management.

IoT 59

IoT Data-driven Data Lake Data Strategy 59

IBM Big Data Hub

OCTOBER 16, 2023

Marketers use ML for lead generation, data analytics, online searches and search engine optimization (SEO). ML algorithms and data science are how recommendation engines at sites like Amazon, Netflix and StitchFix make recommendations based on a user’s taste, browsing and shopping cart history.

Machine Learning 48

Machine Learning Marketing Forecasting Modeling 48

Alation

APRIL 14, 2022

For example, data science always consumes “historical” data, and there is no guarantee that the semantics of older datasets are the same, even if their names are unchanged. Pushing data to a data lake and assuming it is ready for use is shortsighted. It’s not a simple definition.

Metadata 59

Metadata Data Governance Data-driven Modeling 59

Smart Data Collective

AUGUST 7, 2019

The concept of data analysis is, therefore, essential for every organization that deals with vast amounts of data every day. There are many benefits to data analytics. They include everything from improving internal processes, optimizing security, and increasing efficiency. The task of analyzing data is no simple feat.

Data Analytics 111

Data Analytics Analytics Big Data Advertising 111

CIO Business Intelligence

DECEMBER 13, 2022

We’re also doing a lot with population health management, performing more comprehensive patient assessments, managing our high-risk patients, stabilizing transitions of care, optimizing outpatient care, and really trying to call out things that help us understand disease progression.

Strategy 98

Strategy Technology Digital Transformation Data Lake 98

Jet Global

MAY 9, 2024

The key components of a data pipeline are typically: Data Sources : The origin of the data, such as a relational database , data warehouse, data lake , file, API, or other data store. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52