erwin

AUGUST 31, 2023

Let’s explore the continued relevance of data modeling and its journey through history, challenges faced, adaptations made, and its pivotal role in the new age of data platforms, AI, and democratized data access. Embracing the future In the dynamic world of data, data modeling remains an indispensable tool.

Data-driven 98

Data-driven Modeling Enterprise Structured Data 98

AWS Big Data

JUNE 21, 2023

The challenge comes when we need to ask more complex questions of our data, for example, what was the year-on-year quarterly sales growth by product broken down by country? The case for a data warehouse A data warehouse is ideally suited to answer OLAP queries. To house our data, we need to define a data model.

Data Warehouse 105

Data Warehouse Data Lake OLAP Cost-Benefit 105

Cloudera

OCTOBER 7, 2021

Those decentralization efforts appeared under different monikers through time, e.g., data marts versus data warehousing implementations (a popular architectural debate in the era of structured data) then enterprise-wide data lakes versus smaller, typically BU-Specific, “data ponds”.

Metadata 124

Metadata Cost-Benefit Enterprise Interactive 124

AWS Big Data

AUGUST 31, 2023

Amazon Redshift is a fast, fully managed, cloud data warehouse that allows you to process and run your complex SQL analytics workloads on structured and semi-structured data. It also helps you to securely access your data in operational databases, data lakes or third-party datasets with minimal movement or copying.

Data Warehouse 111

Data Warehouse Data-driven Testing Business Intelligence 111

AWS Big Data

OCTOBER 2, 2023

JSON data in Amazon Redshift Amazon Redshift enables storage, processing, and analytics on JSON data through the SUPER data type, PartiQL language, materialized views, and data lake queries. The function JSON_PARSE allows you to extract the binary data in the stream and convert it into the SUPER data type.

Cost-Benefit 115

Cost-Benefit Metadata Structured Data Data-driven 115

IBM Big Data Hub

JANUARY 18, 2023

In another decade, the internet and mobile started the generate data of unforeseen volume, variety and velocity. It required a different data platform solution. Hence, Data Lake emerged, which handles unstructured and structured data with huge volume. It is narrower in focus than data fabric.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

Octopai

MAY 30, 2019

The Benefits of Structured Data Catalogs. At the most basic level, data catalogs help you organize your company’s massive datasets. Most enterprises have huge data lakes with millions of touchpoints all living in the dark. They have little in the way of definition or categorization.

Metadata 40

Metadata Data Governance Data Lake IoT 40

Ontotext

MARCH 8, 2023

Specifically, the increasing amount of data being generated and collected, and the need to make sense of it, and its use in artificial intelligence and machine learning, which can benefit from the structured data and context provided by knowledge graphs. We get this question regularly.

Enterprise 52

Enterprise Knowledge Discovery Risk Machine Learning 52

Corinium

APRIL 25, 2019

Yes, definitely! The last 10+ years or so have seen Insurance become as data-driven as any vertical industry. For example, P&C insurance strives to understand its customers and households better through data, to provide better customer service and anticipate insurance needs, as well as accurately measure risks.

Insurance 150

Insurance Risk IoT Data-driven 150

AWS Big Data

OCTOBER 30, 2024

This is the final part of a three-part series where we show how to build a data lake on AWS using a modern data architecture. This post shows how to process data with Amazon Redshift Spectrum and create the gold (consumption) layer. The following diagram illustrates the different layers of the data lake.

Data Lake 94

Data Lake Machine Learning Data Architecture Data-driven 94

AWS Big Data

NOVEMBER 14, 2024

APIs act as the entry point for applications to access data, business logic, or functionality from your backend services. Amazon Data Firehose – Data Firehose is an extract, transform, and load (ETL) service that reliably captures, transforms, and delivers streaming data to data lakes, data stores, and analytics services.

Data Lake 105

Data Lake Metadata Testing Data-driven 105