AWS Big Data

APRIL 19, 2023

In this post, we look at three key challenges that customers face with growing data and how a modern data warehouse and analytics system like Amazon Redshift can meet these challenges across industries and segments. Nasdaq’s massive data growth meant they needed to evolve their data architecture to keep up.

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Data Warehouse Data Lake Unstructured Data Optimization 59

AWS Big Data

DECEMBER 21, 2023

The Data Platform team is responsible for supporting data-driven decisions at smava by providing data products across all departments and branches of the company. Branches range by products, namely B2C loans, B2B loans, and formerly also B2C mortgages. The departments include teams from engineering to sales and marketing.

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Data Lake Data Warehouse Data-driven B2B 103

AWS Big Data

NOVEMBER 29, 2023

In 2013, Amazon Web Services revolutionized the data warehousing industry by launching Amazon Redshift , the first fully-managed, petabyte-scale, enterprise-grade cloud data warehouse. Amazon Redshift made it simple and cost-effective to efficiently analyze large volumes of data using existing business intelligence tools.

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Data Warehouse Analytics Data Lake Machine Learning 112

AWS Big Data

NOVEMBER 28, 2023

To run analytics on their operational data, customers often build solutions that are a combination of a database, a data warehouse, and an extract, transform, and load (ETL) pipeline. ETL is the process data engineers use to combine data from different sources.

Data Warehouse 104

Data Warehouse Data-driven Machine Learning B2B 104

Ontotext

FEBRUARY 12, 2024

A centralized data engineering team focuses on building a governed self-serviced infrastructure, while domain teams use the services to build full-stack data products. However, data mesh is not about introducing new technologies. by building data products with domain owners.

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Data-driven Data Lake Data Quality Business Objectives 59