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Data Warehouses

Data Lake vs Data Warehouse

Data warehouses and data lakes represent two of the leading solutions for enterprise data management in 2023. While data warehouses and data lakes may share some overlapping features and use cases, there are fundamental differences in the data management philosophies, design characteristics, and ideal use conditions for each of these technologies.

Active Data Warehouses vs. Traditional Data Warehouses

In the digital age, data is the lifeblood of any organization. The way you store and analyze your data can significantly impact your success. This is where data warehouses come into the picture. Data warehouses are essential for businesses of all sizes, as they provide a central repository for data from a variety of sources, which can then be used for analysis and reporting. This data can be used to make better business decisions, improve operational efficiency, and identify new opportunities.

What is a Data Warehouse & Why Are They Important?

In today's digital era, a data warehouse stands as a pivotal cornerstone for businesses. A data warehouse is defined as a digital repository that houses an organization's vast amounts of data, it serves as both a vault and a library, ensuring data is not only safely stored but also easily accessible. Being able to access your company’s data is critical to business success.

Streaming Pipelines to Data Warehouses - Use Case Implementation

Data pipelines do much of the heavy lifting in organizations for integrating, transforming, and preparing data for subsequent use in data warehouses for analytical use cases. Despite being critical to the data value stream, data pipelines fundamentally haven't evolved in the last few decades. These legacy pipelines are holding organizations back from really getting value out of their data as real-time streaming becomes essential.

Data warehouse modernization: Diving deeper into Qlik Talend data integration and quality scenarios

Step right up, ladies and gentlemen, and witness the grand spectacle of the digital age! In a world where data is king, where information reigns supreme, and cloud data warehouses are multiplying like rabbits, there's a technology initiative like no other— data warehouse modernization! This article is the second in the series "Seven Data Integration and Quality Scenarios for Qlik and Talend," and answers everything you wanted to know about data warehouse modernization but were afraid to ask.

Data Warehouse Modernization: Diving Deeper into Qlik Talend Data Integration and Quality Scenarios

Step right up, ladies and gentlemen, and witness the grand spectacle of the digital age! In a world where data is king, where information reigns supreme, and cloud data warehouses are multiplying like rabbits, there's a technology initiative like no other— Data Warehouse Modernization! This article is the second in the series "Seven Data Integration and Quality Scenarios for Qlik and Talend," and answers everything you wanted to know about Data Warehouse Modernization but were afraid to ask.

AWS Redshift vs. The Rest - What's the Best Data Warehouse?

In the age of big data, where humans generate 2.5 quintillion bytes of data every single day, organizations like yours have the potential to harness more powerful analytics than ever before. But gathering, organizing, and sorting data still proves a challenge. Put simply, there's too much information and not enough context. The most popular commercial data warehouse solutions like Amazon Redshift say they deliver structured, usable data for businesses. But is this true?

17 Best Data Warehousing Tools and Resources

Data warehousing improves access to information, speeds up query-response times, and allows businesses to fetch deeper insights from big data. Previously, companies had to invest a lot in infrastructure to build a data warehouse. The advent of cloud technology has significantly reduced the cost of data warehousing for businesses.