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An Introduction to Data Warehouse

Analytics Vidhya

Introduction The following is an in-depth article explaining what data warehousing is as well as its types, characteristics, benefits, and disadvantages. What is a data warehouse? The post An Introduction to Data Warehouse appeared first on Analytics Vidhya. Why is […].

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Data Warehouses, Data Marts and Data Lakes

Analytics Vidhya

By their definition, the types of data it stores and how it can be accessible to users differ. This article will discuss some of the features and applications of data warehouses, data marts, and data […]. The post Data Warehouses, Data Marts and Data Lakes appeared first on Analytics Vidhya.

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Most Frequently Asked Data Warehouse Interview Questions

Analytics Vidhya

Introduction Organizations are turning to cloud-based technology for efficient data collecting, reporting, and analysis in today’s fast-changing business environment. Data and analytics have become critical for firms to remain competitive.

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Data Warehouses: Basic Concepts for data enthusiasts

Analytics Vidhya

Introduction The purpose of a data warehouse is to combine multiple sources to generate different insights that help companies make better decisions and forecasting. It consists of historical and commutative data from single or multiple sources. Most data scientists, big data analysts, and business […].

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Checklist Report: Preparing for the Next-Generation Cloud Data Architecture

Data architectures to support reporting, business intelligence, and analytics have evolved dramatically over the past 10 years.

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What are Schemas in Data Warehouse Modeling?

Analytics Vidhya

Wouldn’t the process be much easier if the raw data were more organized and clean? Here’s when Data […]. The post What are Schemas in Data Warehouse Modeling? appeared first on Analytics Vidhya. It’s possible, of course, but it can be tiresome and not be as accurate as it should be.

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The Need for Data Warehouse and Its Alternatives

Analytics Vidhya

Introduction Data from different sources are brought to a single location and then converted into a format that the data warehouse can process and store. For example, a company stores data about its customers, products, employees, salaries, sales, and invoices. A boss may […].

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Top Considerations for Building an Open Cloud Data Lake

Data fuels the modern enterprise — today more than ever, businesses compete on their ability to turn big data into essential business insights. Increasingly, enterprises are leveraging cloud data lakes as the platform used to store data for analytics, combined with various compute engines for processing that data.

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TCO Considerations of Using a Cloud Data Warehouse for BI and Analytics

Enterprises are pouring money into data management software – to the tune of $73 billion in 2020 – but are seeing very little return on their data investments.