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Data Warehouses: Basic Concepts for data enthusiasts

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. 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.

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Data Warehouse in Azure SQL

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction to Data Warehouse SQL Data Warehouse is also a cloud-based data warehouse that uses Massively Parallel Processing (MPP) to run complex queries across petabytes of data rapidly. Import big […].

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Building Data Warehouse Using Google Big Query

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction to Data Warehouse In today’s data-driven age, a large amount of data gets generated daily from various sources such as emails, e-commerce websites, healthcare, supply chain and logistics, transaction processing systems, etc.

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HIVE – A DATA WAREHOUSE IN HADOOP FRAMEWORK

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon Different components in the Hadoop Framework Introduction Hadoop is. The post HIVE – A DATA WAREHOUSE IN HADOOP FRAMEWORK appeared first on Analytics Vidhya.

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Data Modelling Techniques in Modern Data Warehouse

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Hello, data-enthusiast! In this article let’s discuss “Data Modelling” right from the traditional and classical ways and aligning to today’s digital way, especially for analytics and advanced analytics.

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SAP Datasphere Powers Business at the Speed of Data

Rocket-Powered Data Science

Data collections are the ones and zeroes that encode the actionable insights (patterns, trends, relationships) that we seek to extract from our data through machine learning and data science. Instead, what we really need is for our business to run at the speed of data. Datasphere is not just for data managers.

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Differentiating Between Data Lakes and Data Warehouses

Smart Data Collective

The market for data warehouses is booming. While there is a lot of discussion about the merits of data warehouses, not enough discussion centers around data lakes. We talked about enterprise data warehouses in the past, so let’s contrast them with data lakes. Data Warehouse.

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