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How to Build a Data Warehouse Using PostgreSQL in Python?

Analytics Vidhya

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction Data warehouse generalizes and mingles data in multidimensional space. The post How to Build a Data Warehouse Using PostgreSQL in Python? appeared first on Analytics Vidhya.

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Understanding the Differences Between Data Lakes and Data Warehouses

Smart Data Collective

Data lakes and data warehouses are probably the two most widely used structures for storing data. In this article, we will explore both, unfold their key differences and discuss their usage in the context of an organization. Data Warehouses and Data Lakes in a Nutshell. Key Differences.

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Apache Sqoop: Features, Architecture and Operations

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Apache SQOOP is a tool designed to aid in the large-scale export and import of data into HDFS from structured data repositories. Relational databases, enterprise data warehouses, and NoSQL systems are all examples of data storage.

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Google BigQuery Architecture for Data Engineers

Analytics Vidhya

This article was published as a part of the Data Science Blogathon Introduction Google’s BigQuery is an enterprise-grade cloud-native data warehouse. Since its inception, BigQuery has evolved into a more economical and fully managed data warehouse that can run lightning-fast […].

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Performance Tuning Practices in Hive

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction Apache Hive is a data warehouse system built on top of Hadoop which gives the user the flexibility to write complex MapReduce programs in form of SQL- like queries.

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Why optimize your warehouse with a data lakehouse strategy

IBM Big Data Hub

To do so, Presto and Spark need to readily work with existing and modern data warehouse infrastructures. Now, let’s chat about why data warehouse optimization is a key value of a data lakehouse strategy. To effectively use raw data, it often needs to be curated within a data warehouse.

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How a Discovery Data Warehouse, the next evolution of augmented analytics, accelerates treatments and delivers medicines safely to patients in need

Cloudera

How could Matthew serve all this data, together , in an easily consumable way, without losing focus on his core business: finding a cure for cancer. The Vision of a Discovery Data Warehouse. A Discovery Data Warehouse is cloud-agnostic. Access to valuable data should not be hindered by the technology.