Remove Analytics Application Remove Data Warehouse Remove Relational Database
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Five Ways to Run Analytics on MongoDB – Their Pros and Cons

Rockset

Let’s explore five ways to run MongoDB analytics, along with the pros and cons of each method. 1 – Query MongoDB Directly The first and most direct approach is to run your analytical queries directly against MongoDB. 3 – Use a Data Warehouse Next, you can replicate your data to a data warehouse.

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SQL for Data Engineering: Success Blueprint for Data Engineers

ProjectPro

Businesses will be better able to make smart decisions and achieve a competitive advantage if they can successfully integrate data from various sources using SQL. Data engineers can extract data from a table in a relational database using SQL queries like the "SELECT" statement with the "FROM" and "WHERE" clauses.

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Real-Time Data Ingestion: Snowflake, Snowpipe and Rockset

Rockset

Organizations that depend on data for their success and survival need robust, scalable data architecture, typically employing a data warehouse for analytics needs. Snowflake is often their cloud-native data warehouse of choice. Next Steps Snowflake’s scalable relational database is cloud-native.

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An Overview of Real Time Data Warehousing on Cloudera

Cloudera

Users today are asking ever more from their data warehouse. As an example of this, in this post we look at Real Time Data Warehousing (RTDW), which is a category of use cases customers are building on Cloudera and which is becoming more and more common amongst our customers. What is Real Time Data Warehousing?

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What is Data Hub: Purpose, Architecture Patterns, and Existing Solutions Overview

AltexSoft

One of the innovative ways to address this problem is to build a data hub — a platform that unites all your information sources under a single umbrella. This article explains the main concepts of a data hub, its architecture, and how it differs from data warehouses and data lakes. What is Data Hub?

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100+ Big Data Interview Questions and Answers 2023

ProjectPro

Big Data is a collection of large and complex semi-structured and unstructured data sets that have the potential to deliver actionable insights using traditional data management tools. Big data operations require specialized tools and techniques since a relational database cannot manage such a large amount of data.

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20 Solved End-to-End Big Data Projects with Source Code

ProjectPro

A big data project is a data analysis project that uses machine learning algorithms and different data analytics techniques on a large dataset for several purposes, including predictive modeling and other advanced analytics applications. Access Solution to Data Warehouse Design for an E-com Site 4.