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An Overview of Real Time Data Warehousing on Cloudera

Cloudera

Data processing and analytics drive their entire business. So they needed a data warehouse that could keep up with the scale of modern big data systems , but provide the semantics and query performance of a traditional relational database. They chose to build their RTDW on Cloudera. General Purpose RTDW.

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Object-centric Process Mining on Data Mesh Architectures

Data Science Blog: Data Engineering

In addition to Business Intelligence (BI), Process Mining is no longer a new phenomenon, but almost all larger companies are conducting this data-driven process analysis in their organization. Enhancement of the Data Model for Obect-Centricity The Event Log is a data model that stores events and their related attributes.

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

AltexSoft

The main purpose of a DW is to enable analytics: It is designed to source raw historical data, apply transformations, and store it in a structured format. This type of storage is a standard part of any business intelligence (BI) system, an analytical interface where users can query data to make business decisions.

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The Role of Database Applications in Modern Business Environments

Knowledge Hut

Database Software- Other NoSQL: NoSQL databases cover a variety of database software that differs from typical relational databases. Key-value stores, columnar stores, graph-based databases, and wide-column stores are common classifications for NoSQL databases. Columnar Database (e.g.-

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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. There are quite a few of these on the market, with each trying to enable business intelligence (BI) on MongoDB.

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100+ Big Data Interview Questions and Answers 2023

ProjectPro

Big data operations require specialized tools and techniques since a relational database cannot manage such a large amount of data. Big data enables businesses to gain a deeper understanding of their industry and helps them extract valuable information from the unstructured and raw data that is regularly collected.

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Turning Streams Into Data Products

Cloudera

This blog aims to answer two questions as illustrated in the diagram below: How have stream processing requirements and use cases evolved as more organizations shift to “streaming first” architectures and attempt to build streaming analytics pipelines? Without context, streaming data is useless.”

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