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Data Science for Finance: Benefits, Applications, Examples

Knowledge Hut

Data science is the field of study that deals with a huge volume of data using modern technologically driven tools and techniques to find some sort of pattern and derive meaningful information out of it that eventually helps in business and financial decisions. This work is done by financial data scientists.

Finance 93
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5 reasons why Business Intelligence Professionals Should Learn Hadoop

ProjectPro

The toughest challenges in business intelligence today can be addressed by Hadoop through multi-structured data and advanced big data analytics. Big data technologies like Hadoop have become a complement to various conventional BI products and services. Big data, multi-structured data, and advanced analytics.

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Hive Interview Questions and Answers for 2023

ProjectPro

Pig vs Hive Criteria Pig Hive Type of Data Apache Pig is usually used for semi structured data. Used for Structured Data Schema Schema is optional. Language It is a procedural data flow language. It is suggested to use standalone real database like PostGreSQL and MySQL.

Hadoop 40
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70+ Azure Interview Questions and Answers to Prepare in 2023

ProjectPro

Azure Backup is a cloud-based solution offered by Microsoft that allows you to backup Azure Windows VMs, Azure Managed Disks, Azure File shares, SQL Server databases, SAP HANA databases, Azure PostgreSQL databases, etc. Azure Table Storage- Azure Tables is a NoSQL database for storing structured data without a schema.

BI 52
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100+ Data Engineer Interview Questions and Answers for 2023

ProjectPro

Relational Database Management Systems (RDBMS) Non-relational Database Management Systems Relational Databases primarily work with structured data using SQL (Structured Query Language). SQL works on data arranged in a predefined schema. Non-relational databases support dynamic schema for unstructured data.

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Top 100 Hadoop Interview Questions and Answers 2023

ProjectPro

Hadoop vs RDBMS Criteria Hadoop RDBMS Datatypes Processes semi-structured and unstructured data. Processes structured data. Schema Schema on Read Schema on Write Best Fit for Applications Data discovery and Massive Storage/Processing of Unstructured data. are all examples of unstructured data.

Hadoop 40