Remove Data Visualization Remove Hadoop Remove Support Vector Machines
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Big Data Syllabus: A Comprehensive Overview

Pickl AI

Big Data Technologies and Tools A comprehensive syllabus should introduce students to the key technologies and tools used in Big Data analytics. Some of the most notable technologies include: Hadoop An open-source framework that allows for distributed storage and processing of large datasets across clusters of computers.

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Data science vs. machine learning: What’s the difference?

IBM Journey to AI blog

The fields have evolved such that to work as a data analyst who views, manages and accesses data, you need to know Structured Query Language (SQL) as well as math, statistics, data visualization (to present the results to stakeholders) and data mining.

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What Does the Modern Data Scientist Look Like? Insights from 30,000 Job Descriptions

ODSC - Open Data Science

Tools like Apache Airflow are widely used for scheduling and monitoring workflows, while Apache Spark dominates big data pipelines due to its speed and scalability. Hadoop, though less common in new projects, is still crucial for batch processing and distributed storage in large-scale environments.