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Demystifying Data Science and Analysis
Rating: 5.0 out of 5(1 rating)
5 students

Demystifying Data Science and Analysis

A CommonSensical Guide To Data Terminology
Created byDeena Chadwick
Last updated 4/2021
English

What you'll learn

  • Data Job Titles & Skills – Differentiate similar titles, Know their responsibilities, and Understand the skills needed to be proficient
  • Storing & Packaging Data – Difference between Data Warehouse & Data Lake, Know which data stores work best, Learn the common issues associated with storing data
  • Collecting & Growing Data – Farming & Mining, Learn different ways to grow your data and why, Understand why it is important to grow as well as collect data
  • Cleaning & Fixing Data – 3 steps to cleaning & fixing your data and Know the common tasks used for cleaning data
  • Data Protection – Governance, Compliance, & Security, Responsibilities for data security and compliance, and Introduction to data dishonesty and mis uses
  • Data Analysis – Business Intelligence planning tools, Frameworks for conducting Data Analysis, and How to analyze data for patterns and trends

Course content

1 section • 7 lectures • 1h 10m total length

  • Introduction6:04

    Explore the language of data, clarify terminology and jargon across SQL, NoSQL, JSON, XML, and data concepts, and distinguish similar terms like track, path, and pipeline to unlock data science.

  • Pop Quiz to test your knowledge of Data Terminology
  • Demystifying Data Job Titles & Skills11:26

    Clarify data job titles and skills by contrasting data controller and processor, architect and engineer, scientist and analyst, with governance and data management context.

  • Demystifying Data Storage9:18

    Clarify data storage concepts by explaining data warehouse, data lake, and data swamp, and outline data vaults, data marts, data sets, dark data, and duplicate data.

  • Demystifying Data Collection8:15

    Learn how to collect and maintain data, including requesting, purchasing, and measuring data, and grow it through farming, mining, and augmentation, then clean, validate, and enrich for reliable insights.

  • Demystifying Data Protection1:32
  • Demystifying Data Analysis11:11

    Discover how qualitative, quantitative, and topological data analysis empower business intelligence and strategic planning by linking data insights to vision, strategy, and tactics.

  • For Your Reference: Glossary of 300 Data Terms & Phrases22:18

Requirements

  • Interest in learning about data and the terms and phrases used
  • No prior experience is required. We will start with the basics

Description

Do you want to learn more about data analysis and data science, but find the terms and phrases used confusing? If so you are not alone.

This course will help Demystify Data Science & Data Analysis by defining and explaining the most commonly used and most commonly confused Data Terms and Phrases.

Data is a hot topic right now, and data jobs and responsibilities are increasing. Do you know the difference? Data Lake, Data Warehouse, Data Mart or Data Vault? Data Scientist, Data Analyst, or Data Engineer? Data Fishing, Data Farming, or Data Mining? Dirty, Dark, or Corrupt Data? 

If you want to Understand the Jargon, Speak the Language, and Know the Commonly Used terms & Phrases, this course is for you.

Data Job Titles & Skills

  • Differentiate between similar titles

  • Know their responsibilities

  • Understand the skills needed to be proficient

Storing & Packaging Data

  • Differentiate between Data Warehouse & Data Lake

  • Know which data stores work best

  • Learn the common issues associated with storing data

Collecting & Growing Data

  • Differentiate between Farming & Mining

  • Learn different ways to grow your data and why

  • Understand why it is important to grow as well as collect data

Cleaning & Fixing Data

  • 3 steps to cleaning & fixing your data

  • Know the common tasks used for cleaning data

Data Protection

  • Differentiate between Governance, Compliance, & Security

  • Responsibilities for data security and compliance

  • Introduction to data dishonesty and mis uses

Data Analysis

  • Business Intelligence planning tools

  • Frameworks for conducting Data Analysis

  • How to analyze data for patterns and trends

Who this course is for:

  • Someone who wants to become or will work with a Data Analyst or Data Scientist
  • You should take this course if you want to be able to have conversations on Business Intelligence and Data Visualization
  • Anyone who want to learn the terms and phrases use by Data Scientists and Analysts
  • Product Owners who want to learn more about data analysis and data requirements

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