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Description

The inspiration for building this course is right in the title – it's the Analytics Context We Wish We Had, When We First Started.
This course now includes free access to our Data Fundamentals Handbook, which compliments all the video content in this course in written form.
This course starts with an introduction to the world of data. Context is critical, and it most definitely applies to learning how to work with data. Before even touching a data tool, amongst many other things, we believe it's vital that one fully understands the context surrounding data.
From there you'll delve deep in to the differences between Data Analytics, Data Science, and Data Engineering, and how each of these roles provide value in their own way. In addition, you'll gather a deep understanding of the tools used by professionals – which are the most popular, when one would be preferred over another, and how they can be used in collaboration.
Next, you'll learn about the technical processes that encompass the lineage of data. This section will enable you to internalize the concept of a Data Pipeline, and start building-up a lexicon and literacy for how data moves from collection to analysis.
Finally, you'll see a step-by-step learning roadmap to become a practitioner of Data Analytics. In this section you'll gain access to recommended steps to take after this course, and career paths that are most relevant.
One of the biggest challenges in getting started with data is finding the right place to start, we believe this is it. You are 90 minutes away from truly understanding the world of data – a perspective we've built over a decade of experience.
Who this course is for:
People who want to learn more about data, but don't know where to start
Anyone who believes that learning to work with data will change the way they do business, live their lives and help others
Someone who wants to ultimately work with data tools and learn how to make data-driven decisions
This course is the first step in learning how to work with data, building the context needed to understand the big picture
This course is NOT an Excel or SQL tutorial

What you'll learn

Free access to our Data Fundamentals Handbook, which compliments the video content in this course in written form

The world of data is massive, but that doesn't mean it has to be complicated. Cut through the noise and get a clear vision of the "Big Picture"

Learn the distinguishing factors between Data Analytics, Data Science, and Data Engineering

Discover data tools – which are the most popular, how they work together, and why some are preferred over others

Demystify how data moves from collection to analysis, and what people, processes and technologies are involved

Get a step-by-step learning roadmap to becoming a practitioner of Data Analytics, and insight in to career paths that are most relevant

Context gives each of us the grounding we need to think about data more meaningfully and know it better. Learn to break down some of data's most prized concepts and terms

Requirements

  • You will need a copy of Adobe XD 2019 or above. A free trial can be downloaded from Adobe.
  • No previous design experience is needed.
  • No previous Adobe XD skills are needed.

Course Content

27 sections • 95 lectures
Expand All Sections
1-Setting the Stage: An Introduction to Data
1
1.1-Setting the Stage: An Introduction to Data
2-Roles and Skills of Data Professionals
1
2.1-Roles and Skills of Data Professionals
3-Classification of Data Analytics Tools
1
3.1-Classification of Data Analytics Tools
4-Deep Dive: The Data Analytics "Tool Triangle"
1
4.1-Deep Dive: The Data Analytics "Tool Triangle"
5-Data Types, Files, and Formats
1
5.1-Data Types, Files, and Formats
6-Data Pipelines: How Data Moves From Collection to Analysis
1
6.1-Data Pipelines: How Data Moves From Collection to Analysis
7-Data Flashcards: Key Concepts and Terminology
1
7.1-Data Flashcards: Key Concepts and Terminology
8-Data Analytics Learning Roadmap and Career Paths
1
8.1-Data Analytics Learning Roadmap and Career Paths
9-Thank You
1
9.1-Thank You