A Data Analyst is an explorer, an artist, and a detective all rolle into one.
Section One (Data, Data Everyhere) of the Google Data Analytics Course lays out the introduction to the course to come. It effective lays out the basics of data analysis, how to understand data, and what steps we will be using as we attempt to become proficient data analysts.
We started with the basics:
- The data ecosystem is the elements that interact with one another to produce manage, store, organize and analyze data.
- data science: the creation of new ways ot modelling and understanding the unknown by using raw data.
- data analysis: The collection, tranformation and organization of data in order to draw conclusions, make predictions and drive informed decision-making.
- data analytics: the science of data.
Very early on, the instructors brought up the concept of data-drive decision-making which will occur as a key concept throughout the course.
The key skills for a data analyst are:
- an understanding of context
- the ability to adopt a technical mindset
- an awareness of data design
- an ability to plan data strategy.
Curiousity is the most obvious - and the most important. A data analyst has to want to Understand things, to seek out stories and patterns.
Understanding context no analysis of raw data is useful without understanding the context of how it was collected, the factors that influenced the data collected. Context is everything in understanding data.
technical mindset is the ability to break down a task into smaller steps, using an orderly process to do so.
data design is you we can organize data. How will be sort our data, for example alphabetical or numerical order, size, or other means.
data strategy is the management of the people, processes and tools we will be using in our analysis, and the steps we will be following to work through the process.