2. Data Analytics - Data, Data, Everywhere - Week 2

Definitions:

Analytical Skills // Qualities and characteristics associated with solving problems using facts

Context // a condition in which something exists or happens

A technical mindset // the ability to break things down into smaller steps or pieces and work with them in an orderly and logical way

Data design // how you organize information that is logical and clear to you or for the purpose

Data strategy // the management of the people, processes and tools used in data analysis

Analytical thinking // identifying and defining a problem and then solving it by using data in an organized, step-by-step manner

Data Visualization // graphical representation of information. Graphs, maps, and charts.

Root Cause // the reason why a problem occurs

Gap Analysis // a method for examining and evaluating how a process works currently in order to get where you want to be in the future

Data-driven decision-making // using facts to guide business strategy

Quartile // divides data points into four equal parts

Nonprofits // are organizations dedicated to advancing a social cause or advocating for a particular effort


5 Key Aspects of Analytical Skills

    1. Curiosity

    2. Understanding Context

    3. Having a technical mindset

    4. Data design

    5. Data strategy


5 Key Aspects of Analytical Thinking

    1. Visualization; help understand and explain information effectively

    2. Strategy; know what to achieve with the data and how to get there

    3. Problem-orientation; identify, describe, and solve problems.

    4. Correlation; being able to identify correlation between data

    5. Big-picture and detail-oriented thinking; seeing the big picture and the small details


Correlation does not equal causation.


Data Analysts Questions:

    - What is the root cause of the problem? (Ask why 5 times to hopefully get the answer)

    - Where are the gaps in our process? (Use Gap Analysis)

    - What did we not consider before?

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