6. Data Analytics - Ask Questions to Make Data-Driven Decisions - Week 1

Definitions:

Structured thinking // the process of recognizing the current problem or situation, organizing available information, revealing gaps and opportunities, and identifying the options.

Target Audience // people the company is trying to reach

Leading question // a question that leads someone to answer in a certain way

Fairness // ensuring that your questions don't create or reinforce bias

Common types of problems:

    1. Making predictions

            Using data to make an informed decisions about how things may be in the future

    2. Categorizing things

            Assigning information to different groups or clusters based on common features

    3. Spotting something unusual

            Identifying data that is different from the norm

    4. Identifying themes

            Grouping categorized information into broader concepts

    5. Discovering connections

            Finding similar challenges faced by different entities and combining data and insights to address             them

    6. Finding patterns

            Using historical data to understand what happened in the past and is therefore likely to happen                 again


Effective vs Ineffective Questions:

    Ineffective: vague, lacks context, closed-ended, leading questions

    Effective: open-ended


SMART Methodology:

    Specific;

            Are simple, significant, and focused on a single topic or a few closely related ideas.

    Measurable;

            Can be quantified and assessed.

    Action-oriented;

            Encourages change.

    Relevant;

            They matter, are important, and have significance to the problem you're trying to solve.

    Time-bound

            Specifies the time to be studied. Limits possibilities so answers can be specific.


Core Roles in Data Analytics:

    - Data Analyst

    - Data Engineer

    - Data Scientist

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