Data Analytic Principles/Habits

A set of highly effective and easy to enforce habits that professionalize your analytic work

Ratings 4.33 / 5.00
Data Analytic Principles/Habits

What You Will Learn!

  • Recognize the importance of a methodical approach to doing analytic work
  • Learn good habits for doing analytic work
  • Pick up universally applicable, practical, easy to enforce habits

Description

Do you want to turn your analytic work from mediocre to great?

Do you want to shine at the workplace by demonstrating a superior, professional analytic ability?

Then this course is for you... Read on please.

Over 15 years, I identified a number of steps that elevate the quality of data analytic work. When done habitually, these steps will professionalize the analysis, making it more error resistant, flexible and effective in answering the “question”. This content is what I wish someone taught me when I first started working as a data analyst.

Course content:

  1. Context
  2. Preparations (filing system, inputs, model structure)
  3. Building (calculations, testing/checking, documentation)
  4. Output (results, presentation, iterations)

I have distilled the content into easy to remember sections to ensure that you gain a long lasting value from this course. Each section comes with supplemental material including poster for easy reminder and course reading that for reinforcements.

In Summary

Goal - Help you learn and adopt good habits when doing analytic work.

Format - 40 mins of videos that introduce the principles and illustrate the principles through an example. Poster and Reading Materials for each section serves as cheat sheets for future reference and enforcement.

Target Audience - Beginner level data analysts or Students who are about to enter the workforce (data, statistical, financial analyses)

This course is not a training program on how to use MS Excel. We use Excel to illustrate the principles; not hours on hours of lectures that are hard to remember. 40 minutes is all you need.

Who Should Attend!

  • Beginner data/financial analysts
  • Anyone doing regular spreadsheet work
  • Students who are about to enter the workforce

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Tags

  • Data Analysis
  • Financial Analysis
  • Habits

Subscribers

194

Lectures

23

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