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
Some basic understanding of spreadsheet operations
A basic understanding of what doing analytic work entails
Open mind to change and practice your work habits
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.
Preparations (filing system, inputs, model structure)
Building (calculations, testing/checking, documentation)
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.
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 this course is for:
Beginner data/financial analysts
Anyone doing regular spreadsheet work
Students who are about to enter the workforce
5 sections • 23 lectures • 1h 1m total length
Planning an analysis
Filing System example
What affects quality of input items?
Input Items checking example
What personality attribute makes a great data analyst?