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Business Intelligence Development using Python 3

Business Intelligence Development using Python 3
  • Automate and build a marketing data and user behaviour pipeline.
  • Free tutorial
  • Rating: 3.4 out of 53.4 (80 ratings)
  • 7,911 students
  • 2hr 3min of on-demand video
  • Created by Christoph Odermatt

English

What you’ll learn

  • Understand a Data Pipeline, Marketing Analytics, Data Automation and the basics of Data Engineering.
  • Learn how to use Python Libraries to create your data automation process.
  • How to make powerful analysis.
  • Create strong added value to your business. This will help you for your next job interview or your Performance Review and salary negotiations.

Requirements

  • A minimum of understanding of any computer language.

Description

Interested in automating your marketing pipeline or your business intelligence? Then this is your course! Learn how to relieve yourself of repetitive work by programming it. All this in less than 2 hours!

There are many Business Intelligence, Python beginners or Data Analytics courses out there. I combine these subjects to create a course that connects and automates your Data tracking tools to your Business Intelligence tool.

We will Extract real-life data from Google Analytics and Facebook with Python and Transform these data points into a useful format and then Load them to Google Sheets => ETL (Extract, Transform, Load)

Python is the best language to automate these processes and will be used in this course. This course is truly step-by-step as we made the course so you can code along with us. We extract data from 4 different sources and then use those data points to be able to decide on our future business strategy. And all is done through live examples. I am using my previous teaching experience as a lecturer to create this easy to understand course.

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As a bonus, this course includes all the Python code templates we created for you to download and use on your own projects.

I and my team are constantly available to support you in your learning and to answer questions.

I’ll see you on the inside!

Yours sincerely,

Christoph Odermatt

What are the requirements?

  • A minimum understanding of any computer language and some marketing experience.
  • Any computer running Mac, Windows, or Linux, all is shown on a Mac.
  • All the tools used in the course are free, except for your Marketing you are using.
  • Preferably you already have data from your Marketing on Facebook or Google AdWords.
  • And passion to learn.

What am I going to get from this course?

  • Understand a Data Pipeline, Marketing Analytics, Data Automation and the basics of Data Engineering.
  • Learn how to use Python Libraries to create your data automation process.
  • How to make powerful analysis.
  • Create strong added value to your business. This will help you for your next job interview or your Performance Review and salary negotiations.

Who this course is for:

  • Anyone interested in Data automation.
  • Anyone who is not that comfortable with coding but who is interested in programming with Python. The course has been created with the beginner in mind.
  • Intermediate programmers can learn the Business Intelligence side of the course.
  • Any students in college who want to start a career in Data Intelligence.
  • Any people who want to create added value to their business by automating work.

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Course content

6 sections • 44 lectures • 2h 2m total lengthCollapse all sections

Introduction2 lectures • 3min

  • Introduction02:31
  • Download Python00:45

Let’s get started3 lectures • 12min

  • Marketing KPIs05:06
  • Create accounts05:11
  • Install libraries with PIP01:53
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Access Google Analytics data21 lectures • 1hr 12min

  • Simple GA data access08:21
  • GA data access with active GA account00:27
  • Data access on Jupyter Notebook04:33
  • Add ISO-week function04:30
  • Add extract unsegmented data function03:07
  • Add extract segmented data function04:03
  • Checking for errors in the first part of the code03:11
  • Get the correct date for your function01:19
  • Checking for errors in the extracting data functions03:39
  • Transform extracted totals data to Pandas DataFrame05:19
  • Transform extracted details data to Pandas DataFrame03:15
  • Add initialise Google Drive function02:45
  • Add download worksheet function04:30
  • Add loop function for totals data02:54
  • Authenticate Google Drive API03:20
  • Check for errors in the loop totals function02:05
  • Add loop function for details data02:11
  • Load data to Google Spreadsheet01:45
  • More checks for errors in the loop totals function03:01
  • Add sort index function05:26
  • Make a Python file with complete code02:46

Access Facebook data12 lectures • 28min

  • Create a Facebook app and get the code template02:12
  • Simple Facebook data access03:11
  • Move code to Jupyter Notebook01:37
  • Copy functions from GA Jupyter Notebook and add extract data function02:46
  • Check for errors by printing the extracted data01:52
  • Transform extracted totals data to Pandas DataFrame02:28
  • Transform extracted details data to Pandas DataFrame02:43
  • Add sorting function and loop totals function03:25
  • Add loop function for details data01:09
  • Add sleep to API query function03:39
  • Make a Python file with complete code01:34
  • Test the Python file01:01

Finish assigning data and automate scripts3 lectures • 7min

  • Assignment worksheet totals02:05
  • Assignment worksheet details01:23
  • Crontab automation03:39

Final code3 lectures • 1min

  • Google Analytics code00:02
  • Facebook code00:02
  • JSON template00:09

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