Foundations of Data-Driven Analysis: Technical

71point4 > Foundations of Data-Driven Analysis: Technical

Course introduction

This is a foundational technical course that is designed to help data teams within an organisation to ‘speak the same language’ and to perform core data tasks. In our experience, getting technical teams to understand the broader problem each department faces typically solves 80% of the friction in delivering insight from data.

What you will learn

Upon completion of the course, participants will have the core technical knowledge and a good understanding of the common ‘data scientist’ language and jargon in three key areas:

Navigate the black screen like a pro.

Reproducible research
Realize efficiency gains with fully auditable analytics.

Excel sheets aren’t databases. This course will help you make the transition.

Course schedule

The full course is typically held over five days. However, the course structure and content can be customised according to your team’s availability and skill-level.

Over the five days course participants will be led through a series of practical in-classroom and at-home exercises that build core data skills which can be used in the workplace immediately.

  • Introduction to Ubuntu
  • How to navigate Linux
  • Review of homework from Day 1
  • Introduction to RStudio
  • RStudio as a lab-book with RMarkdown
  • Introduction to Databases
    • Database design
    • Different database types and structures
    • Loading data into SQL
  • Review of practical homework exercises from Day 2
  • Creating a new database (in-class practical exercise)
  • Using SQL to answer policy questions (in-class practical exercise)
  • Review of homework from Day 3
  • Building a data dictionary in RStudio
    • Introduction to Tidyverse R Package
    • Using R to answer policy-related questions (in-classroom practical exercise)
  • Review of homework from Day 4
  • Report writing in RMarkdown
  • Overview of advanced courses

Meet your presenters

Hanjo Odendaal
Hanjo Odendaal

Hanjo Odendaal holds a PhD in Economics from the University of Stellenbosch where his doctoral thesis focussed on exploring the media-economic nexus.

Hanjo's PhD research consisted of constructing a novel economic index which characterized the sentiment towards the current economic climate in news articles using machine learning and sentometric techniques. Hanjo leads the advanced data analytics and statistical modelling aspects of the work at 71point4. He is passionate about exploring different methodologies to collect, analyse and productionize new and alternative data sets. Recent projects include analysing large transactional datasets from an inter-bank switch in Nigeria, analysing mobile money transactional data in Rwanda and working closely with the Bureau for Economic Research (BER) to productize the work from his thesis.

Chris Garbers
Chris Garbers

Chris is a data scientist at 71point4 and holds a PhD in Economics from the University of Stellenbosch.

He has a varied research background that spans both macro and micro economics and has published articles on financial econmetrics, minimum wage effects, and macroprudential regulation. Chris enjoys package development, building production pipelines, and command-line operations. Recent projects include analysing large mobile network and transport datasets in Rwanda and building a package to scrape, parse, and curate employment data for large firms in South Africa.

James Scott
James Scott

James is a research analyst at 71point4. He is a recent graduate of the University of Cape Town, holding an Honours degree in Economics.

James has served as a volunteer consultant for Phaphama SEDI - a student organisation which aims to increase the entrepreneurial capacity of small businesses in Khayelitsha and Philippi. This experience deepened his enthusiasm for development economics and his appreciation of the need for just and equitable society. His interests lie in using data-driven approaches to identify pragmatic solutions to economic development that can power inclusive growth in South Africa.

Juste Nyirimana

Juste Nyirimana holds a Masters in Mathematical Sciences from the African Institute for Mathematical Sciences (AIMS).

Juste's master's thesis examined the effect of climate change on the probability of rain and the rainfall amounts in Kigali. Currently, Juste works as a Data Scientist at the National Bank of Rwanda. He enjoys automating tasks using object oriented programming and deriving insights from data. Recent projects include building a loan monitoring dashboard, and developing a tool for validating data from insurance companies. When not coding, Juste enjoys playing basketball, watching anime, and a cold beer😁.


Violette is a data scientist at the National Bank of Rwanda and holds a MSc in IT from Carnegie Mellon University

She has over two years of experience in the field with the majority of her work centered around building ETL pipelines, developing and automating data validation scripts and application packaging and deployment. To sum it all up, Violette enjoys the engineering side of data science.

Interested in the course?

Get in touch if you are interested in the course or would like more information:

Past courses

The course has been successfully delivered to teams from the Rwanda Ministry of Education, Ministry of Agriculture and Ministry of ICT as part of the Rwanda Economic Digitalisation Programme.