Overview
“Every two days we now create as much information as we did from the dawn of civilization up until 2003.” – Eric Schmidt (CEO of Google)
“Data are widely available; what is scarce is the ability to extract wisdom from them.” – Hal Varian (UC Berkeley and Chief Economist, Google)
The preceding quotes summarize the central theme of this seminar. The world today is awash with data, quantitative and qualitative. In every aspect of our daily lives, from how we work, shop, communicate, or socialize, we consume and create vast amounts of information. These daily activities often create digitized data that could be stored, mined, and analyzed by firms hoping to create valuable business intelligence. With technological advances and developments in customer databases, many firms have access to vast amounts of high-quality data that could be deployed to understand customer behavior and devise better business tactics.
However, much of the promise of such data-driven strategies has failed to materialize largely because some businesses do not attach value to certain data at their disposal. They either do not know that this data exist or they lack the skills to extract value from them. For organizations that have good knowledge of the data they have, the challenge is to figure out how to use this massive amount of data to make better decisions and sharpen their performance. Organizations that lack knowledge of their data face a double layer of challenge: they need the skills to harness this data and the skills to extract actionable information from the data.
In Nigeria, many organizations not only have little information about the data they have, in most cases, they also ignore important opportunities to acquire new data that could – with some processing and mining – be used for better decision-making and improving performance. This program is therefore designed to systematically improve the way most organizations in Nigeria think about data and its role in business and government institutions. The program is positioned to help organizations master the skills requisite for acquiring better data easily and using this data, alongside existing data, for improved decision-making and value creation.
This program is not about statistics, mathematics, or the theoretical aspects of machine learning and modeling. The focus would be on applications of methods in the novel field of data science in extracting actionable knowledge from data. Practical methods for data collection, cleaning, organization, visualization, analysis, and generation of insights would be demonstrated in R – an open-source language popular for doing data science. Emphasis would be placed on how the skills can be applied in areas such as competitive intelligence, human resource management, customer relationship management, market analysis, marketing and operations, etc.
Learning Objectives and Benefits
- Understanding the need for data-driven decision-making
- Learning ways of harnessing existing, ignored, data for business decision-making
- Learning techniques for processing data for analysis
- Obtaining the skills for generating patterns from data and making business predictions
- Acquiring skills for using structured data for business decision-making
- Learning skills for using unstructured/textual data for product development and customer relationship management
- Acquiring skills in data visualization and infographics
Who should attend
This seminar is designed for consultants, data analysts, quality controllers, human resource persons, investment bankers, organizations conducting industry and business research, digital marketers, IT persons, as well as individuals who desire data science skills to improve their market/employment potentials extensively.
Structure and Curriculum
Day 1: Data in Business Organizations and Data Science Tools for Extracting Value from Data
– Understanding the need for data-driven decision-making and the role of Data Science methods – Better ways of obtaining and warehousing business data.
– R for Applied Data Science: Getting Started, Workflow
– Case Study: Data-Driven Decision Making
Day 2: Data wrangling, Transformation, and basic Programming skills
– Tibbles, Data imports, Tidy Data and Relational Data
– Case Study: A Data Tidying Problem
– Filtering, Arranging, Grouping and Mutating Data
– Pipes, Vectors, Functions, and Iterations as Basic programming skills in applied Data Science
– Case Study: Bringing it All together
Day 3: Data Visualization, Exploratory Data Analysis (EDA)
– Visualization as a way of generating Insights from Data
– Data Visualization Tools: Aesthetic Mappings, Facets, Geometric objects – Data Visualization Tools: Infographics
– Exploratory Data Analysis: Generating questions about your data, searching for answers, and using what you learn to refine your questions and/or generate new questions
– Case Study: EDA as an iterative cycle in generating business solutions
Day 4: Model building and predictive insights
– Model Basics: tools for gaining insight into what a model tells you about your data – Model Building: using models to pull out known patterns in real data
– Many Models: using many simple models to understand complex datasets
– Case Study: Data to Model
Day 5: Text mining, analytics, and Communicating insights from data
– Unstructured Data in business organizations and the role of Text mining and analytics – Text Mining Tools: Corpus, TM, Stemming, TDM, DTM
– Text Mining and Analytics Workflow: Preprocessing, Staging and Analysis – Text Analytics: Word Frequency, Clustering, Sentiments Analysis, Topic Modeling, Word Cloud
– Case Study: Value in Text
– Communicating insights from data: R markdown, Graphics for communication
Admission process
1. Click on the Apply Now tab
2. Select the number of participants to enroll in the programme
3. Fill in your details to complete your application
4. Request for an invoice or make an instant payment via our secured payment gateway
5. Upon confirmation of payment, a programme manager will get in touch with you at least three days before the programme commences.
Faculty
Academic Director
Prior to his faculty appointment, Prof. Bongo Adi was a CIPRA MTN Research Fellow at Lagos Business School where he facilitated classes in Public Private Partnerships (PPPs), project finance, and development.
He led various collaborations on research, case studies, and stakeholder engagement with various government agencies including ICRC, NERC, and several ministries involved in PPPs.
He has over 15 years of experience in teaching, policy research, and consulting. As an assistant professor, he has lectured at the University of Tsukuba, Japan, where he was a JSPS fellow, and at the American University of Nigeria. He has received several international awards including the Japan Society for the Promotion of Science (JSPS) award. He is a UNU Fellow and a World Bank scholar.
Adi has consulted for the World Bank, UNCTAD, JIRCAS, JICA, and UNU. He is widely published and his current research interests include electricity market design, private-public partnerships, and the political economy of mega projects.
Testimonials
Upcoming Sessions and Contact
Afolabi Oyewuni
07086095794
aoyewunmi@lbs.edu.ng
Oluwakemi Mfon-Bassey
08086726686
omfon-bassey@lbs.edu.ng
Toba Olugosi
07080070553
tolugosi@lbs.edu.ng
