About the course
Today’s highly connected, digitized economy runs on data — critical business and customer data can help organisations make better decisions and gain competitive advantage. However, there is a growing communication disconnect between data professionals and the rest of the organisation including business decision makers.
While data professionals tend to focus on the technical complexity and/or robustness of their analyses – non-data professionals are unable to contextualise these insights due to their technical nature. As a result, these insights tend to create more confusion as opposed to understanding the recommended next steps to improve business outcomes organisational strategy.
This course aims to deep understanding from start-to-finish of the processes that will enable participants to gain a strong understanding of the fundamentals in data analytics and business insights. Ultimately, providing individuals within a company a solid base of working with data in today’s digital economy.
Course content
Day 1
Module 1: Data Analytics 101
In this module, we will introduce participants to the key metrics and dimensions that are commonly measured by industry practitioners. We will also explore the pros and challenges associated with using these data points and recommended hacks for navigating them.
1. Chapter 1A: Descriptive Analytics
a. Explore different types of data and how it can be visualised, ultimately helping you leverage your findings and strengthen your decision making.
2. Chapter 1B: Predictive Analytics
a. Learn the predictive use cases of data after it is collected and interpreted. You will learn to utilise Google Analytics’ out of the box Predictive Analytics feature to predict customers’ propensity to purchase or churn in the near future.
3. Chapter 1C: Prescriptive Analytics
a. Formulate concrete business recommendations based on how your data trends against targets. These recommendations can be directed toward marketing, sales and other business functions
Practical Exercise #1: Analytics Dashboard Individual Task
Through a guided hands-on session including step-step notes build a report on Google Data Studio that visualises
Module 2: Business Outcomes 101
In this topic, we will discuss the common business indicators adopted by decision makers to track financial health, ROI and other indicators in order to assess and determine the recommended next steps for the business
1. Chapter 2A: Application of Analytics for Business
o Use your learning from the best practices of top data-driven firms to determine the best way to put data to work in your own company or business.
2. Chapter 2B: Customer Behaviour Indicators
o Identify and interpret business indicators for tracking customer behaviour to make better decisions.
3. Chapter 2C: Seasonal Indicators
o Identify and interpret business indicators for tracking seasonality and industry trends to make better decisions.
Practical Exercise #2: Business Indicators Individual Task
Formulate key performance indicators for measuring customer and industry outcomes for Bank ABC.
Day 2
Module 3: Translating technical results to business-friendly language
In this topic, participants will be introduced to and receive hands-on exposure on techniques for adapting technical data to non-technical audiences to increase clarity and value of the data and associated recommendations being communicated.
1. Chapter 3A: Creating organisational value via data analytics
a. Identify strategic, managerial and/or organisational problems related to analytics in your organisation or industry.
b. Assess your organisation’s level of data analytical maturity.
c. Articulate a plan for generating organisational value through improved analytical maturity.
2. Chapter 3B: Uncover data to substantiate business goals
a. Identify high-value data analytics problems and use cases with your organisation.
b. Leverage existing and/or untapped data sources for your organisation.
c. Evaluate your organisation’s data quality
d. Identify data visualisations relevant to your organizational needs and/or analytics goals
3. Chapter 3C: Articulate Value and Risks of Business Decisions
a. Articulate differences between descriptive, predictive & prescriptive approaches
b. Identify data analytics problems relevant to your organisation
c. Identify suitable cause and effect variables as well as confounding factors that could bias results
d. Learn about key communication techniques to inform decision makers on the relationships between key business predictors and business outcomes
Practical Exercise #3: End-End Data Analytics Group Task
Participants will split into teams to work on a simple business scenario where they will be tasked with extracting online store performance data from Google Analytics, translating the results into business insights and making a presentation on the recommended next steps to improve business outcomes.
Kishan
Kishan is the founder of a data analytics company focused on helping organisations leverage data to inform, persuade and effect better business outcomes. He was previously the regional head of Datalicious where he managed business growth and day-day operations, developing data-driven audience solutions for customers that increased e-commerce conversion rates by 200% and reduced paid advertising costs by 30%. Kishan is also a digital strategist with 10+ years of experience building teams from ground up…
