Data tells stories, solves problems and is the brain behind business. As a result, big data has created an overwhelming need for employers to have teams who can sift through data, make sense of it, and utilise it to support the customer experience, sales enablement, and strategic decision-making.
As a data analyst, you will have the power to increase efficiency and improve a companyÂÂ’s performance by learning to read data patterns. Work with complex datasets by advancing your programming skills, and use these skills for data manipulation, analysis and exploration.
The ALX Data Analytics Programme prepares you for a lucrative, in-demand global career as a data analyst.
What Careers Will The Programme Prepare Me For?
Over the duration of this online short course, youÂÂ’ll work your way through the following modules:
Module 1 Fundamentals of Data-Driven Decision-Making
Learn the key concepts and principles of data analysis, and how it can be used to drive business decision-making.
Module 2 Research Questions for Data Analysis
Explore the different types of data analysis, and the research questions that can be answered using these data analysis techniques.
Module 3 Organising Data in Microsoft Excel
Learn the basic functions and formulas for sorting, aggregating, and managing data for analysis in Microsoft Excel.
Module 4 Statistical Analysis Using Microsoft Excel
Learn how to conduct a statistical analysis in Microsoft Excel using several statistical methods and operations.
Module 5 Interpretation of Outcomes
Learn how to interpret statistical findings and draw meaningful conclusions from data related to a variety of business needs.
Module 6 Data Presentation and Visualisation
Discover how to create informative graphs and charts, and how to write impactful reports to guide business decision-making.
Module 7 Introduction to Databases and SQL
Study the fundamental constructs of SQL and relational databases, and understand the opportunities and challenges of working with databases.
Module 8 Looking Towards the Future
Critically reflect on the research process, explore other data analysis tools, and the future of data analysis.
GENERAL NOTES