Beginners Guide To Data Analytics
This course introduces key data analytics skills. Learn to work with datasets, perform basic analysis, create visualizations, and understand simple reports.
Pre-requisite Program(s)
The following program(s) are pre-requisite to taking this program:
RWL Code
BLP-3859DST9235
Category
Data Analytics
Program Type
Paid Program
Program Fee
₦45,000.00
Publish Date
26/04/2025
Language
8 Lessons |
10hrs:45min
1
This introductory lesson establishes Excel as a fundamental data analysis tool and provides essential orientation to the Excel environment. It covers navigation of the Excel interface including ribbons, cells, and the formula bar, along with basic file operations such as opening, saving, and importing various data formats including CSV and Excel files. The lesson introduces students to a sample dataset that will be used throughout the course for hands-on practice and skill development.
This lesson focuses on essential data preparation techniques within Excel, covering fundamental data organization and cleaning processes. It teaches sorting and filtering methods to organize data effectively, techniques for removing duplicate entries and handling blank cells, and the application of basic text functions such as TRIM, LEFT, RIGHT, and CONCATENATE for data cleaning purposes. The lesson also covers data type conversion processes, specifically transforming text data into numerical or date formats for proper analysis.
This lesson introduces the core computational capabilities of Excel through formulas and functions. It covers the fundamentals of formula creation and cell referencing, along with the application of essential functions including SUM, AVERAGE, COUNT, IF, and VLOOKUP for data analysis tasks. The lesson explores basic conditional logic implementation through nested IF statements and introduces the concept and practical application of named ranges for improved formula readability and management.
This lesson introduces advanced data analysis features in Excel, focusing on structured data organization and summarization techniques. It covers the creation and formatting of Excel tables for better data management, along with comprehensive instruction on PivotTables for summarizing and analyzing large datasets. The lesson includes PivotChart creation for visualizing PivotTable results, and explores data grouping techniques and the use of slicers for interactive filtering and data exploration.
This lesson focuses on data visualization techniques within Excel, covering the selection and creation of appropriate chart types for different data scenarios. It includes instruction on various chart formats such as column, bar, line, pie, and combo charts, along with comprehensive customization options including titles, labels, and axis formatting. The lesson covers advanced features like adding trendlines and data labels, and concludes with methods for exporting charts for use in presentations and reports.
This lesson marks the transition from Excel to Tableau, beginning with installation procedures for Tableau Public or Desktop. It provides a comprehensive overview of the Tableau interface and workspace, including navigation and basic functionality. The lesson covers data connection processes for Excel and CSV files, and introduces the fundamental Tableau concept of distinguishing between dimensions and measures, which is crucial for effective data visualization in the platform.
This lesson focuses on practical visualization creation within Tableau, covering the construction of fundamental chart types including bar charts, line charts, and pie charts. It teaches the implementation of interactive features such as filters, labels, and tooltips to enhance user experience, along with data sorting and aggregation techniques. The lesson concludes with best practices for selecting appropriate visual types based on data characteristics and analytical objectives.
This capstone lesson focuses on creating comprehensive analytical presentations through dashboard development and sharing mechanisms. It covers the integration of multiple visualization sheets into cohesive dashboards, along with the implementation of interactive elements such as filters, actions, and drop-down menus. The lesson includes formatting and layout best practices for professional dashboard design, and concludes with publishing options including Tableau Public sharing and PDF export capabilities.