Data Analytics & Business Intelligence

Learn Excel, SQL, Python, Power BI, Tableau and PowerPoint
(with case studies)

includes

Exam PL-300: Microsoft Certified Data Analyst
MO-200: Excel 2019: Core Data Analysis, Manipulation, and Presentation
Exam 98-381: Programing in Python

Data Analytics and Business Intelligence
Training & Certification

Data analytics and business intelligence are two closely related fields that involve the use of data to inform business decision-making.

Data analytics refers to the process of examining and interpreting data to extract meaningful insights and information. This involves collecting, cleaning, and processing data, as well as applying statistical and analytical methods to identify patterns, trends, and relationships in the data.

Business intelligence, on the other hand, is the use of data and analytical tools to support business decision-making. This involves gathering and analyzing data from various sources to create reports, dashboards, and visualizations that provide insights into business performance, trends, and opportunities.

Both data analytics and business intelligence are essential for organizations looking to make data-driven decisions and improve their overall performance. By leveraging these tools, businesses can gain a better understanding of their customers, operations, and market trends, allowing them to optimize their strategies and stay ahead of the competition.

Earning a certification in data analytics and business intelligence can demonstrate your skills and knowledge to potential employers, and help you advance your career in these fields.

This training and certification master class puts together five important data analytics and visualization (Excel, SQL, Python, Tableau, and Power BI). Thus ensuring that whoever comes out of this course, is well-prepared for an exciting Data Analyst Career. This also comes with atleast 10 live projects.

Learning Options

Training & Certification fee

650,000 Naira

Course Learning Outcome

In this course, you will analyse and visualize data using Microsoft Excel, SQL, Python, Power BI and associated tools.

In the Excel course,

Perform data analysis fundamentals.
Visualize data with Excel.
Analyze data with formulas and functions.
Analyze data with PivotTables.
Present visual insights with dashboards in Excel.
Create geospatial visualization with Excel.
Perform statistical analysis.
Get and transform data.
Model and analyze data with Power Pivot.
Present insights with reports.

In the SQL course,

Use SQL to summarize and identify patterns in data.
Apply special SQL clauses and functions to generate descriptive statistics.
Use SQL queries and subqueries to prepare data for analysis
Perform advanced statistical calculations using the window function.
Analyze special data types in SQL, including geospatial data and time data.
Import and export data using a text file and PostgreSQL.
Debug queries that won’t run.
Optimize queries to improve their performance for faster results

In the Python course,

Set up Python and develop a simple application.
Declare and perform operations on data structures, including lists, ranges, tuples, dictionaries, and sets.
Declare and perform operations on simple data types, including strings, numbers, and dates.
Write conditional statements and loops.
Define and use functions, classes, and modules.
Manage files and directories through code.
Deal with exceptions.

In the PowerBI course,

Analyze data with self-service BI.
Connect to data sources.
Perform data cleaning, profiling, and shaping.
Visualize data with Power BI.
Enhance data analysis by adding and customizing visual elements.
Model data with calculations.
Create interactive visualizations.
Use advanced analysis techniques.
Enhance reports and dashboards.
Publish and share reports and dashboards.
Extend Power BI beyond the desktop.

COURSE OBJECTIVES

The chief aim of this data analytics and business intelligence program is to apply statistical analysis and technologies on data to find trends and solve problems by drawing from a range of disciplines such as programming, mathematics, and statistics — to perform analysis on data in an effort to describe, predict, and improve performance through leverage on a range of data management techniques such as data mining, data cleansing, data transformation and data modelling.

COURSE PRE-REQUISITES

This course is widely regarded as the A-Z of data analytics, hence little or no prior experience is required.

To ensure success, students will need to be familiar with using personal computers and should have experience using a keyboard and mouse.

Specific tasks the students should be able to perform include: opening and closing applications, navigating basic file structures, and managing files and folders.

You should have baseline skill using Microsoft Excel worksheets.