Data Analysis Program

Introduction to Data Analytics program will give you insights into applying data and analytics principles in your business. You will gain an understanding of the complete data analytics lifecycle, from problem definition to solution deployment. Through various industry specific examples and case studies, you will learn how analytics, data visualization, and data science methodologies can be used to drive better business decisions.

Key Learning Objectives
✓ Understand how to solve analytical problems in real-world scenarios.
✓ Define effective objectives for analytics projects.
✓ Work with different types of data.
✓ Understand the importance of data visualization to help make more
✓ effective business decisions.
✓ Understand charts, graphs, and tools used for analytics and
✓ visualization and use them to derive meaningful insights.
✓ Create an analytics adoption framework.
✓ Identify upcoming trends in the data analytics field.

Program curriculum
✓ Lesson 1 – Program Introduction
✓ Lesson 2 – Data Analytics Overview
✓ Lesson 3 – Dealing with Different Types of Data
✓ Lesson 4 – Data Visualization for Decision making
✓ Lesson 5 – Data Analysis, Data Analytics, and Business Intelligence
✓ Lesson 6 – Data Analytics in Different Sectors
✓ Lesson 7 – Analytics Framework and Latest trends

This course gives you the information you need to successfully start working with SQL databases and make use of the database in your applications. Learn how to correctly structure your database, author efficient SQL statements and clauses, and manage your SQL database for scalable growth.

Key Learning Objectives
✓ Understand databases and relationships
✓ Use common query tools and work with SQL commands
✓ Understand transactions, creating tables and views
✓ Comprehend and execute stored procedures

Course curriculum
✓ Lesson 1- Fundamentals SQL Statements
✓ Lesson 2-Restore and Back-up
✓ Lesson 3-Selection Commands: Filtering
✓ Lesson 4-Selection Commands: Ordering
✓ Lesson 5-Alias
✓ Lesson 6-Aggregate Commands
✓ Lesson 7-Group By Commands
✓ Lesson 8-Conditional Statement
✓ Lesson 9-Joins
✓ Lesson 10-Subqueries
✓ Lesson 11-Views and Index
✓ Lesson 12-String Functions
✓ Lesson 13-Mathematical Functions
✓ Lesson 14-Date – Time Functions
✓ Lesson 15-Pattern (String) Matching
✓ Lesson 16-User Access Control Functions

Business Analytics with Excel training will boost your analytics career with powerful new Microsoft Excel skills. This business analytics training course will equip you with the concepts and hard skills required for a strong analytics career. You’ll learn the basic concepts of data analysis and statistics, helping promote data-driven decision making. Your new knowledge of this commonly used tool combined with official business analytics certification is guaranteed to ensure career success.

Key Learning Objectives
✓ Understand the meaning of business analytics and its importance in the industry.
✓ Grasp the fundamentals of Excel analytics functions and conditional formatting.
✓ Learn how to analyze with complex datasets using pivot tables and slicers.
✓ Solve stochastic and deterministic analytical problems using tools like scenario manager, solver, and goal seek.
✓ Apply statistical tools and concepts like moving average, hypothesis testing, ANOVA, and regression to data sets using Excel.
✓ Represent your findings using charts and dashboards.
✓ Get introduced to the latest Microsoft analytic and visualization tools, such as
Power BI.

Course curriculum
✓ Lesson 1- Introduction to Business Analytics
✓ Lesson 2- Formatting Conditional Formatting and Important Functions
✓ Lesson 3- Analyzing Data with Pivot Tables
✓ Lesson 4- Dashboarding
✓ Lesson 5- Business Analytics with Excel
✓ Lesson 6- Data Analysis Using Statistics
✓ Lesson 7- Power BI

This Tableau course helps you understand how to build visualizations, organize data, and design charts and dashboards to empower more meaningful business decisions. You’ll be exposed to the concepts of Data Visualization, different combo charts, and stories, working with filters, parameters, and sets, and building interactive dashboards.

Key Learning Objectives
✓ Become an expert on visualization techniques such as heat map, treemap, waterfall, Pareto.
✓ Understand metadata and its usage.
✓ Work with Filter, Parameters, and Sets.
✓ Master special field types and Tableau-generated fields and the process of creating and using parameters.
✓ Learn how to build charts, interactive dashboards, story interfaces, and how to share your work.
✓ Master the concepts of data blending, create data extracts and organize and format data.
✓ Master arithmetic, logical, table, and LOD calculations.

Course curriculum
✓ Lesson 01 – Getting Started with Tableau
✓ Lesson 02 – Core Tableau in Topics
✓ Lesson 03 – Creating Charts in Tableau
✓ Lesson 04 – Working with Metadata
✓ Lesson 05 – Filters in Tableau
✓ Lesson 06 – Applying Analytics to the worksheet
✓ Lesson 07 – Dashboard in Tableau
✓ Lesson 08 – Modifications to Data Connections
✓ Lesson 09 – Introduction to Level of Details in Tableau (LODS)

Microsoft Power BI is a suite of tools used to analyze your data and extract business insights by building interactive dashboards. This Power BI Training course will help you get the most out of Power BI, enabling you to solve business problems and improve operations. This Power BI Training course will help you master the development of dashboards from published reports, discover greater insight from your data with Quick Insights, and learn practical recipes for the various tasks that you can do with Microsoft Power BI—from gathering your data to analyzing it. This course also contains some handy recipes for troubleshooting various issues in Power BI.

Key Learning Objectives
✓ Create dashboards from published reports.
✓ Quickly generate visuals and dashboards with Quick Insights.
✓ Use natural language in the Q&A feature to quickly generate visuals for actionable insight.
✓ Create and manage data alerts.
✓ Get report layout and data visualization best practices.
✓ Understand which charts/graphs to use depending on the question being answered or the story being told.
✓ Use shapes to design, emphasize, and tell a story.
✓ See how to incorporate custom visuals into your reports and Dashboards.
✓ Share reports and dashboards, as well as the pros and cons of each.
✓ Complete a Power BI data analysis/visual project from start to finish.
✓ Improve team collaboration with Microsoft Teams.
✓ Know how to get and prepare your data for analysis and visualization.
✓ Learn how to create relationships between tables in your data model.
✓ Create calculated columns and measures using the DAX language.

Course curriculum
✓ Lesson 1 – Get and Prep Data like a Super Nerd
✓ Lesson 2 – Develop Your Data Nerd Prowess
✓ Lesson 3 – Developing Reports and Dashboards

Kickstart your learning of Python for data science with this introductory course and familiarize yourself with programming.

Key Learning Objectives
✓ Write your first Python program by implementing the concepts of variables, strings, functions, loops, and conditions.
✓ Understand the nuances of lists, sets, dictionaries, conditions and branching, objects, and classes.
✓ Work with data in Python, including reading and writing files, loading, working, and saving data with Pandas.

Course Curriculum:
✓ Lesson 1 – Python Basics
✓ Lesson 2 – Python Data Structures
✓ Lesson 3 – Python Programming Fundamentals
✓ Lesson 4 – Working with Data in Python
✓ Lesson 5 – Working with NumPy Arrays

Gain insight into the R programming language with this introductory course. An essential programming language for data analysis, R programming is a fundamental key to becoming a successful data science professional. In this course, you will learn how to write R code, learn about R’s data structures, and create your own functions. After the completion of this course, you will be fully able to begin your first data analysis.

Course curriculum
✓ Lesson 1 – R Basics
✓ Lesson 2 – Data Structures in R
✓ Lesson 3 – R Programming Fundamentals
✓ Lesson 4 – Working with Data in R
✓ Lesson 5 – Strings and Dates in R

Key Learning Objectives
✓ Learn about math, variables, strings, vectors, factors, and vector operations.
✓ Gain a fundamental knowledge of arrays and matrices, lists, and data frames.
✓ Get an understanding of conditions and loops, functions in R, objects, classes, and debugging.
✓ Learn how to accurately read text, CSV, and Excel files plus how to write and save data objects in R to a file.
✓ Understand and learn how to work on strings and dates in R.