Program Brief:
This training program is to understand the main concepts about data analytics and big data and how to implement it using Microsoft Power BI and Hadoop, and also highlights machine learning, python programming language in relation to big data and data analytics.
Aims for this course:
- Transform your data from regular forms into strategically designed insights, where the light is spotted only on the data that matters.
- Empowering your reports with smart designs and eye-opening visuals.
- Closely highlights the most critical facts and figures that smoothly lead you to make the best decisions.
Learning Outcomes:
- Understand the fundamentals of big data and its significance.
- Gain a foundational knowledge of Hadoop.
- Recognize the role of these tools in big data analytics.
- Comprehend the structure and functionality of the Hadoop Distributed File System (HDFS).
- Explore NoSQL database and their use in data modeling.
- Apply effective data modeling techniques and best practices for analytics.
- Learn the processes for data processing using MapReduce programming model, and Apache Spark.
- Master the techniques for extracting insights from large datasets.
- Analyze and interpret extracted data for valuable insights.
Training Syllabus:
Duration: 4 hours
Description:
In this session, we will introduce you to Data Analytics and Business Intelligence, covering key concepts and tools used in the industry.
Topics:
- What is Business Intelligence
- Importance of Data Stages in Analytics
- Power BI vs. Advanced Excel for Analytics
Duration: 4 hours
Description:
This session will cover the basics of Hadoop and its role in big data analytics.
Topics:
- Overview of Big Data
- Introduction to Hadoop
- Hadoop Architecture
- Key Components of Hadoop
- Importance of Hadoop in Big Data Analytics
Duration: 4 hours
Description:
In this session, we will explore the Hadoop Distributed File System (HDFS) and NoSQL databases, focusing on their application in data modeling for analytics.
Topics:
- Understanding HDFS
- HDFS Architecture
- Data Storage and Replication in HDFS
- Difference Between SQL and NoSQL Querying Languages
- Overview of NoSQL Databases
- Types of NoSQL Databases
- Use Cases for NoSQL in Big Data
- Overview of Python Syntax and Features
- Practical Exercise Using NoSQL Database
Duration: 4 hours
Description:
This session will provide an overview of MapReduce, the process details, and its application in data processing. We will also cover the Word Count case and key enhancement features in YARN task scheduling.
Topics:
- Data Processing Overview
- Importance of Data Processing in Big Data Analytics
- Challenges in Data Processing
- Data Processing with MapReduce
- Word Count Practical Exercise Using MapReduce and Python Programming
Duration: 4 hours
Description:
In this session, we will focus on data processing using Apache Spark and learn how to load and process data with Spark.
Topics:
- Data Processing with Spark
- Spark Data Frames and Datasets
- Word Count Practical Exercise Using Spark and Python Programming
Duration: 4 hours
Description:
This session will focus on the analytics life cycle and the process of preparing data for analysis, including cleaning, transforming, and loading data into Power BI.
Topics:
- Introduction to Power BI for Analytics
- Exploring Power BI Features (Power BI Query)
- Importing Data from Excel, Databases, and Web
- Power BI Visuals
- Case Studies and Practical Examples on Power BI
Duration: 4 hours
Description:
In this session, we will cover data modeling and preparation for analysis using Power BI.
Topics:
- Data Preparation and Processing
- Data Modeling in Power BI
- Cleaning, Transforming, and Loading Data
- Exploring First Data Model
- Case Studies and Practical Examples on Power BI
Duration: 4 hours
Description:
This session will focus on visualizing and analyzing data in Power BI.
Topics:
- Using DAX for Calculations
- Data Visualization Techniques
- Creating Dynamic Dashboards
- Publishing Reports in Power BI Service
- Group Project Introduction: The project will be applied on Power BI using a dataset from Kaggle
Duration: 4 hours
Description:
In this session, we will cover advanced Excel techniques that will empower you to analyze and visualize data effectively.
Topics:
- Advanced Excel Functions (VLOOKUP, INDEX, MATCH, IF, AND, OR)
- Pivot Tables for Summarizing and Analyzing Large Datasets
- Data Visualization in Excel
- Practical Exercise: Create a Sample Dataset, Use VLOOKUP/INDEX/MATCH to Retrieve Data, Implement Nested IF Statements, Apply Pivot Tables and Data Visualizations
Duration: 4 hours
Description:
In the final session, participants will showcase their group projects, where they will analyze a dataset from Kaggle using Power BI. This collaborative project allows you to demonstrate your skills in data analysis, visualization, and communicating insights.
Objectives:
- Apply learned concepts in a real-world scenario using Power BI
- Enhance teamwork and presentation skills
- Critically evaluate data and derive actionable insights
Total Hours: 40 hours
Accreditation:
- Attendance Certification accredited by HUAWEI Academy MSA University and MSA Continuance Learning Center - CLC
Fees:
Standard
MSA Family
This program is officially endorsed by the faculty and serves as a mandatory practical training requirement for Engineering-Computer Science (CS) students seeking graduation eligibility.
Our team is always available to assist you.
MSA University - 26 July Mehwar Road intersection with Wahat Road, 6th of October
Email: clc@msa.edu.eg
Whatsapp: 01272803847
