Next class starting
February 6, 2017
Video Conference link
Will be sent upon your registration and payment
Training Session Details
There will be 8 online sessions, each session being of 2 hours. Every session will have presentation about theory, concepts and technology, followed by time with Hands-on Lab practice exercises.
February 6, 7, 9, 13,14, 16, 20, 21, 23
Times: 6:30 PM - 8:30 PM US Pacific Time
Each session will be recorded and the recordings will be shared after each session with students who have paid for the training.
Desired but not required - exposure to, working proficiency of BI, SQL, scripting, how to handle and manage data and databases, using Excel.
A Microsoft cloud Azure account will be provided to every student where they will install hortonworks hadoop on the cloud virtual machines. Students will carry out the hands-on lab exercises with instructor guidance.
Session 1: Big Data Basics
• An introduction to Big Data?
• Why is Big Data? Why now?
• The Three Dimensions of Big Data (Three Vs)
• Evolution of Big Data
• Big Data versus Traditional RDBMS Databases
• Big Data versus Traditional BI and Analytics
• Big Data versus Traditional Storage
• Key Challenges in Big Data adoption
• Benefits of adoption of Big Data
• Introduction to Big Data Technology Stack
• Apache Hadoop Framework
• Introduction to Microsoft HDInsight – Microsoft’s Big Data Service
• Creating Azure Storage Account
• Creating HDInsight Cluster
• Using services on HDInsight Cluster
Session 2: The Big Data Technology Stack
• Basics of Hadoop Distributed File System (HDFS)
• Basics of Hadoop Distributed Processing (Map Reduce Jobs)
• Loading files to Azure storage account
• Moving files across HDInsight Cluster
• Remote Access to Azure Storage Account and HDInsight Cluster
Session 3: Deep dive into Hadoop Storage System (HDFS) (1 Hour)
• Reading files with HDFS
• Writing files with HDFS
• Error Handling
• Accessing Hadoop configuration files using HDInsight Cluster
Session 4: Processing Big Data –MapReduce and YARN
• How MapReduce works
• Handling Common Errors
• Bottlenecks with MapReduce
• How YARN (MapReduceV2) works
• Difference between MR1 and MR2
• Error Handling
• Running a simple MapReduce application (word count)
• Running a custom MapReduce application (census data)
• Running MapReduce via PowerShell
• Running a MapReduce application using PowerShell
• Monitoring application status
Session 5: Big Data Development Framework
• Introduction to HIVE
• Introduction to PIG
• Loading the data into HIVE
• Submitting Pig jobs using HDInsight
• Submitting Pig jobs via PowerShell
Session 6: Big Data Integration and Management
• Big Data Integration using Polybase
• Big Data Management using Ambari
• Fetching HDInsight data into SQL
• Using Ambari for managing HDInsight cluster
Session 7: Big Data – BI and Reporting using Power BI
• Introduction to Power BI
• Usual workflow of Power BI
• Power BI Ecosystem
• Getting Data into Power BI
• Reports vs Dashboards
• Additional elements of Power BI Reports
• Fetching HDInsight Data into Power BI desktop
• Data Modelling using Power BI desktop
• Creating reports using Power BI desktop
Session 8: PowerBI.com services – Deep dive
• Power BI Dashboards
• Natural Language Query
• Power BI Workspaces – Personal and Group Workspaces
• Sharing using OneDrive for Business
• Publishing reports to Powerbi.com
• Sharing reports using OneDrive for Business
End-to-End Use Case Implementation- Lab Exercise
• Use case -Healthcare Analytics using Hadoop framework through Microsoft HDInsight and Power BI
Class Size: Maximum 22
1. Each student gets access to a login account on the cloud, Microsoft Azure, where they will be able to install Hadoop on a cloud virtual machine and have time to perform hands-on lab exercises with instructor guidance.There will be 2 experienced big data, hadoop instructors supporting the students throughout the class.
ADVANTAGE OF PURCHASING TRAINING TICKET:
1. Class recordings will be made available.
2. Post class support time.
3. Course material available.
4. Cloud account on Microsoft Azure with Hands-on lab exercises under the guidance of two experienced big data, hadoop instructors.
5. Career advancement and Job placement assistance.
1. 100% refund will be provided under the following circumstances:
- In case Omni212 cancels or reschedules the class.
- If the student cancels or raises a refund up to 48 hours before the start of course.
- No negative review is given without giving Omni212 the chance to remedy the situation within 15 days after the complaint was registered by the student.
2. 50% refund will be issued under the circumstance that:
- Student raises a refund request within 3 days after the first training session.
3. No refund will be provided under the following circumstances:
- Student raises a request more than 3 days after start of the course.
- Student registers for the course and does not attend the course for whatever reason.
- Once access to the course material on the cloud has been provided, no refund will be provided.
4. Refunds will be issued within 15 days once the request has been approved.