Big Data Bootcamp

This 2 day instructor-led course will provide a technical overview of Apache Hadoop for project managers, business managers and data analysts. Students will understand the overall big data space, technologies involved and will get a detailed overview of Apache Hadoop. The course will expose students to real world use cases to comprehend the capabilities of Apache Hadoop. Students will also learn about YARN and HDFS and how to develop applications and analyze Big Data stored in Apache Hadoop using Apache Pig and Apache Hive. Each topic will provide hands on experience to the students.

At Course Completion

Students will have learned:

• Learn about the big data ecosystem
• Understand the benefits and ROI you can get from your existing data
• Learn about Hadoop and how it is transforming the workspace.
• Learn about MapReduce and Hadoop Distributed File system.
• Learn about using Hadoop to identify new business opportunities
• Learn about using Hadoop to improve data management processes.
• Learn about using Hadoop to clarify results
• Learn about using Hadoop to expand your data sources
• Learn about scaling your current workflow to handle more users and lower your overall performance cost.
• Learn about the various technologies that comprise the Hadoop ecosystem
• Learn how to write a simple map-reduce job from Java or your favorite programming language
• Learn how to use a very simple scripting language to transform your data.
• Learn how to use a SQL like declarative language to analyze large quantities of data.
• Learn how to connect your existing data warehouse to the Hadoop ecosystem
• Learn how to move your data to the Hadoop ecosystem
• Learn how to move the results of your data analysis to Business Intelligence Tools like Tableaux.
• Learn how to automate your workflow using oozie.
• Learn about polyglot persistence and identifying the right tool for the right job.
• Learn about future trends in Big data and technologies to keep an eye on.
• Discover tips and tricks behind successful Hadoop deployments

10 Features of This Class:

• Led by experienced Big Data and Hadoop consultants.
• Hands on Activities that will immerse you into the capabilities of the Hadoop ecosystem
• Assumes no prior background in Big data
• Material will be designed by a computer science professor using pedagogical techniques to help the student understand the material in an easier manner.
• Provides both foundational and practical knowledge that is essential for successful big data ventures.
• Fast paced introduction to get you up to speed with Big Data.
• Includes materials covered in most Hadoop certification exams
• Labs with practice sessions on a Hadoop cluster
• Will include insights learnt from experience on real projects
• Will include things to do and things not to do with big data projects

Every topic will have hands-on activities built in, to help the students get a better comprehension of the material being covered.

The course is developed and taught by certified Hadoop consultants who have a passion for teaching and help deliver value to various clients using Big Data and Hadoop technologies on a daily basis.

Lesson 1: Introduction to Big Data

• Big Data - a major business & technology trend in enterprise computing
• Exponentially increasing data from ERP data to CRM data to Web data to Big Data

• Big data sources - sensors, social, geospatial, video, others
• Data warehousing, business intelligence, analytics, predictive statistics, data science.

Lesson 2: Survey of Big Data technologies

• First generation RDBMS, ETL and BI systems
• Second generation systems - columnar databases with compression and MPP architectures, data warehousing appliances
• Streaming processing, statistical processing, data visualization
• Enterprise search
• NOSQL databases
• How do technologies like mongodb, MarkLogic, couchdb fit in?
• What is polyglot persistence?
• Apache Hadoop

Lesson 3: Introduction to Hadoop

• What is Hadoop? Who are the major vendors?
• A dive into the Hadoop Ecosystem
• Benefits of using Hadoop
• How to use Hadoop within your infrastructure?
• Where do we use Hadoop?
• Where do we look at options besides Hadoop?

Lesson 4: Introduction to MapReduce

• What is MapReduce?
• Why do you need MapReduce?

Lab:

• How to use MapReduce in Hadoop?
• How does it work from languages like Java?
• How does it work with languages like Ruby?

Lesson 5: Introduction to Yarn

• What is Yarn?
• What are the advantages of using Yarn over classical MapReduce?

Lab:

• How to use Yarn within Hadoop?
• How does it work from languages like Java?
• How does it work with languages like Ruby?

Lesson 6: Introduction to HDFS

• What is HDFS?
• Why do you need a distributed file system?
• How is a distributed file system different from a traditional file system?
• What is unique about HDFS when compared to other file systems?
• Is HDFS reliable?
• Does it offer support for compressions, checksums and data integrity?

Lab:

• Overview of HDFS commands
• Standard file system commands
• Moving data to and from HDFS

Lesson 7: Data Transformation

• Why do you need to transform data?
• What is Pig?
• Use cases for Pig

Lab:

• Hands on activities with Pig
• Joining Data
• Filtering Data
• Storing and Loading Data

Lesson 8: Structured Data Analysis?

• How do you handle structured data with Hadoop?
• What is Hive/HCatalog?
• Use cases for Hive/HCatalog

Lab:

• Hands on activities with Hive/HCatalog
• Storing and Loading Data
• Select expressions
• Hive vs SQL

Lesson 9: Loading data into Hadoop

• How do you move your existing data into Hadoop?
• What is Sqoop?

Lab:

• Hands on activities with Sqoop
• Running evaluation commands with Sqoop
• Importing data from relational databases
• Exporting data to relational databases

Lesson 10: Automating workflows in Hadoop

• Benefits of Automation
• What is oozie?

Lab:

• Demonstration of oozie
• Creating a workflow
• Running a workflow automatically at regular intervals
• Running a workflow automatically when some events are triggered

• Some prior programming experience is a plus
• No prior knowledge of big data or Hadoop is required

Anybody who is involved with databases, data analysis, wondering how to deal with the mountains of data (any where gigabytes of user/log data etc to petabytes will benefit from this program. This course is perfect for - Business Analysts, Software Engineers, Project Managers, Data Analysts, Business Customers, Team Leaders & System Analysts.