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Big Data Boot Camp


2 Days
Classroom Session   |  
2 Days
Live Online

IIBA (CDU)

ASPE is an IIBA Endorsed Education Provider of business analysis training. Select Project Delivery courses offer IIBA continuing development units (CDU) in accordance with IIBA standards.

NASBA (CPE)

NASBA continuing professional education credits (CPE) assist Certified Public Accountants in reaching their continuing education requirements.

PMI (PDU)

Select courses offer Leadership (PDU-L), Strategic (PDU-S) and Technical PMI professional development units that vary according to certification. Technical PDUs are available in the following types: ACP, PBA, PfMP, PMP/PgMP, RMP, and SP.

NASBA
NASBA
17.00 CPEs
PMI
PMP/PgMP
14.00 T-PDUs

Expertise Level: Intermediate
Certification
Classroom Registration Fees
Individual:
$1795.00
Group Rate:
$1595.00
(per registrant, 2 or more)
GSA Individual:
$1310.35
Live Online Registration
Live Online:
$1795.00
Private Onsite Package

The course can be tailored to your needs for delivery at your location. Private, onsite training is designed as a flexible group training option.

Training for 8 or more starting at: $8000.00

Learn More About Enterprise Team Training

Overview

This big data training 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.

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.

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
Upcoming Dates and Locations
Guaranteed To Run
Aug 9, 2017 – Aug 11, 2017    10:30am – 5:30pm Live Online
10:30am – 5:30pm
Register
Aug 24, 2017 – Aug 25, 2017    8:30am – 4:30pm San Diego, California

San Diego Training and Conference Center
350 Tenth Avenue
Suite 950
San Diego, CA 92101
United States

Register
Sep 14, 2017 – Sep 15, 2017    8:30am – 4:30pm Live Online
8:30am – 4:30pm
Register
Sep 14, 2017 – Sep 15, 2017    8:30am – 4:30pm Columbia, Maryland

System Source, Inc.
10480 Little Patuxent Pkwy
Suite 700
Columbia, MD 21044
United States

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Sep 28, 2017 – Sep 29, 2017    8:30am – 4:30pm Omaha, Nebraska

Doubletree Hotel & Executive Meeting Center
1616 Dodge Street

Omaha, NE 68102
United States

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Oct 12, 2017 – Oct 13, 2017    8:30am – 4:30pm Houston, Texas

CTREC-Hilton Training Academy
6200 Savoy Dr
Ste 1000
Houston, TX 77036
United States

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Oct 26, 2017 – Oct 27, 2017    8:30am – 4:30pm Seattle, Washington

Allied Business Systems - Computer Classrooms
10604 NE 38th Place, Suite 118
Yarrow Bay Office Park-1 North
Kirkland, WA 98033
United States

Register
Oct 26, 2017 – Oct 27, 2017    11:30am – 7:30pm Live Online
11:30am – 7:30pm
Register
Nov 8, 2017 – Nov 10, 2017    12:00pm – 4:30pm Live Online
12:00pm – 4:30pm
Register
Nov 9, 2017 – Nov 10, 2017    8:30am – 4:30pm Chicago, Illinois

Microtek Chicago
230 W. Monroe
Suite 900
Chicago, IL 60606
United States

Register
Nov 16, 2017 – Nov 17, 2017    8:30am – 4:30pm San Francisco, California

Learn IT
33 New Montgomery St.
Suite 300
San Francisco, CA 94105
United States

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Dec 7, 2017 – Dec 8, 2017    8:30am – 4:30pm Jacksonville, Florida

Holiday Inn Baymeadows
11083 Nurseryfields Drive

Jacksonville, FL 32256
United States

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Dec 14, 2017 – Dec 15, 2017    8:30am – 4:30pm Portland, Oregon

Kinetic Technology Solutions
1001 SW Fifth Avenue
Suite 305, Congress Center Bldg.
Portland, OR 97204
United States

Register
Dec 14, 2017 – Dec 15, 2017    11:30am – 7:30pm Live Online
11:30am – 7:30pm
Register
Course Outline

1. Introduction to Big Data

  • Big Data - beyond the obvious trends
    • Technologies involved
    • Business drivers
    • Implications for enterprise computing
  • Exponentially increasing data
    • ERP Data
    • CRM Data
    • Web Data
    • Big Data
  • Big data sources
    • Sensors
    • Social
    • Geospatial
    • Video
    • Machine to machine
    • Others
  • Data warehousing, business intelligence, analytics, predictive statistics, data science

 

2. Survey of Big Data technologies

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

 

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?

 

4. Introduction to MapReduce

  • What is MapReduce?
  • Why do you need MapReduce?
  • Using Mapreduce with Java and Ruby

Lab: How to use MapReduce in Hadoop?

 

5. Introduction to Yarn

  • What is Yarn?
  • What are the advantages of using Yarn over classical MapReduce?
  • Using Yarn with Java and Ruby

Lab: How to use Yarn within Hadoop?

 

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?
  • HDFS and reliability?
  • Does it offer support for compressions, checksums and data integrity?

Lab: Overview of HDFS commands

 

7. Data Transformation 

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

Lab: Hands on activities with Pig

 

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

 

9. Loading data into Hadoop

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

Lab: Hands on activities with Sqoop

 

10. Automating workflows in Hadoop

  • Benefits of Automation
  • What is oozie?
  • Automatically running workflows
  • Setting up workflow triggers

Lab: Demonstration of oozie

 

11. Exploring opportunities in your own organization

  • Framing scenarios
  • Understanding how to ask questions
  • Tying possibilities to your own business drivers
  • Common opportunities
  • Real world examples

 

Hands-on Exercises

You'll experience "in-the-trenches" practice built around actual big data implementations. You'll learn to avoid pitfalls and do it right the first time. Your instructor will help you map the tools and techniques you learn in this class to your own business, so they can be applied in your own organization immediately after the class.

 

How to use MapReduce in Hadoop?

  • How does it work from languages like Java?
  • How does it work with languages like Ruby?

 

How to use Yarn within Hadoop?

  • How does it work from languages like Java?
  • How does it work with languages like Ruby?

 

Overview of HDFS commands

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

 

Hands-on activities with Pig

  • Joining Data
  • Filtering Data
  • Storing and Loading Data

 

Hands-on activities with Hive/HCatalog

  • Storing and Loading Data
  • Select expressions
  • Hive vs SQL

 

Hands-on activities with Sqoop

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

 

Demonstration of Oozie

  • Creating a workflow
  • Running a workflow automatically at regular intervals
  • Running a workflow automatically when some events are triggered
Who should attend

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
Pre-Requisites

No prior knowledge of big data and/or Hadoop is required for this class. Some prior programming experience is a plus for this class, but not necessary.

Yes, this course looks perfect for my needs!

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