Introduction to Big Data and NoSQL Training

This Introduction to Big Data and NoSQL Training training class provides an introduction to Big Data as well as NoSQL (Not Only SQL) database systems. The fundamental concepts of and ideas behind Big Data / NoSQL technologies are methodically explored and many buzzwords demystified. The course is supplemented by hands-on labs that help attendees reinforce their theoretical knowledge of the subject.

This course is intended for a general audience including business and technology team leadership.


Public Classes: Delivered live online via WebEx and guaranteed to run . Join from anywhere!

Private Classes: Delivered at your offices , or any other location of your choice.

Course Topics
  1. Learn to define Big Data.
  2. Gain an overview of Big Data Stores.
  3. Learn NoSQL.
  4. Learn about Big Data Business Intelligence and Analytics.
  5. Learn via real-world case studies.
  6. Learn how to adopt NoSQL.
  1. Introduction to NoSQL Systems
    1. Gartner's Definition of Big Data
    2. The V
    3. 3
    4. Properties
    5. Limitations of Relational Databases
    6. Limitations of Relational Databases (Cont'd)
    7. What are NoSQL (Not Only SQL) Databases?
    8. What are NoSQL Databases?
    9. The Past and Present of the NoSQL World
    10. NoSQL Database Properties
    11. NoSQL Benefits
    12. Use Cases for NoSQL Database Systems
    13. NoSQL Database Storage Types
    14. The CAP Theorem
    15. Mechanisms to Guarantee a Single CAP Property
    16. NoSQL Systems CAP Triangle
    17. Limitations of NoSQL Databases
    18. Mix-and-Match Approach
    19. Big Data Sharding
    20. Sharding Example
    21. Google BigTable
    22. BigTable-based Applications
    23. BigTable Design
    24. Barriers to Adoption
    25. Dismantling Barriers to Adoption
    26. Industry trends
    27. NoSQL Technology Adoption Action Plan
    28. Quiz
    29. Quiz Answers
    30. Summary
  2. Introduction to Hadoop
    1. The Client – Server Processing Pattern
    2. Apache Hadoop
    3. Apache Hadoop Logo
    4. Typical Hadoop Applications
    5. Hadoop Clusters
    6. Hadoop Distributions
    7. Hadoop's Main Components
    8. Hadoop Distributed File System (HDFS)
    9. HDFS Considerations
    10. Data Blocks
    11. HDFS NameNode Directory Diagram
    12. HDFS Balancing
    13. Accessing HDFS
    14. Examples of HDFS Commands
    15. Other Supported File Systems
    16. YARN
    17. Hadoop-based Systems for Data Analysis
    18. MapReduce
    19. Similarity with SQL Aggregation Operations
    20. MapReduce Word Count Example
    21. Distributed Computing Economics
    22. Discussion: Divide and Conquer
    23. Apache Pig
    24. Pig Latin
    25. Running Pig
    26. Pig Latin Script Example
    27. What is Hive?
    28. Hive's Value Proposition
    29. Who uses Hive?
    30. What Hive Does Not Have
    31. HiveQL
    32. Working with Hive Tables
    33. Summary
  3. Apache HBase
    1. What is HBase?
    2. HBase Design
    3. HBase Master (HMaster)
    4. Sparse Data Sets
    5. Regions and Region Servers
    6. HBase Features
    7. HBase High Availability
    8. The Write-Ahead Log (WAL) and MemStore
    9. HBase vs RDBS
    10. HBase vs RDBS (Cont'd)
    11. Interfacing with HBase
    12. HBase Thrift and REST Gateway
    13. HBase Table Design
    14. Column Families
    15. A Cell's Value Versioning
    16. Timestamps
    17. Accessing Cells
    18. HBase Table Design Digest
    19. The Conceptual View of an HBase Table
    20. HBase Compaction
    21. Loading Data in HBase
    22. Column Families Notes
    23. Cardinality of Column Families
    24. Hotspotting
    25. Rowkey Design Notes
    26. Security
    27. HBase Shell
    28. HBase Shell Command Groups
    29. Creating and Populating a Table Using HBase Shell
    30. Getting a Cell's Value
    31. Counting Rows in an HBase Table
    32. HBase Java Client
    33. HBase Scanners
    34. The Scan Class
    35. The KeyValue Class
    36. The Result Class
    37. Getting Versions of Cell Values Example
    38. The Cell Interface
    39. HBase Java Client Example
    40. Scanning the Table Rows
    41. Dropping a Table
    42. The Bytes Utility Class
    43. Table Schema Main Rules to Follow
    44. Good Use Cases for HBase
    45. Not Good Use Cases for HBase
    46. Business Continuity Caveats
    47. Summary
  4. Apache Cassandra
    1. What is Apache Cassandra?
    2. Main Features
    3. Peer-to-Peer (No Master)
    4. Wide Column Store NoSQL Databases
    5. Cassandra Model vs Relational Model
    6. Column Families
    7. Columns
    8. Simplified Data Model
    9. Data Model
    10. The Cap Placement
    11. CQL
    12. CQL Simple Examples
    13. The Update Statement
    14. Update Caveats
    15. Update Statement with TTL and TIMESTAMP Examples
    16. Collections
    17. Example of Using a Set Collection
    18. Using the List Collection
    19. Data Replication
    20. Visualizing Data Replication
    21. The Write Path
    22. Sequential Data Storage Engine
    23. Java Client Code Example
    24. Data Distribution
    25. Native Aggregate Functions
    26. Creating UDFs
    27. HBase vs Apache Cassandra
    28. Cassandra vs MongoDB
    29. Security
    30. WAN-Wide High Availability
    31. Summary
Class Materials

Each student in our Live Online and our Onsite classes receives a comprehensive set of materials, including course notes and all the class examples.

Class Prerequisites

Experience in the following is required for this Hadoop class:

  • Basic programming skills, some knowledge of SQL.

Training for Yourself

$625.00 or 1 vouchers

Upcoming Live Online Classes

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Training for your Team

Length: 1 Day
  • Private Class for your Team
  • Online or On-location
  • Customizable
  • Expert Instructors

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