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Home > Training > Big Data > Big Data Management Solutions for Architects Training

Big Data Management Solutions for Architects Training (Coming Soon)

Course#: WA2267

Many organizations are overwhelmed by the sheer volume of information they have to process in order to stay competitive.  Traditional database systems may become either prohibitively expensive to handle the exponential growth of data volumes or found unsuitable for the job.  Finding solutions to meet the challenges posed by  Big Data requires, among other things, understanding the value proposition of NoSQL systems and the Cloud as well new techniques of data processing.

Objectives

This intensive training course aids IT architects in building a solid use case for embracing NoSQL systems and Cloud-based solutions in the enterprise.

The course is supplemented by hands-on labs that help attendees reinforce their theoretical knowledge of the learned material.

Topics

  • NoSQL and Big Data Systems Overview
  • Applied Data Science and Business Analytics
  • Big Data Business Intelligence and Analytics
  • Enterprise Architecture Lessons Learned And Anti-Patterns
  • Adopting NoSQL
  • Cloud Layering
  • Cloud SLAs

Audience

IT Architects, Managers and Team Leads

Prerequisites

Participants should have background in enterprise information systems design

Duration

2 Days

Outline of WA2267 Big Data Management Solutions for Architects Training

CHAPTER 1. DEFINING BIG DATA

  •  Gartner's Definition of Big Data
  •  Challenges Posed by Big Data
  •  The Cloud and Big Data
  •  Transforming Data into Business Information
  •  Data-Driven Decision Making

CHAPTER 2. NOSQL AND BIG DATA SYSTEMS OVERVIEW

  •  Limitations of Relational Databases
  •  What are NoSQL (Not Only SQL) Databases?
  •  NoSQL Past and Present
  •  NoSQL Database Properties
  •  NoSQL Benefits
  •  NoSQL Database Storage Types
  •  The CAP Theorem
  •  Limitations of NoSQL Databases
  •  Big Data Sharding
  •  Sharding Example
  •  Cloud Solutions
  •  Amazon S3
  •  Amazon Storage SLAs
  •  Amazon Glacier
  •  Amazon S3 Security
  •  Data Lifecycle Management with Amazon S3
  •  Amazon S3 Cost Monitoring
  •  OpenStack
  •  OpenStack Object Store (Swift)
  •  Components of Swift
  •  Google BigTable
  •  BigTable Design
  •  Applications using BigTable
  •  Google App Engine
  •  Google App Engine Billing
  •  Google Cloud Storage
  •  Hadoop
  •  Hadoop's Core Components
  •  Hadoop Distributed File System
  •  Accessing HDFS
  •  HBase
  •  HBase design
  •  Cassandra
  •  MemcacheDB
  •  Neo4j
  •  MongoDB
  •  MongoDB Operational Intelligence
  •  MongoDB Use Cases

CHAPTER 3. APPLIED DATA SCIENCE AND BUSINESS ANALYTICS

  •  What is Data Science
  •  Data Science vs Business Analytics vs Data Mining
  •  Examples of Applied Data Science Projects
  •  Strategic Information Value of Data Science
  •  MapReduce Programming Model
  •  Contrasting SQL with MapReduce

CHAPTER 4. BIG DATA BUSINESS INTELLIGENCE AND ANALYTICS

  •  Traditional Data Mining Constraints
  •  NoSQL Data Querying and Processing
  •  The UnQL Specification
  •  Analyzing Big Data with Hadoop
  •  MapReduce with Hadoop
  •  Hadoop Streaming
  •  Making Things Simpler with Hadoop Pig Latin
  •  What is Hive?
  •  Interfacing with Hive
  •  Business analytics with Hive
  •  Data Mashups in R
  •  RHadoop (R + Hadoop)
  •  MongoDB Operational Intelligence
  •  MongoDB Use Cases
  •  MongoDB Query Language
  •  Amazon Elastic MapReduce
  •  Querying Big Data in Google App Engine

CHAPTER 5. BIG DATA REAL WORLD CASE STUDIES

  •  Hadoop @ Yahoo
  •  Yahoo for Hadoop
  •  Yahoo!!
  •  Big Data @ Facebook
  •  Hive @ Facebook
  •  Mailtrust (Rackspace's mail division)

CHAPTER 6. ENTERPRISE ARCHITECTURE (EA) VALUE PROPOSITION

  •  The Value of Alignment Between Business and Technology
  •  Strategic Needs for Architecture
  •  EA from Strategy to Technology
  •  Tactical EA: IT Yearly Planning
  •  Tactical EA: IT as an Investment Portfolio
  •  Operational Needs for Architecture

CHAPTER 7. ENTERPRISE ARCHITECTURE (EA) LESSONS LEARNED AND ANTI-PATTERNS

  •  Key EA Lessons Learned
  •  Three Critical Changes EA Must Make To Survive Hard Times
  •  Scott Ambler’s EA Anti-Patterns
  •  EA Anti-Patterns

CHAPTER 8. ADOPTING NoSQL

  •  Hype Cycle and Technology Adoption Model
  •  Barriers to Adoption
  •  Dismantling Barriers to Adoption
  •  Use Cases for NoSQL Database Systems
  •  Example Applications
  •  Industry trends
  •  Enterprise Big Data / NoSQL Offerings
  •  NoSQL Technology Adoption Action Plan

CHAPTER 9. CLOUD LAYERING

  •  Cloud Layering Overview
  •  Content Services
  •  Logic Services
  •  Orchestration in the Cloud
  •  Utility - Security Services
  •  Security Service Example
  •  Utility - Data Services
  •  Cloud Layering Examples

CHAPTER 10. CLOUD SLAs

  •  The Importance of Cloud SLAs
  •  What Belongs in a Cloud SLA?
  •  Minimal Cloud SLA
  •  Robust Cloud SLA
  •  Governing Cloud Service Quality
  •  Supporting Clouds
We regularly offer classes in these and other cities. Atlanta, Austin, Baltimore, Calgary, Chicago, Cleveland, Dallas, Denver, Detroit, Houston, Jacksonville, Miami, Montreal, New York City, Orlando, Ottawa, Philadelphia, Phoenix, Pittsburgh, Seattle, Toronto, Vancouver, Washington DC.
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