Data Science Overview | Technologies, Tools, and Roles in the Data-Driven Enterprise

Foundations

• Grids and Virtualization
• Service-Oriented Architecture
• Enterprise Service Bus
• Enterprise Message Bus
• The Cloud

The Hadoop Ecosystem

• HDFS: Hadoop Distributed File System
• Resource Negotiators: YARN, Mesos, and Spark; ZooKeeper
• Hadoop Map/Reduce
• Spark
• Hadoop Ecosystem Distributions: Cloudera, Hortonworks, OpenSource

Big Data, NOSQL, and ETL

• Big Data vs. RDBMS
• NOSQL: Not Only SQL
• Relational Databases: Oracle, MariaDB, DB/2, SQL Server, PostGreSQL
• Key/Value Databases: JBoss Infinispan, Terracotta, Dynamo, Voldemort
• Columnar Databases: Cassandra, HBase, BigTable
• Document Databases: MongoDB, CouchDB/CouchBase
• Graph Databases: Giraph, Neo4J, GraphX
• Apache Hive
• Common Data Formats
• Leveraging SQL and SQL variants

ETL: Exchange, Transform, Load

• Data Ingestion, Transformation, and Loading
• Exporting Data
• Sqoop, Flume, Informatica, and other tools

Enterprise Integration Patterns and Message Busses

• Enterprise Integration Patterns: Apache Camel and Spring Integration
• Enterprise Message Busses: Apache Kafka, ActiveMQ, and other tools

Developing in Hadoop Ecosystem

• Languages: R, Python, Java, Scala, Pig, and BPMN
• Libraries and Frameworks
• Development, Testing, and Deployment

Artificial Intelligence and Business Systems

• Artificial Intelligence: Myths, Legends, and Reality
• The Math
• Statistics
• Probability
• Clustering Algorithms, Mahout, MLLib, SciKit, and Madlib
• Business Rule Systems: Drools, JRules, Pegasus

The Team

• Agile Data Science
• NOSQL Data Architects and Administrators
• Developers
• Grid Administrators
• Business and Data Analysts
• Management
• Evolving your Team
• Growing your Infrastructure

Join an engaging learning environment, where you’ll explore:

• Foundations: Grids & Virtualization; SOA, ESB/EMB and the Cloud
• The Hadoop Ecosystem: HDFS, Resource Navigators, MapReduce, Spark, and Distributions
• Big Data, NOSQL, and ETL
• ETL: Exchange, Transform, Load
• Handling Data and a Survey of Useful tools
• Enterprise Integration Patterns and Message Busses
• Developing in Hadoop Ecosystem: R, Python, Java, Scala, Pig, and BPMN
• Artificial Intelligence and Business Systems
• Who’s on the Team? Roles and Functions in Data Science
• Growing your Infrastructure

This is a seminar-style course that combines engaging expert lectures, pertinent skills, tool demonstrations, and group discussions.

Attendees should have:

• Exposure to Enterprise Information Technology
• Familiarity with Relational Databases

Business Analysts, Data Analysts, Data Architects, Database Administrators, Network Administrators (Grid), Developers, Technical Manager, or anyone else in the data science realm who needs to have a baseline understanding of the core areas of modern Data Science technologies, practices, and tools.