Greenplum Unified Analytics Platform (UAP) - Getting Started with Greenplum for Big Data Analytics - page 22

Chapter 2. GreenplumUnifiedAnalytics
Platform (UAP)
Now that we understand the context of data science and analytics, let us explore re-
quirements for a platform that helps implement analytics in an agile way. There are
many pieces to an analytics project that requires a unified or integrated platform as
opposed to a bunch of tools or frameworks.
This chapter elaborates on the architecture and application of Greenplum Unified
Analytics Platform ( UAP ) in Big Data analytics context. Greenplum UAP combines
the capabilities to process structured and unstructured data with a productivity engine
and a social network engine that cans the barriers between the data science teams.
The Greenplum UAP solution combines Greenplum Database (an MPP, shared noth-
ing, and analytics optimized relational database competing with data warehousing
solutions), HD (a Hadoop distribution with proprietary integration), Greenplum Chorus
(an analytics collaboration platform), Greenplum DCA (a flexible appliance for hosting
the Greenplum UAP), and administration tools for managing and monitoring platform
components. While this chapter introduces you to Unified Analytics Platform, Chapter
4 , Implementing Analytics with Greenplum UAP provides detailed step-by-step guid-
ance on how to use the components, and configure the environment for implementa-
tion.
The topics covered in this chapter are listed as follows:
• Need for a unified or integrated platform for Big Data analytics
• Core concepts of analytical data architecture:
• Data warehousing, OLTP versus OLAP
• Column-oriented databases
• Parallel versus distributed processing/computing
• Shared nothing data architecture and massive parallel processing
( MPP )
• Elastic scalability
• Data loading patterns: ETL versus ELT versus ETLT
• Greenplum UAP, composed of: