CON7183

Copyright © 2014 Oracle and/or its affiliates. All rights reserved. |

Fast-Track Big Data Implementation with the Oracle Big Data Platform

Suraj Krishnan Director, Applications & Middleware, Oracle Advanced Customer Support Jegan Sundarapandian Technical Lead Oracle Advanced Customer Support

Oracle Confidential – Internal/Restricted/Highly Restricted


Today’s Agenda

1

2

3

4

Oracle ACS Introduction

Big Data Usage Patterns

Oracle Big Data Platform

Oracle Big Data Differentiator

Big Data Solution Architecture

Oracle Confidential – Internal/Restricted/Highly Restricted 3

5


Oracle Advanced Customer Support (ACS)

Oracle Confidential – Internal/Restricted/Highly Restricted


Oracle Advanced Customer Support (ACS) Who are we?

We Operate Globally as part of Oracle Customer Support Services

We Bring Expertise and Experience across the Complete Oracle Stack

ACS Works Closely with Oracle Development to Enhance Supportability

Our #1 Focus is Customer Success

5

#1

Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 6

Oracle Advanced Customer Support What do we do?

Plan & Design

Build & Deploy

Support & Maintain

Optimize & Modernize

Supportability at Every Step of your Lifecycle


Big Data Usage Patterns



Sample Big Data Industry Use Cases

Challenged by Data Volume, Velocity, and Variety

COMMUNICATIONS Location-based advertising

EDUCATION & RESEARCH Experiment sensor analysis

CONSUMER PACKAGED GOODS Sentiment analysis of what is the recent trend, problems

FINANCIAL SERVICES Risk & portfolio analysis New products

AUTOMOTIVE Auto sensors reporting location, problems

MEDIA/ ENTERTAINMENT Viewers / advertising effectiveness

HEALTH CARE Patient sensors, monitoring, EHRs Quality of care

LIFE SCIENCES Clinical trials Genomics

HIGH TECHNOLOGY / INDUSTRIAL MFG. Mfg. quality Warranty analysis

ON-LINE SERVICES / SOCIAL MEDIA People & career matching Website optimization

OIL & GAS Drilling exploration sensor analysis

RETAIL Consumer sentiment Optimized marketing

LAW ENFORCEMENT & DEFENSE Threat analysis—social media monitoring, photo analysis

TRAVEL & TRANSPORTATION Sensor analysis for optimal traffic flows Customer sentiment

UTILITIES Smart Meter analysis for network capacity


Common Big Data Use Cases, Why should you care ?

How can banks better understand customers and markets

Why do companies lose customers?

How can companies predict customer preferences?

How can companies increase campaign efficiency?

How to retailers target promotions guaranteed to make you buy ?

How can organizations use machine generated data to identify potential trouble ?

How can companies detect threats and fraudulent activity?

What can you do with new data



Bridging Business and Data

Business

Data Analytics

• Value Proposition • Goals • Communicate

Results

• Techniques • Interpretation • Model

Requirements

• Integration • Manipulation • Quality

Assurance


The Big Data Divide ETL/ELT

Biz Txn

Data

Man

ag

em

en

t

Secu

rity

, G

ove

rnan

ce

Advanced

Analytics

Visual

Discovery

Master &

Ref Data

Stru

ctu

red

Distributed

File System

EPM / BI App

Reporting &

Dashboards

MapReduce

Solutions

CDC

Real-Time

DB Rep

Data Marts

ODS

Machine

Generated

Social

Media

Text, Image

Video, Audio

Key-Value Data Store

Un

stru

ctu

red

Se

mi-

st

ruct

ure

d

Custom Code

Sandboxes

DBMS (OLTP)

Data Warehouse


Business Value from Big Data

Tap into diverse data sets

Find and monetize unknown relationships

Better data-driven business decisions

Process Optimization, Grow Revenue, New Business Models


Three Common Myths of Big Data

I can build my own Big Data infrastructure easily.


Hadoop IS Big Data Big data is not mission-critical.

Big Data will be driving the strategic business decisions of

every organization in the future. So it is absolutely

mission critical.

The inexpensive infrastructure myth will not work for most companies. If you are looking at bigdata

from a mission-critical perspective, it makes

enormous sense to only use “purpose built” hardware.

Hadoop is just part of the larger

puzzle, and connecting other data sources and tools to Hadoop

carries hidden costs on the human, software, networking, and

hardware fronts

* Source: ESG: Getting Real About Big Data: Build Versus Buy


Big Data = Just Hadoop


Run the Business Integrate existing systems

Support mission-critical tasks

Protect existing expenditures

Insure skills relevance

Relational Hadoop

Change the Business

Disrupt competitors

Disintermediate supply chains

Leverage new paradigms

Exploit new analyses

NoSQL

Scale the Business

Serve faster

Meet mobile challenges

Scale-out economically

NoSQL + Relational + Hadoop + ….


Oracle Big Data Platform



How Oracle Defines Big Data Technology

Big Data Applications

Business Analytics

Big Data Platform

Data Warehouse Data Reservoir +

Discovery Biz Intelligence +

by Industry & LoB


Stream Acquire – Organize – Analyze

Oracle BI Foundation Suite

Oracle Real-Time Decisions

Endeca Information Discovery

Decide

Oracle Event Processing Oracle Big Data

Connectors

Oracle Data Integrator

Oracle Advanced Analytics

Oracle

Database

Oracle Spatial & Graph

Apache Flume

Oracle GoldenGate

Oracle NoSQL

Database

Cloudera Hadoop

Oracle R

Distribution

Oracle Big Data Approach – Product View


Big Data Appliance X4-2

Sun Oracle X4-2L Servers with per server: 2 * 8 Core Intel Xeon E5 Processors

64 GB Memory

48TB Disk space

Integrated Software: Oracle Linux

Oracle Java VM

Cloudera Distribution of Apache Hadoop (CDH) + Options

Cloudera Manager

Oracle R Distribution

Oracle NoSQL Database


Big Data Appliance X4-2

X4-2L Servers (2 x 8 Xeon E5-2650 V2)

InfiniBand Connectivity

12 * 4TB SAS HC Disks

64GB Memory (expandable per node)

InfiniBand Switches 2 Gateway Switches

1 Spine Switch

Cisco Management Switch


Oracle Big Data Platform Advantage



Oracle Platform Advantage

Oracle’s advantage is focused on RDBMS + Hadoop + NoSQL .

SQL engine is more than data access. It is all of the options that can be deployed on top of the engine

Security

Advanced Analytics



Oracle Big Data SQL – A New Architecture

Powerful, high-performance SQL on Hadoop

Full Oracle SQL capabilities on Hadoop

SQL query processing local to Hadoop nodes

Simple data integration of Hadoop and Oracle Database Single SQL point-of-entry to access all data

Scalable joins between Hadoop and RDBMS data

Optimized hardware

High-speed Infiniband network between Hadoop and Exadata


Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 24

Use Existing SQL Skills on Native Hadoop Data – Big Data Without Any Expensive New Hires

CREATE TABLE web_logs

(click VARCHAR2(4000))

ORGANIZATION EXTERNAL

( TYPE ORACLE_HIVE

DEFAULT DIRECTORY Dir1

ACCESS PARAMETERS

(

com.oracle.bigdata.tablename logs

com.oracle.bigdata.cluster mycluster)

)

REJECT LIMIT UNLIMITED

New set of properties

ORACLE_HIVE and ORACLE_HDFS access drivers

Identify a Hadoop cluster, data source, column mapping, error handling, overflow handling, logging

New table metadata passed from Oracle DDL to Hadoop readers at query execution

Architected for extensibility StorageHandler capability enables future support

for other data sources

Examples: MongoDB, HBase, Oracle NoSQL DB


Big Data Solution Architecture



Big Data Solution Architecture: Step 1 Sources

Where data comes from?

Logs, Sensors,

Network Collecting Stations

Social Media DW Data

ERP, CRM, HCM, Misc Data


Big Data Solution Architecture: Step 2 If it’s Fast Data it can’t wait

Filter and Correlate

Event Processing predefines rules to filter and correlate data integrated with Coherence and NoSQL

Move Golden Gate captures

immediately and moves information.

Act Real-Time Decisions, together with BPM and BAM supports automated decisions and monitoring


Big Data Solution Architecture: Step 3 Start the Data Reservoir: Data First

• Acquires any data (store it in Hadoop or NoSQL) • Cost effective way to store historical data that hadn’t historical archive (eg. Fast Data) • Could be a part of the Enterprise/Logical DW

OR OR

BDA


Big Data Solution Architecture: Step 4 The Data Warehouse Enrichment: Model First

Push (some) Data from Reservoir + ERPs Detach Source Data Model from Warehouse Data Model using transformation flows Use an Industry Warehouse Data Model as a starting point

ODI

AIRLINES RETAIL

Industry Data Models


Big Data Solution Architecture: Step 5 Advanced Analytics: The Data Science Practice

Use in-database Out-of-the-Box Models

Have your Data Scientists create their own models

Complex Data Types and Data Processing

DATA MINING ENTERPRISE R

Advanced Analytics OLAP SPATIAL & GRAPH

TEXT MINING MAPREDUCE


Big Data Solution Architecture: Step 6 Rapid Sandbox Deployment with Endeca


What’s Next ? - Try Big Data Lite VM 4.0

Load your own data into the VM Use the Oracle MoviePlex demo data that's provided.

•Oracle Database 12c Release 1 Enterprise Edition (12.1.0.2) - including Oracle Big Data SQL-enabled external tables •Cloudera Distribution including Apache Hadoop (CDH5.1.2), Cloudera Manager (5.1.2) • Oracle Big Data Connectors 4.0 • Oracle NoSQL Database Enterprise Edition 12cR1 (3.0.14) • Oracle JDeveloper 12c (12.1.3) • Oracle SQL Developer and Data Modeler 4.0.3 • Oracle Data Integrator 12cR1 (12.1.3) • Oracle GoldenGate 12c • Oracle R Distribution 3.1.1 • Oracle Perfect Balance 2.2

CON7183

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