Oracle Big Data Appliance and Big Data SQL for advanced analytics

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

Big DataChanging the Way You Manage and Analyze Big Data

Jean-Pierre DijcksBig Data Product ManagementServer Technologies


Use Data

12%

Executives who feel they understand the impact data

will have on their organizations

Produce Data


From Storing Data to Monetizing Data

*Source : ‘Enterprise Architecture As Strategy: Creating a Foundation for Business Execution’ by J Ross, P. Weill, D. Robertson, HBS Press, 2006

StoringData

ManagingData

MonetizingData

DisparateData Marts

EnterpriseData Warehouse

Big Data Management System

StrategicBusiness

Value of IT

IT Budget

CostCenter

ProfitCenter

100%

84%92%

145%


Analytics 2.0

Analytics 3.0

Analytics 1.0

• Reporting with limited use of descriptive analytics

• Limited range of tabular data • Batch oriented analysis • Analysis bolted onto limited set

of business processes

• Firms “Competing on Analytics”• Extended analytics to larger and

less structured datasets• Emergence of Big Data into the

commercial world• Recognition of Data Science role

in commercial orgs.

• Platform for monetization• Deeper analysis & more data• Faster test-do-learn iterations• Different types of data & wider

business process coverage• Analysts focus on discovery and

driving business value• “Agile” with operational elements

incorporated into design patterns

Adapted from: Tom Davenport material – Harvard Business Review (2010)

The Path to Monetizing Big Data


ActionableEvents

Streaming Engine Data Reservoir Enterprise Data & Reporting

Discovery Lab

ActionableMetrics

ActionableData Sets

InputEvents

Execution

Innovation

Discovery Output

Data

Conceptual View

StructuredEnterprise Data


De PersgroepCreating a linked customer analytics system

Objectives Maximizing customer value Optimizing campaign cost through

Automation and Targeting

Solution Single, rich customer repository based on Big

Data Appliance and NG Data® Lily®

Analytics drive: subscriber management (up-sell/cross-sell, churn,

conservation) editorial use (article engagement, adapt content over

time)

- Toyota Global Vision

Customer Data Store

Digital, RDBMS, External

BDA

Mobile

Web

Subscribers

NG DataLily

Customer Analytics

Phase 1: Improved Data Quality Single View of all Customers improves

customer management

Benefits

Social

CustomerAnalytics & aggegated

data

Oracle Data Warehouse

Business Objects


GlobacomImprove Customer Information

Objectives Respond to customer queries in as close to real

time as possible Understand behavior, improve retention, and

increase cross-selling d services

Solution Capture and analyzie >1B CDR’s daily in Oracle Big

Data Appliance Integrate resulting data, using Oracle NoSQL Database

into online systems Leverage xDR Navigator from partner mCentric to

improve first call resolution ratesBDA

mCentric

Save over 35,000 call processing minutes per day

Analyze network events 40x faster

Benefits


US-based BankLowering Costs by Simplifying IT Infrastructure

Objectives Comply with regulations requiring more data

to support stress testing Reduce IT costs & streamline processing by

eliminating duplicate data stores

Solution Single, reliable BDA/Exadata-based ODS

supporting all downstream systems Landing zone & archival repository for both

structured & unstructured data Use Exadata as “19th” BDA node

- Toyota Global Vision

Operational Data StoreMainframe,

RDBMS, more

BDA Exadata

• Agile business model

• All data• De-normalized

& Partial-normalized

• Normalized• Aggregate data• EDW

Oracle Enterprise Manager

Oracle Data Integrator

Data Delivery

MasterS1

MasterS2

MasterSn

SOA/APICRMSOther

Faster access to 6x more data Lower costs, simplified architecture and fast

time to value

Benefits


Enterprise Class Big Data Capabilities

zBY INDUSTRY & LINE OF BUSINESS

BIG

DAT

A AP

PLIC

ATIO

NS

DISCOVERY

BUSI

NES

SAN

ALYT

ICS

BUSINESS ANALYTICS

DATA RESERVOIR

BIG

DAT

AM

ANAG

EMEN

T

DATA WAREHOUSE

SOU

RCES


Oracle Big Data Management System

SOU

RCES

Oracle Database

Oracle IndustryModels

Oracle Advanced Analytics

Oracle Spatial & Graph

Big Data Appliance

Cloudera Hadoop

Oracle NoSQL Database

Oracle R Advanced Analytics for Hadoop

Oracle R Distribution

Oracle Database

Oracle Advanced Security

Oracle Advanced Analytics

Oracle Spatial & Graph

Oracle Exadata

Oracle Big DataConnectors

Oracle DataIntegrator

Oracle Big Data SQL


Strengths of Both Systems

Tooling maturity

Stringent Non-Functionals

ACID transactions

Security

Variety of data formats

Data sparsity

ETL simplicity

Cost effectively store data

Ingestion rate

Straight Through Processing (STP)

0

5

Hadoop

RDBMS

• Hadoop is good at some things

• Databases are good at others• SQL is very important

Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 13

“The implementation of this Big Data solution will help CaixaBank remain at the forefront of innovation in the financial sector, delivering the best and most competitive services to our customers”– Juan Maria Nin, Chief Executive Officer, CaixaBank


Feedback Loop

Data Management

Big Data Platform

(Hadoop/NoSQL)

Relational Data Warehouse

(OCDM)

Analytic Apps

Customer Experience

Operations

Monetization

Adapters

ETL/ELT Adapters

Real-Time Adapters

ThirdParty

DataSources

Oracle Comms Apps (BSS/OSS)

Oracle Comms Ntwk Products (Tekelec

& Acme)

Other Oracle Apps (CRM, ERP, etc.)

Third Party Sources

Oracle Communications Data ModelReference Architecture

To Other Apps

Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | Oracle Confidential – Internal/Restricted/Highly Restricted

15

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– Balanced Configurations– No bottlenecks


Two Challenges

1. Make Hadoop easily consumable for customers

2. Enable Oracle SQL on All Data


Recap: Big Data Appliance OverviewBig 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• Oracle Big Data SQL*• Cloudera Distribution of Apache Hadoop – EDH Edition• Cloudera Manager• Oracle R Distribution• Oracle NoSQL Database

* Oracle Big Data SQL is separately licensed


Recap: Standard and Modular

Starter Rack is a fully cabled and configured for growth with 6 servers

In-Rack Expansion delivers 6 server modular expansion block

Full Rack delivers optimal blend of capacity and expansion options

Grow by adding rack – up to 18 racks without additional switches


Oracle Big Data Appliance

Engineered Systems Benefits

Lower TCO than DIY Hadoop Clusters

Faster Time to Value

Higher Performance out-of-box

Lower Management Overhead

Integrated and Comprehensive Security

Tight Integration with your Infrastructure


TCO Data Points: 18 servers (DL380 vs. X4-2L)

864TB Raw Storage 288 Cores 1152GB Total Memory

Cloudera Enterprise Subscription with all options

Subscription vs. Perpetual Equivalent Installation Cost Not calculated:

Soft Cost (people and time to value) Data integration licenses

Engineered Systems Benefits

Year 1 Year 2 Year 3 Year 4 Year 5$0

$200,000

$400,000

$600,000

$800,000

$1,000,000

$1,200,000

$1,400,000

Oracle BDAHP + ClouderaSavings

List Price Comparisons

Cum

ulati

ve C

ost a

nd S

avin

gs


Engineered Systems BenefitsBDA 3.0 DIY CDH 5.0

Management Console

Single Command Patching and Upgrade

Full Stack Patching and Upgrading

Automatic Cluster Re-Configuration

Security (AAA) out-of-box

Encryption out-of-box (network and at-rest)

InfiniBand + Optimizations

Stack Tuning (OS, Java, Hadoop)


What does it mean to engineer a BDA?

Linux Optimization

Java Configuration

Pre-Configured AAA security and Encryption

Pre-Configured Hadoop Settings

Ex: HDFS, Memory and MR Slots

Network Optimizations

Node Configurations (Roles and Growth)


Security Differentiators

Oracle Database BDA 2.5 DIY CDH 4.6

User Authentication

Row Level Access Controls

Monitoring and Auditing

Encryption at Rest

Network Encryption

Masking, Redaction etc.

Column Lvl Access Ctrl


BDA Security Overview

Authentication through Kerberos

Authorization through Apache Sentry

Auditing through Oracle Audit Vault

Encryption for Data-at-Rest

Network Encryption


Exadata+

Oracle Database

Big Data Appliance+

Hadoop & NoSQL

Embrace Innovation and Integrate

UnifyDevelopment languages

SecurityAdministration

SupportWorkload managementLifecycle management

Availability


Oracle Big Data Management System

One fast SQL query, on all your data.

Oracle SQL on Hadoop and beyond, with a Smart Scan service as in Exadata and the security of Oracle Database


Big Data SQL

SELECT w.sess_id, c.nameFROM web_logs w, customers cWHERE w.source_country = ‘Brazil’AND w.cust_id = c.customer_id;

Relevant SQL runs on BDA nodes

10’s of Gigabytes of Data

Only columns and rows needed to answer query are returned

Hadoop Cluster

Big Data SQL

Oracle Database

CUSTOMERSWEB_LOGS


Big Data SQL

SELECT w.sess_id, c.nameFROM web_logs w, customers cWHERE w.source_country = ‘Brazil’AND w.cust_id = c.customer_id;

Relevant SQL runs on BDA nodes

10’s of Gigabytes of Data

Only columns and rows needed to answer query are returned

Hadoop Cluster

Big Data SQL

Oracle Database

CUSTOMERSWEB_LOGS

SQL Push Down in Big Data SQL

• Hadoop Scans on Unstructured Data• WHERE Clause Evaluation• Column Projection• Bloom Filters for Better Join Performance• JSON Parsing, Data Mining Model Evaluation


Data & Analytics

Oracle Big Data Appliance and Big Data SQL for advanced analytics