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Big Data 
Changing the Way You Manage and Analyze Big Data 
Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 
Jean-Pierre Dijcks 
Big Data Product Management 
Server Technologies
Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 
Use 
Data 
12% 
Executives who feel they 
understand the impact data 
will have on their organizations 
Produce 
Data
From Storing Data to Monetizing Data 
IT Budget 
*Source : ‘Enterprise Architecture As Strategy: Creating a Foundation for Business Execution’ by J Ross, P. Weill, D. Robertson, HBS Press, 2006 
Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 
Storing 
Data 
Managing 
Data 
Monetizing 
Data 
Disparate 
Data Marts 
Enterprise 
Data Warehouse 
Big Data 
Management System 
Strategic 
Business 
Value of IT 
Cost 
Center 
Profit 
Center 
100% 
84% 
92% 
145%
The Path to Monetizing Big Data 
Analytics 2.0 
Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 
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)
Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 
Conceptual View 
Actionable 
Events 
Streaming Engine Data Reservoir Enterprise Data & Reporting 
Discovery Lab 
Actionable 
Metrics 
Actionable 
Data Sets 
Input 
Events 
Execution 
Innovation 
Discovery 
Output 
Data 
Structured 
Enterprise 
Data
De Persgroep 
Creating a linked customer analytics system 
Benefits 
Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 
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 Data 
Lily 
Customer 
Analytics 
Phase 1: 
 Improved Data Quality 
 Single View of all Customers improves 
customer management 
Social 
Business 
Objects 
Oracle Data 
Warehouse 
Customer 
Analytics & aggegated 
data
Benefits 
 Save over 35,000 call processing minutes per 
day 
 Analyze network events 40x faster 
Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 
Globacom 
Improve 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 rates 
BDA 
mCentric
US-based Bank 
Lowering Costs by Simplifying IT Infrastructure 
Oracle Enterprise Manager 
• Agile business 
model 
• All data 
• De-normalized 
& Partial-normalized 
Benefits 
Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 
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 
• Normalized 
• Aggregate data 
• EDW 
Operational Data Store 
Mainframe, 
RDBMS, more 
BDA Exadata 
Oracle Data Integrator 
Data Delivery 
Master 
S1 
Master 
S2 
Master 
Sn 
SOA/API 
CRMS 
Other 
 Faster access to 6x more data 
 Lower costs, simplified architecture and fast 
time to value
Enterprise Class Big Data Capabilities 
BY INDUSTRY &z LINE OF BUSINESS 
Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 
BIG DATA 
APPLICATIONS 
DISCOVERY 
BUSINESS 
ANALYTICS 
BUSINESS ANALYTICS 
DATA RESERVOIR 
BIG DATA 
MANAGEMENT 
DATA WAREHOUSE 
SOURCES
Oracle Big Data Management System 
Oracle Big Data SQL 
Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 
SOURCES 
Oracle Database 
Oracle Industry 
Models 
Oracle Advanced 
Analytics 
Oracle Spatial & Graph 
Cloudera Hadoop 
Oracle NoSQL Database 
Oracle R Advanced 
Analytics for Hadoop 
Oracle R Distribution 
Big Data Appliance 
Oracle Database 
Oracle Advanced Security 
Oracle Advanced 
Analytics 
Oracle Spatial & Graph 
Oracle Exadata 
Oracle Big Data 
Connectors 
Oracle Data 
Integrator B
Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 
Strengths of Both Systems 
Tooling maturity 
5 
4 
3 
2 
1 
0 
Stringent Non-Functionals 
ACID transactions 
Security 
Variety of data formats 
Data sparsity 
Straight Through Processing 
(STP) 
Ingestion rate 
Cost effectively store data 
ETL simplicity 
Hadoop 
RDBMS 
• Hadoop is good at some 
things 
• Databases are good at others 
• SQL is very important
“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 
Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 
13
Oracle Communications Data Model 
Reference Architecture 
Big Data 
Platform 
(Hadoop/NoSQL) 
Relational 
Data Warehouse 
(OCDM) 
Data Management 
Feedback Loop 
Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 
Customer 
Experience 
Operations 
Monetization 
Analytic Apps 
ETL/ELT 
Adapters 
Real-Time 
Adapters 
Third 
Party 
Adapters 
Oracle Comms Apps 
(BSS/OSS) 
Oracle Comms 
Ntwk Products (Tekelec 
& Acme) 
Other Oracle Apps 
(CRM, ERP, etc.) 
Third Party Sources 
Data 
Sources 
To Other Apps 
B
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 
Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 
Oracle Confidential – Internal/Restricted/Highly Restricted 15
Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 
Two Challenges 
1. Make Hadoop easily consumable for customers 
2. Enable Oracle SQL on All Data 
16
Recap: Big Data Appliance Overview 
Big Data Appliance X4-2 
Sun Oracle X4-2L Servers with per server: 
Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 
• 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 
17 
* Oracle Big Data SQL is separately licensed
Recap: Standard and Modular 
Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 
18 
 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
Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 
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
Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 
Engineered Systems Benefits 
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 
$1,400,000 
$1,200,000 
$1,000,000 
$800,000 
$600,000 
$400,000 
$200,000 
$0 
Year 1 Year 2 Year 3 Year 4 Year 5 
Oracle BDA 
HP + Cloudera 
Savings 
List Price Comparisons 
Cumulative Cost and Savings
Engineered Systems Benefits 
BDA 3.0 DIY CDH 5.0 
Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 
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) 
Copyright © 2014 Oracle and/or its affiliates. All rights reserved. |
Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 
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
Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 
BDA Security Overview 
 Authentication through Kerberos 
 Authorization through Apache Sentry 
 Auditing through Oracle Audit Vault 
 Encryption for Data-at-Rest 
 Network Encryption
Embrace Innovation and Integrate 
Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 
Exadata 
+ 
Oracle Database 
Big Data Appliance 
+ 
Hadoop & NoSQL 
Unify 
Development languages 
Security 
Administration 
Support 
Workload management 
Lifecycle 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 
Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 26
WEB_LOGS CUSTOMERS 
Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 
Big Data SQL 
27 
SELECT w.sess_id, c.name 
FROM web_logs w, customers c 
WHERE 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 
Big Data SQL 
B B B 
Hadoop Cluster 
Oracle Database
WEB_LOGS CUSTOMERS 
Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 
Big Data SQL 
28 
SELECT w.sess_id, c.name 
FROM web_logs w, customers c 
WHERE 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 
Big Data SQL 
B B B 
Hadoop Cluster 
Oracle Database 
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
Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 29
Oracle Big Data Appliance and Big Data SQL for advanced analytics

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Oracle Big Data Appliance and Big Data SQL for advanced analytics

  • 1.
  • 2. Big Data Changing the Way You Manage and Analyze Big Data Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | Jean-Pierre Dijcks Big Data Product Management Server Technologies
  • 3. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | Use Data 12% Executives who feel they understand the impact data will have on their organizations Produce Data
  • 4. From Storing Data to Monetizing Data IT Budget *Source : ‘Enterprise Architecture As Strategy: Creating a Foundation for Business Execution’ by J Ross, P. Weill, D. Robertson, HBS Press, 2006 Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | Storing Data Managing Data Monetizing Data Disparate Data Marts Enterprise Data Warehouse Big Data Management System Strategic Business Value of IT Cost Center Profit Center 100% 84% 92% 145%
  • 5. The Path to Monetizing Big Data Analytics 2.0 Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 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)
  • 6. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | Conceptual View Actionable Events Streaming Engine Data Reservoir Enterprise Data & Reporting Discovery Lab Actionable Metrics Actionable Data Sets Input Events Execution Innovation Discovery Output Data Structured Enterprise Data
  • 7. De Persgroep Creating a linked customer analytics system Benefits Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 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 Data Lily Customer Analytics Phase 1:  Improved Data Quality  Single View of all Customers improves customer management Social Business Objects Oracle Data Warehouse Customer Analytics & aggegated data
  • 8. Benefits  Save over 35,000 call processing minutes per day  Analyze network events 40x faster Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | Globacom Improve 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 rates BDA mCentric
  • 9. US-based Bank Lowering Costs by Simplifying IT Infrastructure Oracle Enterprise Manager • Agile business model • All data • De-normalized & Partial-normalized Benefits Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 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 • Normalized • Aggregate data • EDW Operational Data Store Mainframe, RDBMS, more BDA Exadata Oracle Data Integrator Data Delivery Master S1 Master S2 Master Sn SOA/API CRMS Other  Faster access to 6x more data  Lower costs, simplified architecture and fast time to value
  • 10. Enterprise Class Big Data Capabilities BY INDUSTRY &z LINE OF BUSINESS Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | BIG DATA APPLICATIONS DISCOVERY BUSINESS ANALYTICS BUSINESS ANALYTICS DATA RESERVOIR BIG DATA MANAGEMENT DATA WAREHOUSE SOURCES
  • 11. Oracle Big Data Management System Oracle Big Data SQL Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | SOURCES Oracle Database Oracle Industry Models Oracle Advanced Analytics Oracle Spatial & Graph Cloudera Hadoop Oracle NoSQL Database Oracle R Advanced Analytics for Hadoop Oracle R Distribution Big Data Appliance Oracle Database Oracle Advanced Security Oracle Advanced Analytics Oracle Spatial & Graph Oracle Exadata Oracle Big Data Connectors Oracle Data Integrator B
  • 12. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | Strengths of Both Systems Tooling maturity 5 4 3 2 1 0 Stringent Non-Functionals ACID transactions Security Variety of data formats Data sparsity Straight Through Processing (STP) Ingestion rate Cost effectively store data ETL simplicity Hadoop RDBMS • Hadoop is good at some things • Databases are good at others • SQL is very important
  • 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 Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 13
  • 14. Oracle Communications Data Model Reference Architecture Big Data Platform (Hadoop/NoSQL) Relational Data Warehouse (OCDM) Data Management Feedback Loop Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | Customer Experience Operations Monetization Analytic Apps ETL/ELT Adapters Real-Time Adapters Third Party Adapters Oracle Comms Apps (BSS/OSS) Oracle Comms Ntwk Products (Tekelec & Acme) Other Oracle Apps (CRM, ERP, etc.) Third Party Sources Data Sources To Other Apps B
  • 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 Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | Oracle Confidential – Internal/Restricted/Highly Restricted 15
  • 16. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | Two Challenges 1. Make Hadoop easily consumable for customers 2. Enable Oracle SQL on All Data 16
  • 17. Recap: Big Data Appliance Overview Big Data Appliance X4-2 Sun Oracle X4-2L Servers with per server: Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | • 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 17 * Oracle Big Data SQL is separately licensed
  • 18. Recap: Standard and Modular Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 18  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
  • 19. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 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
  • 20. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | Engineered Systems Benefits 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 $1,400,000 $1,200,000 $1,000,000 $800,000 $600,000 $400,000 $200,000 $0 Year 1 Year 2 Year 3 Year 4 Year 5 Oracle BDA HP + Cloudera Savings List Price Comparisons Cumulative Cost and Savings
  • 21. Engineered Systems Benefits BDA 3.0 DIY CDH 5.0 Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 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)
  • 22. 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) Copyright © 2014 Oracle and/or its affiliates. All rights reserved. |
  • 23. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 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
  • 24. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | BDA Security Overview  Authentication through Kerberos  Authorization through Apache Sentry  Auditing through Oracle Audit Vault  Encryption for Data-at-Rest  Network Encryption
  • 25. Embrace Innovation and Integrate Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | Exadata + Oracle Database Big Data Appliance + Hadoop & NoSQL Unify Development languages Security Administration Support Workload management Lifecycle management Availability
  • 26. 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 Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 26
  • 27. WEB_LOGS CUSTOMERS Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | Big Data SQL 27 SELECT w.sess_id, c.name FROM web_logs w, customers c WHERE 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 Big Data SQL B B B Hadoop Cluster Oracle Database
  • 28. WEB_LOGS CUSTOMERS Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | Big Data SQL 28 SELECT w.sess_id, c.name FROM web_logs w, customers c WHERE 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 Big Data SQL B B B Hadoop Cluster Oracle Database 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
  • 29. Copyright © 2014 Oracle and/or its affiliates. All rights reserved. | 29

Editor's Notes

  1. The idea behind this is to address both the operational cost savings things like a data pool or ETL / batch replatforming brings to the table as well as the previous business value discussion, but all with (initial?) lower IT budgets
  2. 2010 Tom Davenport in HBR
  3. To meet the needs of Creating Value from
  4. Big Data SQL represents a new architecture for querying data in its natural format, wherever it leves, and – when running on Oracle Big Data Appliance and Oracle Exadata – provides a world-class Big Data Management System.
  5. Big Data SQL’s Smart Scan capability radically reduces the cost of joining data with Oracle Database as well. When a join between massive data in Hadoop and smaller data in Oracle occurs, Big Data SQL can process rows using Bloom filters. This ensures that only data from Hadoop which meets the join conditions are transmitted back to the database. As before, this can reduce the amount of data being transmitted and processed by the database by an order of magnitude or more. But in this case, Oracle Database is responsible for joining a part of average sized tables. By processing data at the source, whether it’s stored in Hadoop or Oracle Database, Big Data SQL ensures the best possible use of all the compute resources in a Big Data Management System.
  6. Big Data SQL’s Smart Scan capability radically reduces the cost of joining data with Oracle Database as well. When a join between massive data in Hadoop and smaller data in Oracle occurs, Big Data SQL can process rows using Bloom filters. This ensures that only data from Hadoop which meets the join conditions are transmitted back to the database. As before, this can reduce the amount of data being transmitted and processed by the database by an order of magnitude or more. But in this case, Oracle Database is responsible for joining a part of average sized tables. By processing data at the source, whether it’s stored in Hadoop or Oracle Database, Big Data SQL ensures the best possible use of all the compute resources in a Big Data Management System.