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Copyright © 2018, Oracle and/or its affiliates. All rights reserved. |
OOW2018 – Data Integration
Modern Stream-based Data Integration
Product Development
October, 2018
Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018
Safe Harbor Statement
The following is intended to outline our general product direction. It is intended for
information purposes only, and may not be incorporated into any contract. It is not a
commitment to deliver any material, code, or functionality, and should not be relied upon
in making purchasing decisions. The development, release, timing and pricing of any
features or functionality described for Oracle’s products may change and remains at the
sole discretion of Oracle Corporation.
Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018 2
Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018
Data Democratization
Data Monetization
Self-service IT
Open-Data
Regulatory Governance
Digital Transformation
Market Disruption
Customer 360
WHAT DOES THE
BUSINESS WANT?BUSINESS IMPERATIVES
3
4Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018
DATA INTEGRATION
MAKES IT POSSIBLE
Applications
Polyglot Data
Databases
Data Services
Analytics &
Data Warehouse
Data Lake &
Data Science
DATA
INTEGRATION &
GOVERNANCE
5Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018
MODERN DATA “PLUMBING”
IS CRITICALLY IMPORTANT FOR MODERN DATA ARCHITECTURE
“Integration tops the list of challenges in the world of data
and analytics today. […] Co-located data is not the same as
integrated data. […] You have to have something to connect
the dots.”
https://www.cio.com/article/3269012/analytics/why-data-analytics-initiatives-still-fail.html
Why Data Analytics Initiatives Still Fail
April, 2018
6Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018
WHY IS THE DATA “PLUMBING” SO IMPORTANT?
#1 - Feedback Loops
Need to be Quicker
#2 - More Data from
More Sources
#3 - New Regulatory
Pressure for Transparency
Every industry and
geography under more
scrutiny
Data inputs happening
faster and from more
devices
Business demand for
faster, data-driven
decisions
7Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018
OLD-STYLE DATA PLUMBING NOT GOOD ENOUGH ANYMORE
Batch processing, hub-and-
spoke Kimball-style solution
Data storage is a mix of file
system, database, hadoop
Data governance is ad-hoc
and inconsistent
Data Workloads
are in Motion
Data at rest
is in Object Storage
All Data Inventory
is in a Catalog
Traditional Approaches Modern Approaches
8Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018
Hadoop
is dead
Hub-and-
Nope!
ETL tools
are toast
EDW is a
dinosaur
9Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018
Streaming
Pipelines
Data Sushi
(HIPSTER)
Serverless
Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018
What is Modern?
Source Data Consumers
#1 – Ingest happens any time
data is available
#2 – Processing can happen
at any latency
#3 – Data is available in the
consumer’s format
Raw Data
Ingest
Stream Processing
Batch Processing
& Long Term Storage
Serving
Layer
#4 – Infrastructure is Serverless
#5 – Data at rest is on Object Storage
Application Data
Polyglot Data
SQL & NoSQL Data
Data Lake & Data Science
Data Services for Applications
EDW & Analytics for Reporting
10
Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018
What is Modern Data Ingestion?
#1 – Ingest happens any time
data is available
Raw Data
Ingest
Copying data is bad, but overloading the source application is worse
• Physical co-location is usually first step in a Data Lake
• Optimize for minimal impact on source systems
• Replication of changed data is usually best option for databases
Event driven is mandatory in new world order
• Move data the moment it can, don’t wait for a job scheduler
• Some data is process-bound to batch
Support key styles of data movement and virtualization
• Parallel Data Copy for File-centric Data
• Database Replication for Relational Data
• Bulk Extraction or Storage Replication for full copies
• Data Federation/Virtualization is a “nice to have” but most source systems
can’t take the pain
Initial loads subject to laws of physics and speed of light
• Terabytes take time
• Optimize for database bulk copy programs (BCP for block level unloaders) or
big data copy programs (DCP is highly parallel)
• There is no such thing as magic 
Bulk Copy
Utilities
Source Data
Application Data
Polyglot Data
SQL & NoSQL Data
11
Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018
GoldenGate is Modern
https://www.oracle.com/us/products/middleware/data-integration/oracle-goldengate-innovations-wp-5093027.pdf
NON-RELATIONAL DATA
KERNEL INTEGRATIONS
REMOTE CAPTURE
SIMPLIFICATION
MICROSERVICES
CONTAINERS
MONITORING
STREAM ANALYTICS
CLOUD
SUBSCRIPTIONS
GOLDENGATE FOR STREAMING BIG DATA:
12
Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018
What is Modern Data Processing?
#2 – Processing can happen
at any latency
Stream Processing
Batch Processing
Pipeline Editor
Object Storage
Streaming Use Cases
• Clickstream Analytics
• Recommendation Engines
• Fraud Detection / Alerting
Pipeline “Logic” Layer
• Specify data pipelines, rules and
embed Machine Learning
• Architecture decoupling:
independent from the engines
• Improve usability for analysts
Streaming Engines
• Oracle Preferred: Flink for true
streaming, Spark for micro-
batching and ML use cases
• Others: Storm, Kafka Streams,
Samza, or Vendor Proprietary
Batch Use Cases
• ETL Offloading
• Data Lake Loading
• Large Scale Analytics
Batch (MPP) Processing
• Engines: Spark for most cases,
Hive or Flink in special cases
• Storage: Object Storage
Interactive Data Access
• SQL for direct query of very large
data sets:
• Hive SQL (basic)
• Spark SQL (basic)
• Sparkline OLAP (advanced)
• Machine Learning & Graph
• MLlib
• GraphX
* In your own data center you can have mixed workloads run from same
physical clusters (ie; Kappa-style) but from the Cloud you should only pay
for what you use and not care how the infrastructure is managed…
13
Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018
What is a Modern Serving Layer?
#3 – Data is available in the
consumer’s format
Serving
Layer
Streaming API for Real-Time Data
• Publish and Subscribe (Kafka), with Apps-friendly REST APIs
• REST-based means that API Gateways can be used for Secure
ACLs
• HTTPS transmission and no file system access to data
• Data redaction at API / contract level
SQL-based Access for Interactive Reporting
• Bulk data movement (ETL) out to external data
warehouses/marts
• Direct SQL access to data stored in the Data Lake (Spark OLAP)
• Most widely used data manipulation language
• Numerous LDAP-based client security patterns for data privacy
Direct Access to Raw Data for Specialists
• Native access to data buckets (object storage) or HDFS (file
system)
• Especially useful for Machine Learning / AI programs
• Direct access to large data sets without unnecessary
movement
• Identity for local access is granted at object level (eg; a data file)
Consumers
Data Lake & Data Science
Data Services for Applications
EDW & Analytics for Reporting
SQL
14
Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018
What is Modern Infrastructure?
#4 – Infrastructure is Serverless
#5 – Data at rest is on Object Storage
OCI Compute
Ingest
Stream
Batch
Serve
Public Cloud Infrastructure is setting the standard for low-cost and high-performance
• Pay only for what you use, serverless style of operation takes operational burdens away from the IT consumers
• Fast compute with flat network runs 5x faster than Amazon (https://blogs.oracle.com/cloud-infrastructure/oracle-tests-better-in-performance-than-amazon-web-services )
• Very low cost storage that is practically infinite, with 99.999999% reliability
OCI Object Store
Source Data
Application Data
Polyglot Data
SQL & NoSQL Data
Consumers
Data Lake & Data Science
Data Services for Applications
EDW & Analytics for Reporting
15
Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018
What is Modern?
Source Data ConsumersRaw Data
Ingest
Stream Processing
Batch Processing
& Long Term Storage
Application Data
Polyglot Data
SQL & NoSQL Data
Data Lake & Data Science
Data Services for Applications
EDW & Analytics for Reporting
Bulk Copy
Utilities
Batch Processing
Pipeline Editor
Object Storage
Serving
Layer
SQL
ANY DATA ANY LATENCY ANY FORMAT ANYWHERE
16
Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018
What is Modern? Oracle Cloud
Source Data ConsumersRaw Data
Ingest
Stream Processing
Batch Processing
& Long Term Storage
Application Data
Polyglot Data
SQL & NoSQL Data
Data Lake & Data Science
Data Services for Applications
EDW & Analytics for Reporting
Bulk Copy
Utilities
Batch Processing
Pipeline Editor
Object Storage
Serving
Layer
SQL
ANY DATA ANY LATENCY ANY FORMAT ANYWHERE
Oracle Data Pipelines
Oracle Data Integration
Oracle Big Data
Oracle
Events
Oracle
Data
Integration
Oracle
Database
Oracle
Events
Oracle Big
Data
Oracle Cloud
17
Copyright © 2018, Oracle and/or its affiliates. All rights reserved. |Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018 18
Original Architecture Stream Data Platform
https://www.confluent.io/blog/stream-data-platform-1/
Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | 19
Microservices-based
GoldenGate
data service
19 different
enterprise
applications
Enterprise Data Lake
Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018
Copyright © 2018, Oracle and/or its affiliates. All rights reserved. |Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018 20
✓ Fully managed, replicates >30TB’s per day, low latency
✓ Real-time streaming data platform built with
Oracle GoldenGate, Kafka, Flink and Kubernetes
✓ Provide shared, curated, “private” streams and stream
processing computation running on eBay cloud
✓ Dynamic stream endpoint discovery
✓ Standardized data format & stream catalog
✓ Secure stream access control
✓ Data movement across security zones over secure connections
✓ Comprehensive monitoring, alerting and remediation
https://www.ebayinc.com/stories/blogs/tech/rheos/
Copyright © 2018, Oracle and/or its affiliates. All rights reserved. |Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018 21
https://medium.com/netflix-techblog/netflix-billing-migration-to-aws-part-iii-7d94ab9d1f59
On Premise
Billing
Application
Cloud Data Platform
“GoldenGate stood out in terms of features it offered
which aligned very well with our use case.”
Copyright © 2018, Oracle and/or its affiliates. All rights reserved. |Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018 22
Enterprise Data Lake
Copyright © 2018, Oracle and/or its affiliates. All rights reserved. |Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018 23
Financial Data
Warehouse
Oracle Data
Integration
Platform
ETL
24Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018
ORACLE UNIQUE TECHNOLOGY
COLLABORATIVE, COMMON PANE OF GLASS
PUSHDOWN OPTIMIZER FOR ETL IN STREAMS, BATCH OR DB
HYBRID AGENT-BASED ARCHITECTURE
GOLDENGATE-BASED STREAMING DATA INGESTION
STREAMING ANALYTICS BEST-IN-CLASS USER EXPERIENCE
GoldenGate for Kappa / Streaming
Raw
Data
Layer
Apps Layer
Speed Layer
Batch Layer
Application
Serving
Layer
REST
APIs
Analytics
Tools
Data
Science
Data Marts
GG GG
User
Updates
DBMS
Updates
Capture
Trail
Route
Deliver
Pump
SSL/HTTPS
JSON
ORC
CSV
Parquet
XML
DDL
Events
Prepared
Data
Prepared
Data
EBay runs 200 billion transactions per
day; more than 25 TB of changed data
per day via GoldenGate and less than 2
seconds of end-to-end latency (Flink)
LinkedIn operates GoldenGate on >200
databases across 5 global data centers
(Samza for processing)
Quickbooks.com runs GG on Oracle,
SQL Server and DB2 hosted on AWS
(GG+Kafka is enterprise data fabric that
feeds their data science/ML platform)
Apple iTunes and uses GG+Kafka to
ingest transactions into 5,000+ node
Data Lake (for data science)
General Motors uses GG+Kafka and
GG+S3 to move transactions from 600+
databases into their Data Lake
Maersk uses GG+Kafka for realtime IoT
tracking of global shipments and port of
entries (customs tracking)
MGM shifting entire IT data
architecture to GG+Kafka for streaming
Validation by forward-leaning customers: Kappa ETL architecture
• We see GG customers using various Stream Processing engines: Spark
Streaming, Flink, Kafka Streams, Apex/DataTorrent, Samza, Kinesis
Firehose, Storm, etc.
Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018 25
GoldenGate now Includes Stream Analytics
ETL
Services
Dimensional
Data
Cubes
Ingest Database Events Select Processing Patterns Build Event Pipelines Serve Data Downstream
Any GoldenGate event is included
free, Kafka native events require
full-use license
Rich set of pre-built patterns can
dramatically improve developer
efficiency and time-to-value
Tool can easily leverage geo-fencing,
machine-learning, and other lookup
data within the data stream
Data can be delivered out to kafka,
databases, or easily staged for
downstream ETL jobs
connect
Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018 26
Oracle Data Integration Platform
Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018
Common Framework for Data Integration Use Cases
Database
Migrations
Database
Replication
Data Warehouse
Automation
Data Lake
Automation
Data Governance
Oracle Cloud
Non-Oracle Data Centers
Application Data
Polyglot Data
SQL & NoSQL Data
27
Oracle Databases
Data Integration Platform - Built for Collaboration
Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018
DBA Data Engineer ETL Developer Data Steward Data Analyst
Builds replication/ingest pipelines
Works mostly with databases
(data models, sql, plsql)
Builds pipelines for Data Lake
Works mostly with code
(java, scala, python, sql)
Builds pipelines for DW/Marts
Works mostly with tools
(data models, sql, mappings)
Manages policies & cleansing rules
(for pipelines and data at rest)
Works mostly with tools
Domain expert, prepares data
Works mostly with tools
Many Personas Need to Work Together for Data Integration Solutions
Oracle Data Integration Platform
Non-Oracle SQL and Polyglot Data Apps & SaaS
Logs
28
Data Integration Platform - Data Lake Solutions
Data Ingest
Best-in-class streaming or batch
data ingestion/loading
Data Preparation
Deduplicate, Enhance, Link and
Consolidate Enterprise Data
Data Catalog
Scan and inventory data from
across all locations
Stream Analytics
Apply governed business rules
across many sources
Data Lake Builder
Quickly create and load a policy-
driven data lake
Data Pipelines
Organize, cleanse and process
any data in the Lake
Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018 29
Agent Execution Runs from Anywhere
Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018
Oracle Data Integration
Platform Cloud:
1. Design the Solution
2. Administer the Deployments
3. Meter the Subscriptions
Control
Plane
Firewall
Data
Plane
Support on-prem use cases! Customer data can stay in the “Data Plane” only.
Corporate data center AWS
Amazon
EC2
Amazon
Redshift
Azure
Azure
VM
Azure
HD Insight
<https>
30
Machine-assisted ETL Optimizer for DW Loading
Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018
Files
Staging
(Batch)
Lookup
Table
Reporting
Tables
Staging
(streaming)
Device
Object
Store
Streaming
Sources
Batch
Sources
2. SQL
Filter
6. Flink
ETL
5. Spark
ETL / ML
10. SQL
ETL
3. Bulk
Unload
4. Parallel
Copy
9. Block
Load
1. Log
Capture
7. Direct
Replication
8. Direct
Copy
Unified Editor (DAG) to Model End-to-End PipelineData
Engineer
Data
Analyst
1
3
4
7
8
9
Oracle Cloud Infrastructure
Intelligent Optimizer to Execute ETL in Most Optimal Engine
2
5
6
10
31
Pattern for Logical Data Zones & Topic Types
Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018
Raw Data (LCR)
Schema Events
(DDL)
Prepared Data Topics
Master Data Topics
ETL ETL
1 Topic : 1 Table
Data Consumers
Applications
Analytics
ODS (Data Store)
Data Marts
Data Warehouses
Stream Data Producers
Apps & DBs:
Staging Trusted Master
ETL
Bulk Data Producers
ETL
Data Science
Events are
Pushed
Batching
Interactive
Queries
OLAP SQL
Bucket 1 Bucket 2 Bucket 3
32
Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 201833
Presen-
tations:
Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018 34
Data Integration Programming – FOCUS ON DOC LINK
Demo
Kiosks:
Hands-
on Labs:
Oracle
Enterprise
Data Quality
Oracle
GoldenGate
Oracle
Data Integrator
Oracle
Data Integration
Platform Cloud
Oracle
Stream
Analytics
Introduction to
Data Integration
Platform Cloud
HOL6277
Operational Data Stores,
Enterprise Data Warehouses,
and Data Marts in the Cloud
HOL6278
Faster Oracle GoldenGate
Deployments in the Cloud
Using Microservices
HOL6282
Analyzing
Oracle GoldenGate Streams
with Oracle Data Integration
Platform Cloud
HOL6286
The Exchange -
Integration Area
- Moscone South
The Exchange -
Analytics & Big Data Area
- Moscone West
The Exchange -
Data Management Area
- Moscone South
Oracle
Data Catalog
Cloud
Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018 35
Data Integration Programming – FOCUS ON DOC LINK
Monday, October 22
• PRM4229 - Oracle’s Data Platform Roadmap: Oracle GoldenGate,
Oracle Data Integrator, Governance
• PRO4230 - Oracle’s Data Platform in the Cloud: The Foundation for
Your Data
• PRO4231 - Oracle’s Data Platform in the Cloud: Powered by Oracle
GoldenGate/Oracle Stream Analytics
Tuesday, October 23
• PRO4232 - Oracle’s Data Platform in the Cloud Deep Dive
• PRM4061 - Oracle's Data Platform: Strategy and Roadmap for
Oracle Data Integrator
• PRO4233 - Actionable Business Insights with Oracle Stream
Analytics
• HOL6277 - Introduction to Data Integration Platform Cloud
• HOL6278 - Operational Data Stores, Enterprise Data Warehouses,
and Data Marts in the Cloud
• PRO4234 - Stream Processing Enterprise Data with Oracle
GoldenGate and Oracle Stream Analytics
• PRM4235 - Oracle’s Data Platform in the Cloud: Roadmap for
Oracle Enterprise Data Quality
Wednesday, October 24
• CAS4060 - Oracle's Data Platform: Customer Panel
• HOL6282 - Faster Oracle GoldenGate Deployments in the Cloud
Using Microservices
• HOL6286 - Analyzing Oracle GoldenGate Streams with Oracle Data
Integration Platform Cloud
• PRM4239 - Oracle Data Platform: Strategy and Vision for Data
Catalog
Thursday, October 25
• PRO4238 - Oracle’s Data Platform: Oracle GoldenGate for Big Data
• PRM4236 - Oracle’s Data Platform in the Cloud: Strategy and
Roadmap for Oracle GoldenGate
• PRO4557 - Loading Application Data in a Data Warehouse and a
Data Lake in Batch and Real Time
• TIP4240 - Oracle’s Data Platform: Easily Load, Manage, Govern,
and Secure a Data Lake
Presenters: Highlight your current
session in bold red, and gray out any
session that has already happened
Connect with Oracle Integration
@OracleDI
Blogs.oracle.com/DataIntegration/
@OracleIntegrate
Blogs.oracle.com/Integration/
Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018 36
Safe Harbor Statement
The following is intended to outline our general product direction. It is intended for
information purposes only, and may not be incorporated into any contract. It is not a
commitment to deliver any material, code, or functionality, and should not be relied
upon in making purchasing decisions. The development, release, timing, and pricing of
any features or functionality described for Oracle’s products may change and remains at
the sole discretion of Oracle Corporation.
Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018
37

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Stream based Data Integration

  • 1. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | OOW2018 – Data Integration Modern Stream-based Data Integration Product Development October, 2018 Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018
  • 2. Safe Harbor Statement The following is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions. The development, release, timing and pricing of any features or functionality described for Oracle’s products may change and remains at the sole discretion of Oracle Corporation. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018 2
  • 3. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018 Data Democratization Data Monetization Self-service IT Open-Data Regulatory Governance Digital Transformation Market Disruption Customer 360 WHAT DOES THE BUSINESS WANT?BUSINESS IMPERATIVES 3
  • 4. 4Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018 DATA INTEGRATION MAKES IT POSSIBLE Applications Polyglot Data Databases Data Services Analytics & Data Warehouse Data Lake & Data Science DATA INTEGRATION & GOVERNANCE
  • 5. 5Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018 MODERN DATA “PLUMBING” IS CRITICALLY IMPORTANT FOR MODERN DATA ARCHITECTURE “Integration tops the list of challenges in the world of data and analytics today. […] Co-located data is not the same as integrated data. […] You have to have something to connect the dots.” https://www.cio.com/article/3269012/analytics/why-data-analytics-initiatives-still-fail.html Why Data Analytics Initiatives Still Fail April, 2018
  • 6. 6Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018 WHY IS THE DATA “PLUMBING” SO IMPORTANT? #1 - Feedback Loops Need to be Quicker #2 - More Data from More Sources #3 - New Regulatory Pressure for Transparency Every industry and geography under more scrutiny Data inputs happening faster and from more devices Business demand for faster, data-driven decisions
  • 7. 7Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018 OLD-STYLE DATA PLUMBING NOT GOOD ENOUGH ANYMORE Batch processing, hub-and- spoke Kimball-style solution Data storage is a mix of file system, database, hadoop Data governance is ad-hoc and inconsistent Data Workloads are in Motion Data at rest is in Object Storage All Data Inventory is in a Catalog Traditional Approaches Modern Approaches
  • 8. 8Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018 Hadoop is dead Hub-and- Nope! ETL tools are toast EDW is a dinosaur
  • 9. 9Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018 Streaming Pipelines Data Sushi (HIPSTER) Serverless
  • 10. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018 What is Modern? Source Data Consumers #1 – Ingest happens any time data is available #2 – Processing can happen at any latency #3 – Data is available in the consumer’s format Raw Data Ingest Stream Processing Batch Processing & Long Term Storage Serving Layer #4 – Infrastructure is Serverless #5 – Data at rest is on Object Storage Application Data Polyglot Data SQL & NoSQL Data Data Lake & Data Science Data Services for Applications EDW & Analytics for Reporting 10
  • 11. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018 What is Modern Data Ingestion? #1 – Ingest happens any time data is available Raw Data Ingest Copying data is bad, but overloading the source application is worse • Physical co-location is usually first step in a Data Lake • Optimize for minimal impact on source systems • Replication of changed data is usually best option for databases Event driven is mandatory in new world order • Move data the moment it can, don’t wait for a job scheduler • Some data is process-bound to batch Support key styles of data movement and virtualization • Parallel Data Copy for File-centric Data • Database Replication for Relational Data • Bulk Extraction or Storage Replication for full copies • Data Federation/Virtualization is a “nice to have” but most source systems can’t take the pain Initial loads subject to laws of physics and speed of light • Terabytes take time • Optimize for database bulk copy programs (BCP for block level unloaders) or big data copy programs (DCP is highly parallel) • There is no such thing as magic  Bulk Copy Utilities Source Data Application Data Polyglot Data SQL & NoSQL Data 11
  • 12. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018 GoldenGate is Modern https://www.oracle.com/us/products/middleware/data-integration/oracle-goldengate-innovations-wp-5093027.pdf NON-RELATIONAL DATA KERNEL INTEGRATIONS REMOTE CAPTURE SIMPLIFICATION MICROSERVICES CONTAINERS MONITORING STREAM ANALYTICS CLOUD SUBSCRIPTIONS GOLDENGATE FOR STREAMING BIG DATA: 12
  • 13. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018 What is Modern Data Processing? #2 – Processing can happen at any latency Stream Processing Batch Processing Pipeline Editor Object Storage Streaming Use Cases • Clickstream Analytics • Recommendation Engines • Fraud Detection / Alerting Pipeline “Logic” Layer • Specify data pipelines, rules and embed Machine Learning • Architecture decoupling: independent from the engines • Improve usability for analysts Streaming Engines • Oracle Preferred: Flink for true streaming, Spark for micro- batching and ML use cases • Others: Storm, Kafka Streams, Samza, or Vendor Proprietary Batch Use Cases • ETL Offloading • Data Lake Loading • Large Scale Analytics Batch (MPP) Processing • Engines: Spark for most cases, Hive or Flink in special cases • Storage: Object Storage Interactive Data Access • SQL for direct query of very large data sets: • Hive SQL (basic) • Spark SQL (basic) • Sparkline OLAP (advanced) • Machine Learning & Graph • MLlib • GraphX * In your own data center you can have mixed workloads run from same physical clusters (ie; Kappa-style) but from the Cloud you should only pay for what you use and not care how the infrastructure is managed… 13
  • 14. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018 What is a Modern Serving Layer? #3 – Data is available in the consumer’s format Serving Layer Streaming API for Real-Time Data • Publish and Subscribe (Kafka), with Apps-friendly REST APIs • REST-based means that API Gateways can be used for Secure ACLs • HTTPS transmission and no file system access to data • Data redaction at API / contract level SQL-based Access for Interactive Reporting • Bulk data movement (ETL) out to external data warehouses/marts • Direct SQL access to data stored in the Data Lake (Spark OLAP) • Most widely used data manipulation language • Numerous LDAP-based client security patterns for data privacy Direct Access to Raw Data for Specialists • Native access to data buckets (object storage) or HDFS (file system) • Especially useful for Machine Learning / AI programs • Direct access to large data sets without unnecessary movement • Identity for local access is granted at object level (eg; a data file) Consumers Data Lake & Data Science Data Services for Applications EDW & Analytics for Reporting SQL 14
  • 15. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018 What is Modern Infrastructure? #4 – Infrastructure is Serverless #5 – Data at rest is on Object Storage OCI Compute Ingest Stream Batch Serve Public Cloud Infrastructure is setting the standard for low-cost and high-performance • Pay only for what you use, serverless style of operation takes operational burdens away from the IT consumers • Fast compute with flat network runs 5x faster than Amazon (https://blogs.oracle.com/cloud-infrastructure/oracle-tests-better-in-performance-than-amazon-web-services ) • Very low cost storage that is practically infinite, with 99.999999% reliability OCI Object Store Source Data Application Data Polyglot Data SQL & NoSQL Data Consumers Data Lake & Data Science Data Services for Applications EDW & Analytics for Reporting 15
  • 16. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018 What is Modern? Source Data ConsumersRaw Data Ingest Stream Processing Batch Processing & Long Term Storage Application Data Polyglot Data SQL & NoSQL Data Data Lake & Data Science Data Services for Applications EDW & Analytics for Reporting Bulk Copy Utilities Batch Processing Pipeline Editor Object Storage Serving Layer SQL ANY DATA ANY LATENCY ANY FORMAT ANYWHERE 16
  • 17. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018 What is Modern? Oracle Cloud Source Data ConsumersRaw Data Ingest Stream Processing Batch Processing & Long Term Storage Application Data Polyglot Data SQL & NoSQL Data Data Lake & Data Science Data Services for Applications EDW & Analytics for Reporting Bulk Copy Utilities Batch Processing Pipeline Editor Object Storage Serving Layer SQL ANY DATA ANY LATENCY ANY FORMAT ANYWHERE Oracle Data Pipelines Oracle Data Integration Oracle Big Data Oracle Events Oracle Data Integration Oracle Database Oracle Events Oracle Big Data Oracle Cloud 17
  • 18. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. |Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018 18 Original Architecture Stream Data Platform https://www.confluent.io/blog/stream-data-platform-1/
  • 19. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | 19 Microservices-based GoldenGate data service 19 different enterprise applications Enterprise Data Lake Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018
  • 20. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. |Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018 20 ✓ Fully managed, replicates >30TB’s per day, low latency ✓ Real-time streaming data platform built with Oracle GoldenGate, Kafka, Flink and Kubernetes ✓ Provide shared, curated, “private” streams and stream processing computation running on eBay cloud ✓ Dynamic stream endpoint discovery ✓ Standardized data format & stream catalog ✓ Secure stream access control ✓ Data movement across security zones over secure connections ✓ Comprehensive monitoring, alerting and remediation https://www.ebayinc.com/stories/blogs/tech/rheos/
  • 21. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. |Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018 21 https://medium.com/netflix-techblog/netflix-billing-migration-to-aws-part-iii-7d94ab9d1f59 On Premise Billing Application Cloud Data Platform “GoldenGate stood out in terms of features it offered which aligned very well with our use case.”
  • 22. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. |Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018 22 Enterprise Data Lake
  • 23. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. |Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018 23 Financial Data Warehouse Oracle Data Integration Platform ETL
  • 24. 24Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018 ORACLE UNIQUE TECHNOLOGY COLLABORATIVE, COMMON PANE OF GLASS PUSHDOWN OPTIMIZER FOR ETL IN STREAMS, BATCH OR DB HYBRID AGENT-BASED ARCHITECTURE GOLDENGATE-BASED STREAMING DATA INGESTION STREAMING ANALYTICS BEST-IN-CLASS USER EXPERIENCE
  • 25. GoldenGate for Kappa / Streaming Raw Data Layer Apps Layer Speed Layer Batch Layer Application Serving Layer REST APIs Analytics Tools Data Science Data Marts GG GG User Updates DBMS Updates Capture Trail Route Deliver Pump SSL/HTTPS JSON ORC CSV Parquet XML DDL Events Prepared Data Prepared Data EBay runs 200 billion transactions per day; more than 25 TB of changed data per day via GoldenGate and less than 2 seconds of end-to-end latency (Flink) LinkedIn operates GoldenGate on >200 databases across 5 global data centers (Samza for processing) Quickbooks.com runs GG on Oracle, SQL Server and DB2 hosted on AWS (GG+Kafka is enterprise data fabric that feeds their data science/ML platform) Apple iTunes and uses GG+Kafka to ingest transactions into 5,000+ node Data Lake (for data science) General Motors uses GG+Kafka and GG+S3 to move transactions from 600+ databases into their Data Lake Maersk uses GG+Kafka for realtime IoT tracking of global shipments and port of entries (customs tracking) MGM shifting entire IT data architecture to GG+Kafka for streaming Validation by forward-leaning customers: Kappa ETL architecture • We see GG customers using various Stream Processing engines: Spark Streaming, Flink, Kafka Streams, Apex/DataTorrent, Samza, Kinesis Firehose, Storm, etc. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018 25
  • 26. GoldenGate now Includes Stream Analytics ETL Services Dimensional Data Cubes Ingest Database Events Select Processing Patterns Build Event Pipelines Serve Data Downstream Any GoldenGate event is included free, Kafka native events require full-use license Rich set of pre-built patterns can dramatically improve developer efficiency and time-to-value Tool can easily leverage geo-fencing, machine-learning, and other lookup data within the data stream Data can be delivered out to kafka, databases, or easily staged for downstream ETL jobs connect Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018 26
  • 27. Oracle Data Integration Platform Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018 Common Framework for Data Integration Use Cases Database Migrations Database Replication Data Warehouse Automation Data Lake Automation Data Governance Oracle Cloud Non-Oracle Data Centers Application Data Polyglot Data SQL & NoSQL Data 27
  • 28. Oracle Databases Data Integration Platform - Built for Collaboration Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018 DBA Data Engineer ETL Developer Data Steward Data Analyst Builds replication/ingest pipelines Works mostly with databases (data models, sql, plsql) Builds pipelines for Data Lake Works mostly with code (java, scala, python, sql) Builds pipelines for DW/Marts Works mostly with tools (data models, sql, mappings) Manages policies & cleansing rules (for pipelines and data at rest) Works mostly with tools Domain expert, prepares data Works mostly with tools Many Personas Need to Work Together for Data Integration Solutions Oracle Data Integration Platform Non-Oracle SQL and Polyglot Data Apps & SaaS Logs 28
  • 29. Data Integration Platform - Data Lake Solutions Data Ingest Best-in-class streaming or batch data ingestion/loading Data Preparation Deduplicate, Enhance, Link and Consolidate Enterprise Data Data Catalog Scan and inventory data from across all locations Stream Analytics Apply governed business rules across many sources Data Lake Builder Quickly create and load a policy- driven data lake Data Pipelines Organize, cleanse and process any data in the Lake Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018 29
  • 30. Agent Execution Runs from Anywhere Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018 Oracle Data Integration Platform Cloud: 1. Design the Solution 2. Administer the Deployments 3. Meter the Subscriptions Control Plane Firewall Data Plane Support on-prem use cases! Customer data can stay in the “Data Plane” only. Corporate data center AWS Amazon EC2 Amazon Redshift Azure Azure VM Azure HD Insight <https> 30
  • 31. Machine-assisted ETL Optimizer for DW Loading Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018 Files Staging (Batch) Lookup Table Reporting Tables Staging (streaming) Device Object Store Streaming Sources Batch Sources 2. SQL Filter 6. Flink ETL 5. Spark ETL / ML 10. SQL ETL 3. Bulk Unload 4. Parallel Copy 9. Block Load 1. Log Capture 7. Direct Replication 8. Direct Copy Unified Editor (DAG) to Model End-to-End PipelineData Engineer Data Analyst 1 3 4 7 8 9 Oracle Cloud Infrastructure Intelligent Optimizer to Execute ETL in Most Optimal Engine 2 5 6 10 31
  • 32. Pattern for Logical Data Zones & Topic Types Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018 Raw Data (LCR) Schema Events (DDL) Prepared Data Topics Master Data Topics ETL ETL 1 Topic : 1 Table Data Consumers Applications Analytics ODS (Data Store) Data Marts Data Warehouses Stream Data Producers Apps & DBs: Staging Trusted Master ETL Bulk Data Producers ETL Data Science Events are Pushed Batching Interactive Queries OLAP SQL Bucket 1 Bucket 2 Bucket 3 32
  • 33. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 201833
  • 34. Presen- tations: Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018 34 Data Integration Programming – FOCUS ON DOC LINK Demo Kiosks: Hands- on Labs: Oracle Enterprise Data Quality Oracle GoldenGate Oracle Data Integrator Oracle Data Integration Platform Cloud Oracle Stream Analytics Introduction to Data Integration Platform Cloud HOL6277 Operational Data Stores, Enterprise Data Warehouses, and Data Marts in the Cloud HOL6278 Faster Oracle GoldenGate Deployments in the Cloud Using Microservices HOL6282 Analyzing Oracle GoldenGate Streams with Oracle Data Integration Platform Cloud HOL6286 The Exchange - Integration Area - Moscone South The Exchange - Analytics & Big Data Area - Moscone West The Exchange - Data Management Area - Moscone South Oracle Data Catalog Cloud
  • 35. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018 35 Data Integration Programming – FOCUS ON DOC LINK Monday, October 22 • PRM4229 - Oracle’s Data Platform Roadmap: Oracle GoldenGate, Oracle Data Integrator, Governance • PRO4230 - Oracle’s Data Platform in the Cloud: The Foundation for Your Data • PRO4231 - Oracle’s Data Platform in the Cloud: Powered by Oracle GoldenGate/Oracle Stream Analytics Tuesday, October 23 • PRO4232 - Oracle’s Data Platform in the Cloud Deep Dive • PRM4061 - Oracle's Data Platform: Strategy and Roadmap for Oracle Data Integrator • PRO4233 - Actionable Business Insights with Oracle Stream Analytics • HOL6277 - Introduction to Data Integration Platform Cloud • HOL6278 - Operational Data Stores, Enterprise Data Warehouses, and Data Marts in the Cloud • PRO4234 - Stream Processing Enterprise Data with Oracle GoldenGate and Oracle Stream Analytics • PRM4235 - Oracle’s Data Platform in the Cloud: Roadmap for Oracle Enterprise Data Quality Wednesday, October 24 • CAS4060 - Oracle's Data Platform: Customer Panel • HOL6282 - Faster Oracle GoldenGate Deployments in the Cloud Using Microservices • HOL6286 - Analyzing Oracle GoldenGate Streams with Oracle Data Integration Platform Cloud • PRM4239 - Oracle Data Platform: Strategy and Vision for Data Catalog Thursday, October 25 • PRO4238 - Oracle’s Data Platform: Oracle GoldenGate for Big Data • PRM4236 - Oracle’s Data Platform in the Cloud: Strategy and Roadmap for Oracle GoldenGate • PRO4557 - Loading Application Data in a Data Warehouse and a Data Lake in Batch and Real Time • TIP4240 - Oracle’s Data Platform: Easily Load, Manage, Govern, and Secure a Data Lake Presenters: Highlight your current session in bold red, and gray out any session that has already happened
  • 36. Connect with Oracle Integration @OracleDI Blogs.oracle.com/DataIntegration/ @OracleIntegrate Blogs.oracle.com/Integration/ Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018 36
  • 37. Safe Harbor Statement The following is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions. The development, release, timing, and pricing of any features or functionality described for Oracle’s products may change and remains at the sole discretion of Oracle Corporation. Copyright © 2018, Oracle and/or its affiliates. All rights reserved. | Oracle OpenWorld 2018 37