It’s no secret that companies are producing more data than ever before, while under pressure to determine how to most effectively use it. As a result, most companies are now moving towards streaming first data architectures – helping their businesses to gain insights from these large data volumes as they happen. Creating streaming first data architectures can seem like an overwhelming prospect to many and that is why it’s important to understand the key components needed to make sure the architectures you build for your business are future-proof. View this webcast on-demand to: • Learn how data delivery, performance, and scalability play key roles streaming first architecture success • Understand the best ways to enforce metadata across the data pipeline • Examine the strategies of how Syncsort customers have implemented best practices for streaming first architectures • Learn how Syncsort Connect solutions can help your business implement a streaming first data architecture

1. Keys to a
Streaming-First Architecture
Ashwin Ramachandran

2. Housekeeping
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Keys to a Streaming-First Architecture - © Syncsort 2019

3. • Common applications of streaming data
• Why streaming data?
• Keys to success
• Connect CDC
Agenda
Keys to a Streaming-First Architecture - © Syncsort 2019

4. “
”
Importance of streaming has grown enormously in recent
years because it provides a competitive advantage that
reduces the time gap between data arrival and its analysis.
Some insights are more valuable immediately after an event
occurs, but the value diminishes very rapidly with time.
Gartner, Stream Processing: The New Data Processing Paradigm

5. Keys to a Streaming-First Architecture - © Syncsort 2019
Despite the rise in importance, challenges exist
47% 12% 9%
Need to build streaming pipelines
to support digital business
Currently incorporate
streaming into their analytics
and data requirements
Very effective in getting value
from the data generated or
collected across the enterprise
Sources:
Stream Processing: The New Data Processing Paradigm, Gartner 2019
Data Trends for 2019: Extracting Value from Data, Syncsort 2019

6. • Real-time insights: streaming data reveals up-to-the-moment markers of the state of the business, allowing
organizations to be more agile and maintain competitive advantage.
• Break down data silos: 68% of organization struggle with disparate, siloed datasets that negatively impact
operations. Streaming data can ensure that these datasets always remain connected.
• Evolve business applications: leverage streaming data to feed applications that require real-time responses,
such as machine learning-driven fraud detection or AML applications.
• Improve customer experiences: create a customized experience for customers based on common behaviors
and correlations that streaming data can reveal.
Keys to a Streaming-First Architecture - © Syncsort 2019
Common applications of streaming data

7. Identify the right data
Keys to a Streaming-First Architecture - © Syncsort 2019
• Port workloads to less-expensive, strategic
platforms
• Connect applications together, leveraging the
existing transactional capabilities of the current
application platform, and the wealth of new
capabilities of the cloud
• Feed analytics with up-to-date information so your
business runs on current insight
Legacy data can provide a treasure-trove of
information that can transform your business when
leveraged via a streaming paradigm

8. Keys to a Streaming-First Architecture - © Syncsort 2019
Leverage the right
technology
• Guaranteed data delivery and fault tolerance
• Scalability and performance
• As your business grows, so will the demands on your
streaming pipeline.
• Lightweight footprint and impact
• When replicating from the systems that run your
business, ensure the solution won’t negatively impact
your running applications
• Maintain your metadata
• Integrate with technologies like Kafka and the schema
registry to maintain metadata lineage
Keep in mind the following must-haves:

9. Streaming and
Syncsort

10. Keys to a Streaming-First Architecture - © Syncsort 2019
Connect CDC enables organizations to build streaming data
pipelines and easily share application data across the enterprise
– from mainframes to the cloud. Connect CDC powers insights
with the most up-to-date information and helps to keep the
business in sync.

11. Top use cases for Connect CDC
Stream real-time application data from traditional systems
to mission critical business applications and analytics
platforms that demand the most up-to-date information
for accurate insights
• Traditional systems examples: mainframes, EDWs, IBM i
• Business application examples: fraud detection, hotel
reservations, mobile banking, etc.
Support Cloud and hybrid architectures by sharing
application data to, from and among cloud platforms
• A variety of application topologies that can be combined,
including: one-way, two-way, bidirectional, consolidated,
distributed, and cascade
Keys to a Streaming-First Architecture - © Syncsort 2019

12. Self-service data integration through browser based interface
• Design, deploy and monitor real-time change replication from a
variety of traditional systems (mainframe, RDBMS, EDW) to next-
generation distributed streaming platforms like Apache Kafka
Guaranteed data delivery
• Fault tolerant
• Protects against loss of data if a connection is temporarily lost
• Keeps track of exactly where data transfer left off and
automatically restarts at that exact point – no manual
intervention
• No missing or duplicate data!
Maintain metadata integrity
• Integrates with Kafka schema registry
Connect CDC
Keys to a Streaming-First Architecture - © Syncsort 2019

13. Connect Portal
The Connect Portal serves as the next-generation UI for
Connect CDC, Connect ETL and Connect for Big Data
• First Release includes:
• High-performance database loading (former
DataFunnel functionality)
• Connect CDC – ability to design, deploy and monitor
the real-time replication of changes from Oracle to
Kafka
• Future releases will include the following Connect CDC
endpoints:
• Sources
— SQL Server
— IBM i
— Db2 LUW
• Targets
— Amazon Kinesis
The new Syncsort Connect UI
Keys to a Streaming-First Architecture - © Syncsort 2019

14. Keys to a Streaming-First Architecture - © Syncsort 2019
Streaming data pipelines with Syncsort Connect
Custom
Real-Time
Applications
Sources Destinations
Syncsort
Connect
CLIENT OBJECTIVES
• Connecting business-critical
legacy applications with
downstream applications and
analytics platforms
PRIMARY
• Keeping the data lake fresh,
building a real-time data
pipeline
OTHERS
Syncsort
Connect
Mainframe
IBM i
RDBMS

15. Questions?