apidays LIVE Australia 2020 - Building Business Ecosystems How to make the data you use for your critical business decisions accessible, clean and compliant Janet Liao, Product Marketing Lead, APAC at Talend

1. Making data for critical business decisions
accessible, clean and compliant
Janet Liao, Product Marketing Lead APAC

2. 22
DATA TYPES DATABASES
DEPLOYMENT
PLATFORMS
USE CASES
INCREASING DIVERSITY
DATA
ENGINEERING
GAPS
TECHNOLOGY CHALLENGE
Data Ops
DATA DRIVEN
BUSINESS
DECISIONS
USER CHALLENGE
Data Democratisation
INCREASING
COMPLIANCE /
REGULATIONS
GOVERNANCE CHALLENGE
Privacy l Industry Compliance
ORGANIZATIONAL
SILOS
INTEGRATION CHALLENGE
Cloud l On-Prem l Datalakes l
THE DATA MANAGEMENT LANDSCAPE

3. Data Chaos
• 400+ sources of data1 and 6+ tools in most orgs2
• 30% of revenues ($9 - $14 Million) lost due to bad data3
• $1.5 – $1.8 Trillion costs due to Shadow IT4
• 45% of digital transformation projects fail5
86% of businesses recognize that extracting value from existing data is very important6
Only 30% believe they are able to do this effectively6
1. Data Integration Solution Review, Companies Are Drawing from over 400 Different Data Sources on Average, 2019
2. IDC Data Integration and Integrity End User Survey, 2017
3. Entrepreneur, Why Bad Data Could Cost Entrepreneurs Millions, 2019
4. Fortinet, 5 Must –haves for Effectively Security Azure, 2019
5. McKinsey Digital, Digital transformation: Improving the odds of success, 2019
6. Microstrategy, Harvard Business Review Analytic Services Study Reveals Most Organizations Aren’t Prepared for a Data-Driven Future, 2018
More Data
More Locations
More Silos
Insufficient
Quality And
Governance
Disjointed
Projects &
Shadow IT
Accelerating
Change In
Technology

4. EXPERIENCES
INTELLIGENCEINFORMATION
DATA
Analytics
Operations
PROCESSES
DATA-
DRIVEN
BUSINESS
APIs
APIs APIs
APIs
APIs
APIs APIs
LEVERAGING API WITH DIGITAL TRANSFORMATION
SOLVING DATA CHAOS

5. ▪ Parallelize teams’ work
▪ Reduces development cost
▪ Reduces time-to-market
▪ Reduces developer’s learning curve
API Contract
Business DeveloperConsumer
API
Testing
API Design &
Implementation
API
Documentation
LEVERAGING API WITH DIGITAL TRANSFORMATION
SOLVING DATA CHAOS
Making data more accessible to everyone

6. 66
360o
Projects
Enterprise
Data Search
Data
Engineering
Process
Compliance
or Audit
Reporting
Modernizing
Data
Management
Architecture
Cloud DWH
Migration
Data-driven
Marketing
Campaigns
Leverage AI / ML
Technology
Real-time
Streaming
Projects
IOT Projects
CMO
CFO
Multiple Use Cases
CTO Legal Head
CDO
CEO Product Head
IS JUST API SUFFICIENT IN MANAGING DATA ?
A PLETHORA OF USE CASES

7. 77
IS JUST API SUFFICIENT IN MANAGING DATA ?
DIFFERENT STAKEHOLDER’s EXPECTATIONS OF DATA
Marketing / LOBs Legal / DPOIT
USE CASE – CUSTOMER 360
• How can we create a 360o
customer view with all the silo-
ed IT systems within the
organization ?
• How do we ensure that data is
secure and protected and
meets a minimum viable
quality ?
• How can we respond and meet
expectations of different
stakeholder’s data requests on
customers in real time ?
• How can we leverage on 360
profile to create more accurate
/ predictive upsell and cross
sell programmes ?
• How do we market more
relevant products to the
customer digitally ?
• How can I know the
customer’s sentiments on our
marketing campaigns ?
• How can we comply to data
protection and privacy legal /
industry frameworks ?
• How do we know that
customers had given their
consent ?
• In the event of data breach,
how can we inform customer
which of their data had been
breached / tampered with ?

8. 88
WHAT ELSE DO WE NEED ?
TO CREATE ACCESSIBLE, CLEAN AND COMPLIANT DATA
API services
Application
Integration
SHARE
Real time 360°
View
Data-as-a-service
Empower people with
collaboration tools
@
Matching
Golden
record
Create single
point of trust
Draw end-to-
end lineage
Capture
any data
Integrate
at speed
Certify &
protect
Organize
Curation
Standardize
COLLECT TRANSFORMGOVERN
Set the rules for
Survivorship
Enrich with
ML & AI
Discover and
document
USE CASE – CUSTOMER 360

9. 99
A Data Fabric is a design concept for attaining
reusable and augmented data integration
services, data pipelines and semantics for
flexible and integrated data delivery.
It is an optimized combination of data
management and integration technology,
architecture design and services delivered
across multiple deployment and
orchestration platforms.
This results in faster, informed and, in some
cases, completely automated data access and
sharing.
2019
Orchestrating disparate data sources intelligently
and securely in a self-service manner, leveraging
data platforms such as data lakes, Hadoop, Spark,
in-memory, big data warehouse, and NoSQL to
deliver a unified, trusted, and comprehensive view
of customer and business data across the
enterprise…
It minimizes complexity by automating processes
across the fabric stack, pushing down logic and
processing to various data platforms automatically
and intelligently, leveraging data pipelines to
ingest and process data streams dynamically, and
managing governance and security policies across
the fabric.
2019
LATEST DATA MANAGEMENT APPROACH – DATA FABRIC
ANALYST VIEW

10. 1010
A framework
comprising
architecture &
technologies
Automate,
reuse and
augment data
patterns
Govern & secure
disparate data
and technologies
Faster and
governed self-
service access to
data
DATA
FABRIC
DATA FABRIC
DEFINITION

11. 1111
Integrity
Speed
Data Stewards
Data Architects/
Engineers
Integration Specialists
Analysts
Data Scientists
Citizen Integrators How can I …?
How can I …?
How can I …?CEO / CTO /
CDO
CMO
Legal / HR
DATA FABRIC
SUPPORTS MULTIPLE STAKEHOLDERS

12. 25 office locations across North
America, Europe, and Asia-Pacific
4 cloud locations
AWS: US East, EMEA, APAC
Azure: US west
Talend Data Fabric is recognized as a
leader by top analyst firms
Trusted by over 4,750 global
organizations
Deep partnerships with leading cloud
ecosystems
PING US FOR A DEMO ON DATA FABRIC or REACH OUT
TO US ON OUR VIRTUAL BOOTH TO FIND OUT MORE !
TALEND
A LEADER IN DATA INTEGRATION & INTEGRITY