This document discusses treating database code like application code through DataOps. It begins by explaining that businesses are innovating quickly but data has become a constraint, slowing teams down. Database changes often cause risk and delays. It then discusses how application teams avoid data groups, creating risk. The next section explores where organizations want to go - rapidly deploying changes while finding issues early through automation. Benefits include reduced lead time, improved quality, faster time to market, and reduced risk. The document concludes by asking if increased database deployment automation could accelerate overall application release cycles.

1. DataOps, DevOps
and the
Developer
Treating Database Code Just Like App
Code

2. Treating Database Code Just Like App Code
2
§ Part 1: Where are we now?
§ Part 2: Where do we want to go and how do we get there?
§ Part3: What are the benefits?
§ Part 4: Q&A

3. Part 1:
Where are we now?

4. APPLICATION
Businesses are innovating fast…
4
Automation PipelinesBusiness Drivers

5. …but Data has become the new constraint, creating risk and
slowing teams down!
• Database changes are often a major
source of risk and delay when
performing deployments.
• Database are a source of data for
applications, master data, analytics and
reporting.
• Simple database changes have the potential
to damage the business if they are not
integrated into CI/CD process.
5

6. Application Teams Development Teams Avoid the Data Group
• According to Gartner:
• The disconnect between the data and
development groups creates a huge
amount of risk
• The data group is not providing guidance or
at times even aware of the changes being
made by developers.
• The safeguards that the data team has put
into place to protect the enterprise
completely fail when the development
team avoids them.
6
*Gartner: Implement Agile Database Development to Achieve Continuous Development

7. Enterprises have a critical application release velocity gap
• More application changes mean more database
changes
• The combination of application automation and
manual database deployments has created a velocity
gap
• Any gains in efficiency, productivity, speed, and time-
to-market is offset by the database release processes
• To keep up with the nonstop pace of business
innovation, enterprises must automate the way they
deploy application and database changes to deliver
better experiences faster
7
Database Deployments
Application Releases
The
Velocity
Gap
The Velocity Gap
#ofReleases
Time

8. RedMonk Observations
8
1. Application development is a set of processes and technologies that have been continually refined
and improved over decades to improve release velocity
2. As part of the effort to improve velocity, organizations industry-wide have begun to break down
the barriers between their App Dev and Ops teams - a phenomenon better known as DevOps
3. With digital business now table stakes and enterprises from all industries facing disruption from
digital natives, speed and velocity have never been more critical
4. Unlike with application development, data operations generally look much as they did a decade or
more ago, and the antiquated tools and procedures simply weren’t built operate at the pace
needed today
5. Enterprises that have seen order of magnitude improvements in their application release cycles
from DevOps and the associated procedural and tooling improvements are wondering why their
database teams can’t evolve in similar fashion
This is why modern software development organizations are turning to DataOps.

9. Poll Question:
What Challenges Does Your Team
Face in Accelerating the Database
Deployment Process?

10. Part 2:
Where do we want to go and
how do we get there?

11. Use Case: Rapid Deployment
• Find Issues Early
• Decrease Costs
• Accelerate Time to
Market
Push Trigger Build
Code Deployment
Schema Update
Data Deployment
Delphix Plugin
CODE
Virtual DB
UNIT
TEST
CODE
Virtual DB
INTEGRATION
TEST
CODE
Virtual DB
ACCEPTANCE
TEST
Sync and Mask
TEST DATA SOURCES
Provision Secure Data

12. Use Case: Test Automation
• Automate Test Setup
• Enforce Standards
• Decrease Production
Issues
Push Trigger Build
Code Deployment
Schema Update
Data Deployment
Delphix Plugin
CODE
Virtual DB
UNIT
TEST
CODE
Virtual DB
INTEGRATION
TEST
CODE
Virtual DB
ACCEPTANCE
TEST
Sync and Mask
TEST DATA SOURCES
Provision Secure Data

13. Use Case: Production Hot Fix
• Replicate Issues Without
Impacting Production
• Isolate Problems and
Intelligently Update
Production
• Synchronize Fix With All
Lower Tier
Environments
Push Trigger Build
Code Deployment
Schema Update
Data Deployment
Delphix Plugin
CODE
Virtual DB
UNIT
TEST
CODE
Virtual DB
INTEGRATION
TEST
CODE
Virtual DB
ACCEPTANCE
TEST
Sync and Mask
TEST DATA SOURCES
Provision Secure Data

14. Poll Question:
Has Your Team Ever Experienced
Production Issues Due to
Database Change Errors?

15. Part 3:
What are the benefits?

16. Benefits
16
§ Reduced product lead
time and eliminate
wait-states
§ Increased quality,
success, and employee
satisfaction
§ Minimize risk of
disruption by
competitors by
accelerating release
cycles
§ Enable self-service and
eliminating manual
processes
§ Eliminate wait:
§ Production data
delivered in
minutes.
§ Feedback on
database code
in minutes
§ Communicate status to
reduce churn
Faster Development Improve Quality
Faster Time
to Market
Reduce Risk
• Test against production
quality data to ensure
quality
• Enforce standards and
best practices on database
code
• Simulate changes prior to
release to catch problems
before they become
problems
§ Eliminate errors due to
manual configuration
and delivery
§ Reduce surface area of
risk and enable
compliance by only
leveraging masked
data in non-production
envt’s
§ Dry-run the production
push in lower
environments

17. Poll Question:
Would Increased Automation in
the Database Deployment
Process Have the Potential to
Accelerate Overall Application
Release Cycles?

18. Part 4:
Q&A

19. Thank You
To learn more,
check out our white
paper.