In this webinar, source{d} CEO Eiso Kant will introduce source{d} Enterprise Edition (EE), the data platform for the software development life cycle (SDLC), With built-in visualization, management capabilities and advanced analytic functions, source{d} EE provide IT executives with visibility into their software portfolio, engineering processes and workforce. Learn how source{d} EE can help everyone in the IT organization to quickly get access to customizable analytic solutions for IT modernization and software compliance, cloud-native and DevOps transformation, engineering effectiveness, and talent management.

1. July 2019
The Data Platform for your
Software Development Life Cycle
1

2. 2
Agenda
Industry Challenges
source{d} EE Overview
source{d} EE Solutions
Demo
Q&A

3. 3
Industry challenges

4. 4
7 out of 10
enterprise IT initiatives fail
*McKinsey Report 2018

5. IT projects fail because executives have no visibility
Lack of visibility comes from:
Lorem ipsm
congue
Codebases
High Risk of
Failure
Processes Teams
Open Source
Proprietary
FTEs
Outsourcing
Large volume, variety, intricacy and versions of data
Source code, software development and business data are
spread across many silos
Retrieving, storing and querying at scale is hard
Shadow IT and “Dark Data” due to developer frustration
with legacy systems & slow processes

6. 6
source{d} EE overview

7. 7
source{d}
gives IT executives visibility into
codebases, IT teams & processes
If you can’t measure it, you can’t improve it. – Peter Drucker

8. From “dark data” to enlightened decisions
Center scattered codebases into a single source
of truth. Make wiser use of existing technology,
reduce duplication of software assets.
Accelerate IT modernization & Cloud Migration.
Identify patterns, drive innovation and
collaboration in your organization
TEAMS
PROCESSES
CODEBASES
Quickly assess your talent pool, knowledge
gaps and effectively manage your teams with
data-driven KPIs
8
Hard data,
accurate
information
Data-driven
decision
making

9. Make better decisions
based on insights from
state-of-art dashboards,
graphs, charts and
tables 9
The source{d} platform for the SDLC
TIMELY
Get up-to-date insights
into your Software
Development Life
Cycle at the right time
SCALABLE AI-POWERED
Leverage Machine
Learning on Code to
provide advanced and
predictive analysis
ACTIONABLE
Process billions of lines
of code & Engineering
data from thousands of
developers

10. 10
One platform from CIO to IT Managers
Easy to install, source{d] works where you do!
From version control management systems to
new data sources or hosting options, you choose
what platforms to use & add.
EASY TO SETUP & CUSTOMIZE
Built-in dashboard templates abstract away
the complexity of analyzing SDLC data
history at scale and automatically suggest
what metrics to look at for a set of key IT
initiatives.
AUTOMATED STANDARDIZATION
With robust role-based access control and
advanced security and monitoring functionality,
source{d} is designed for enterprise-wide
adoption.
SECURE & COMPLIANT
DASHBOARDS
SQL LAB UNIVERSAL ASTs
Planned announcement on 6/24

11. Powerful analyses on demand
Universal ASTs* enable deep & wide analyses across
programming languages through semantic concepts
11
Quickly answer your most complex questions
Empower your teams through SQL queries
ACCESSIBLE LANGUAGE AGNOSTIC
source code UASTs
← write questions
get answers →
* Universal ASTs were developed by source{d} as a language agnostic layer on top of source code, analyze source code independent of the diversity of programming languages

12. 12
Strong open-source & industry leadership
15.5K+ stars
2.5K+ forks
10+ Popular Open Source Projects
(go-git, Babelfish, Gitbase, etc)
500+Machine Learning on Code
community members
GitHub & Community Metrics Industry recognition
Top Open Source Users

13. Apache Superset
GitbaseBabelfish
SivaGo-GitBorgesRoversData Retrieval
Data Analysis
Data visualization
HerculesGemini
Enterprise Mgmt
Apache Spark Kubernetes Helm
Infrastructure DeploymentData Processing
Source{d} Enterprise Edition Stack

14. 14
source{d} EE Solutions

15. Solving key enterprise challenges for IT execs
1
5
Chief Architects, VP of IT
Applications
IT Modernization &
Compliance
Chief Architects, Head of
Continuous Delivery
Cloud Native &
DevOps
Transformation
Head of Developer Experience,
VP of IT Operations
Engineering Effectiveness
& Efficiency
VP and Director of
Engineering
Talent Assessment
& Management

16. IT Modernization & Compliance
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Technical Debt Assessment
Legacy Languages/ Framework analysis, Unmaintained
code analysis, Code maintenance hotspots, Arguments
and methods count, File and method lengths
Software Governance, Risk & Compliance
Share of apps on preferred tech, Top Offending
Technology Components, compliance report / Score by
entities, teams, repos, development guidelines, Top
detected problems and overridden rules
Application Portfolio Management
Share of similar / duplicate code between
teams/repository, Legacy vs Microservices Apps
categorization, Complexity / Health scores for major
applications

17. DevOps & Cloud Native Transformation
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Vendor Management
Top Vendors by category, Fastest Growing /
Declining Vendors, Share of adoption of key
technologies broken down by team
Dependency / Change Management
Dependency classification breakdown, Top internal
vs external imports, 3rd party imports heatmap
Cloud Migration
Share of repositories with a Dockerfile, Share of
repositories containing Helm charts, Share of API
code per repository

18. Engineering Effectiveness & Efficiency
18
Overall Engineering Effectiveness
Top Vendors by category, Fastest Growing / Declining
Vendors, Share of adoption of key technologies broken
down by team
Code Review Activity
Code Review Engagement, Time to First Comment,
Number of Comments / Reviewers, Documentation /
Test Coverage
Pull / Merge Request Activity
Average time to merge, Time to merge based on code
size, Most active repositories, Pull request breakdown
by topic

19. Talent Assessment & Management
19
Expertise Management
Top Areas of Expertise, Fastest Growing /
Declining Expertise, Code ownership, Expertise
Misalignment
Innersource & Collaboration
Per-project code ownership plots, Co-occurrence
of developers across different projects, Share of
repositories with missing documentation
Resource Allocation & Attrition
Internal / External Attrition or Churn Rates, Cost
breakdown by activity, Workload Balance

20. 20
Demo!

21. Benefits-funded ROI (reduction in costs & risk)
No. of developers: 5,000 - No. of Developer hired / year: 300
Average salary per developer: $110K - Onboarding time: 40h / Dev
✔ $11.6M / year in Developer Productivity - Given a 5% productivity gain
and 20% reduction in Onboarding time
✔ Savings on talents Acquisition & Retention - As Tech stack &
Engineering Culture becomes more appealing, overall Developer morale is higher.
✔ Bonus - Shifting IT budget from maintenance to innovation, from CapEx to
OpEx, Faster Time to market, etc
A single developer spends
on average 32 Hours a
month fixing errors and
replicating issus
Average 2019 Salary for a
Developer in the US
$110,000
$46,000
The annual developer
cost of bad code &
technical debt.
899 Hours*
The time a developer
spends per year on
errors and code issues.
* Sources: Evans Data Corp, CIA Factbook, Stripe research
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22. 22
source{d} CE vs EE
Community Enterprise
Single node code analysis ✔ ✔
Distributed Analysis
Multi-node on Cloud/on Prem. ✘ ✔
Advanced built-in analyses ✘ ✔
Extensibility
3rd-party integrations ✘ ✔
External data sources ✘ ✔
User-defined functions ✘ ✔
Security & Governance
SSO & RBAC ✘ ✔
Monitoring & Audit Logging ✘ ✔
Code Retrieval & Storage
Code discovery ✘ ✔
Retrieval & storage backends ✘ ✔
Deployment options ✘ ✔
Support & Certification
Enterprise grade support and SLA ✘ ✔
✔ Security & Compliance
✔ Scale & Performance
✔ Support & SLAs
✔ Enterprise Training
✔ Flexible deployment / hosting options
✔ Advanced queries and UDFs

23. Business Intelligence for the Software Development Life Cycle
sourced.tech blog.sourced.tech github.com/src-d