This document discusses building self-service analytics through data APIs. It defines self-service analytics and embedded analytics. It outlines three ways to provide self-service analytics: using third-party BI tools, building your own stack, or doing nothing. Building your own stack is challenging due to dependencies, APIs, and data models. Large companies provide extensive data platforms through predefined reports, dashboards, data APIs, and report designers that serve large datasets through a single data model. A "silver bullet" is a single, schema-less data API that can query any data, providing multiple use cases through a common access point and data model with transparency.

1. Building Self-Service Analytics through
Data API
or
What Big Companies are hiding from
You
BigDataConference, 2019
Vilnius, Lithuania

2. Dionizas Antipenkovas
CEO, Founder of peekdata.io
Education: Software Engineering
Background: Database Engineer,
Data Architect, Developer
Experience: 25y+
Hobbies: Startup
Now: Coding & Growing Startup
Future: Not startup (I hope )
d.antipenkovas@peekdata.io, +370 698 00881

3. Definitions
Ways to get to it
Aha!
Examples and links
Topics to
cover

4. Analytics for Customers - Why?
• Better Productivity based on
Analytics
• Lower Operational Cost
• Improve Customer Retention
• Gain Competitive Edge
• Generate Additional Revenue
“Analytic Adopters
are x3 more likely
to see and increase
in revenue of
greater than 20%”

5. Self-service Analytics: Define
• Dashboards & KPIs
• Predefined Reports
• Scheduling
• Designing Reports/Report Writer
• Power-Pivot
• Filtering
• Data API
• Data Exports
• Design/Create
Own Data Context
Customer 1
Customer 2
Customer N
…

6. What is Embedded Analytics?
Embedded analytics is the integration of business intelligence
and reporting capabilities directly into an application.
“Analytics” mean:
• Dashboards & KPIs
• Designing & Running
Reports
• Self-Service
“Embedded” mean:
• Infusing 3rd party BI tool
into your Product/Platform
• White labeling

7. 3 ways to get to it:
• Using 3rd party BI Tools and
Solutions (Embedding)
• Building your own stack
• Forgetting about all of this
Decision Drivers:
• Customer needs
• Price
• Legacy
• Backlog

8. Using existing BI tools
(Embedded Analytics)

9. 100+ BI tools and Solutions

10. Integration
• Embedding
• Standalone, </> Iframe, Code level?
• Configuration (white labeling)
• Limited APIs
• User Management and Provisioning
• Ownership of user?
• Security
• Context Separation
• Transparency

11. Scaling
• Licensing
• Deployment
• Pipelines
• Intermediate storages
• Automation
• More Data sources
• BigData?
• Management and ownership

12. Conclusions
• Good for Small/Mid-size projects
• Not so trivial for Bigger scale
• Could be expensive
• Licensing
• Development is still needed
• Difficult to Operate
• Not all use cases covered

13. Building your own stack

14. Let’s build!
Pre-Defined Reports
(s01-e01)
- Open source stuff! (d3, BizCharts, ChartJS…)
- APIs + ORMs = Easy!
- Nobody cares…

15. We can extend it
Pre-Defined Reports
(s02-e01)
- More open source (Plotly, Highcharts..)
- Microservices!
- Interesting…
(but nobody cares)
Dashboards

16. Let’s try to finish…
Pre-Defined
Reports
(s03-e04..)
- JS gurus will help…
- Maybe GraphQL?
- Not funny anymore…
Dashboards
Report
Designer
Blue dream:
External
{REST API}

17. End results: “As usual”
• Exciting & Interesting Journey
• Long way & Expensive
• Difficult to Maintain
• Dependencies!
• Swamp in APIs and Data
• Many data models
• Not all use cases covered
• Report designer?
• Data API

18. More seasons coming?
- Don’t think so….

19. How about big companies? How they
are solving?
• Provide rich extensive data platform:
• Predefined Reports, Dashboards, Data APIs, Report Designer, Data
Exports…
• Thousands of data slices?
• Keep one data model and standard naming?
• Serve large datasets?
• Manage dependencies?
• Have full transparency?

20. “Silver bullet”?
Single, Schema less Data API to query any of your data
Fn(Request)

21. {
"scopeName": "Mortgage-Lending",
"requestID": "441b67a0-d8ef-4cac-b6bf-dcf8a52efd8c",
"consumerInfo": "Peekdata-Report-Builder-Demo",
"metrics": [ "loan amount", "weighted average interest rate" ],
"dimensions": [ "currency" ],
"filters": { …. },
"sortings": { …. },
"options": { …. }
}
Schema-Less Data API Request

22. Why single, schema-less Data API?
Pre-Defined
Reports
Dashboards
Report
Designer {REST API}
• Multiple Use cases
Covered
• Faster Development
• Reduce dependencies
• Transparent

23. Demo & Examples
http://reportbuilder.peekdata.io/
https://gitlab.com/peekdata

24. Peekdata.io
• Out of the box
• Configurable
• Performant
• Automated
• Multiple Connectors
• Sharding
• Transparent

25. Benefits
Faster development
Additional Value
One common access
point and data model
Extensive
transparency
Multiple data sources through
single gateway

26. More Use Cases
• Self-service analytics module within your solution
• Data API for your external partners and internal
development teams
• Smooth migration to other data storage technologies
• Update data structures based on usage metrics

27. Data API Implementations and
Examples
• developers.google.com/analytics/devguides/reporting/core/v3/refere
nce
• https://ga-dev-tools.appspot.com/request-composer/
• tech.yandex.com/metrika/doc/api2/api_v1/examples-docpage/
• http://cube.dev/ (Slack)
• https://www.peekdata.io/data-api.html
• http://reportbuilder.peekdata.io/
• https://gitlab.com/peekdata

28. Build or Reuse?
VS

29. Takeaways
• It depends
• Many BI tools and solutions around, but…
• Toolset, for building your own Data Platform is complete
now
• Nothing comes for free
Enjoy development - building, embedding or whatever!

30. Make your data easily
accessible, every time and
everywhere
Thank You!
www.peekdata.io