Thought leadership Oct2015 selfserve
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Transcript of Thought leadership Oct2015 selfserve
Data Driven Decisions via a Self Serve Ecosystem
Ron KrzoskaDirector of Engineering, Analytics Motorola Mobility [email protected]
Ron KrzoskaDirector of Engineering, Analytics [email protected] ronkrzoska
Example Cloud Ecosystem
WebProduct
Sales
Business Operation
CustomerSupport
Partners & Carriers
Consumers: Phones, Wearables &
Companion ProductsInternal Business
Teams
Marketing
FinanceEngineering
Motorola Cloud
How is data gathered?
On-Device Applications & Services
Web Applications
Cloud ecosystem gathers data from the device and web applications on a periodic basis*
● Data is stored in big data repository
*Must follow strict user opt in and privacy guidelines for gathering device and web information. PII data should be anonymized as appropriate
How does the business use the data?
Business - Activation reports Executive/key stakeholder usersDrives business objective
Device - Stability insights Consumer and Development Insights through product lifecycle
Customers - User Opinion Insights enable the voice of the customer to be heard and become actionable
Device - Analyzer Tool - Real time device insight improves customer experience.
Experience - Insights identify consumer usage and behavior to drive roadmap.
Ecosystem - The bedrock of a data driven culture. Robust community of users with bi-annual summit, robust training and support environment via solution engineering, moto ask and data wiki
George who is leading the user experience ona new feature is checking the latest experimental results and adjusting the application’s setting in real time during his commute
RequirementsUbiquity
Insights on all form factorWith you at all timeEnabling real-time feedback loop, action and
communicationInsights
The source for business decision makingExplanation based Models and
ExperimentationRecommendation based on Alerts & ModelsPredictions based on Extrapolation, Models
and Experimentation
Who uses analytics?
Inflection point/opportunity
How to promote self serve and democratize Analytics within the
company while maintaining quality as well as managing Big
Data access?
Prior environment- Reports are produced by a centralized team- Insight needs are rapidly changing- In the eyes of our customers, long lead time on report evolution
Key assumption: Business community gains SQL knowledge
Attributes: Standard retrieval, flexible access and visualization
Institutionalize SQL cultureResponsive designReport sharingReport viewing
Multiple Access Points for Data1. Browser Internal/External 2. Mobile App
Confluence’s Data Wiki
OSQA’s FAQ (Stackoverflow)
Data & Analytics Summit
Solution Engineering
Analytics EcosystemDevice Instrumentation
Big Data Environment
Cloud (GAE/GCE) Big Data
DriveInsights
BigFeed ETL
Product Architecture
Big Querydatasets
Drive Insights
AppEngine
Google Analytics
data
Device Instrumentation
App Engine
Tableaureports
Big FeedApp
Engine
Users, ReportsDatastore
Goo
gle
Driv
e
Users
Machine Learned
Models
gCha
rt +
D3
+ Ta
blea
u AP
I
Bigfeed - Big Query to Big Query ETL
BigFeed
Check-in Data(PB)
StagingData(TB) Reporting
Data(GB)
BigFeed
An example of what’ possible with self serve big data solution
● Approaching 1000 monthly users● Over 60 developers of reports● Data driven decisions are institutionalized
across the business
Conclusion
● A self service ecosystem is viable and effective in a large organization● The ecosystem must include simple and intuitive tools● A thoughtful support system is needed
In this presentation, Ron Krzoska will discuss the journey to a data driven culture. This will be done through the lense of building a self service analytics ecosystem. The vision, business value as well as user profiles frame the path. The requirements have been realized with a SQL based solution. The experience, learning and custom capabilities to meet the needs of the business are discussed as well as the adoption throughout the business.
Abstract