Real-time Business Intelligence - InterSystems Benelux

DeepSee Overview
Joe Gallant
Symposium 2010

Embedded + Real Time
Delivered as an
integral part of an
application
Access to current
data needed for
operational decision
making
Embedded Real-Time
Business Intelligence

Competitive Comparison
Embedded Real-Time BI
Data accessed in
place
Current + historical,
detail + summary data
Any application user
Traditional BI
Data extracted and
loaded periodically
Historical summary
data only
Specialist users with
tool + data schema
expertise

DeepSee In Action @ QuadraMed
Rules
Rules
Patient Registration
Workflow
“With DeepSee, you’re
managing the
configuration and
performance of your
business in real time.”
Patient Registration
Workflow with DeepSee
• Real-time
monitoring of
quality, throughput,
backlog, …
• Dynamic tuning of
rules

Registration WorkList Dashboard

Actionable Business Intelligence

DeepSee Lessons Learned
• People like DeepSee!
– Tremendous customer interest
– Embedded BI is actually useful
• What people like about DeepSee:
– Performance
– Ability to handle complex data
– Ease of use
– Thin client
• Finding the right use case is the key!

DeepSee Lessons Learned
• What people would like improved in
DeepSee:
– Performance
– Ability to handle complex data
– Ease of use
– Thin client

All DeepSee is divided in 3 parts
Query
Engine
Portal
Data Model

DeepSee Model Improvements
• Well-defined data model
– Simplifies the design of the data model
– XML representation is available
– Better integration with source control
• Removes the need to modify existing
transactional classes
• Use of standard bitmap and bitslice indices
• Object-based time dimensions for better
flexibility

DeepSee Data Model
• Cubes
– Defines dimensions and
measures
• Subject Areas
– “Views” on cubes
– Provides automatic filtering
• KPIs
– Makes more sophisticated
computations available to
dashboards
– Can make use of DeepSee, SQL,
or custom logic
Note: Lifting of cubes in
thunderstorm will void warrantee

DeepSee Execution Engine
• Cleaner, more streamlined engine based on
native index structures
• ResultSet API available to make DeepSee
functionality available to applications
• Support for MDX query language
– Subset at first (reasonably complete)
– More complete implementation as needed
– Extensions for additional power

DeepSee Query Engine
• Analyzer
– Visual query construction
– Queries can be saved
• DeepSee ResultSet
– Programmatic API
• DeepSee Shell
– Interactive queries
Keep fingers away from gears
Keep arrows away from eyes
Keep magnifying glass out of strong sunlight

DeepSee Performance and Scalability
• Multi-level, incremental caching to support
large data models (100M+ facts)
• Support for parallel execution of queries to
exploit multi-core architectures:
– Queries are split by # of facts
– Queries are split by # of cells
– Subqueries and joins
• Logic for updates to Data Model is
streamlined

DeepSee User Interface
• Clear separation of DeepSee engine and
DeepSee UI
– APIs available to access DeepSee engine
• Built with Zen technology
– Supports multiple browsers
– Standard Zen components
– Uses the DeepSee APIs

DeepSee Portal
• User Portal
– Clean, easy way to see dashboards,
reports, and saved queries
• Dashboards
– Display data from saved queries or
KPIs
– Data displayed in visual “widgets”
– Dashboard “actions” can interact with
application logic

DeepSee Overview
Joe Gallant
Symposium 2010