Transcript Document

Customer Use Cases
Vaikom Krishnan
Chief Architect,
Celequest Corporation
Overview
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Celequest
Low event throughput, complex analytics
High event throughput, simple analytics
Property of Celequest Corporation Proprietary and confidential. All rights reserved.
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Core Technology
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Celequest is the leading provider of dashboards for operational
performance management.
Privately held software company started in 2002
Celequest technology is comprised of the following six key
components:
 Main memory Streaming Database
 Event and Context Engine to populate the streaming database
 Rules Engine to identify exceptional conditions
 Alert Engine to propagate the exceptional condition and related
information
 Metadata Server
 Security Manager
 Dashboard/Visualization engine to visualize the metrics set up in the
streaming database
Property of Celequest Corporation Proprietary and confidential. All rights reserved.
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Celequest Core Technology
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Optimized Event & Context processing
 High Performance
 Scalable
 Minimum intrusion on operational system
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Adaptive Streaming Engine
 Interactive Data Modeling
 Dynamic View Initialization
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Standard-based architecture
 Extensible
 Rapid deployment and integration with third party applications
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Business-user oriented interface
 Self Service UI
 Personalization and Security model supporting named users
 Thin Client (DHTML / Flash)
Property of Celequest Corporation Proprietary and confidential. All rights reserved.
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Key Concepts in Celequest
Custom Interfaces
App. Workbench
Scenario Modeler
 CQ-API
 JDBC
 Web Services
 HTTP
Real-time Data/
Events
• DHTML
Presentation
Layer
Activity
Dashboard
Adaptive Intelligence
Event Table
Alerts
Workflow
Rules
 EAI Vendors
 JDBC
 JMS
 Web Services
 HTTP
 Actional/ERP
Agents
Views
Metrics
BI Tools
Context Table
Business
Metrics
Aggregate Temporal
Views
Views
Contextual Data
(Operational Systems
Datawarehouse)
Streaming Dataflow Engine
Streaming Data Store
Celequest Activity Server
Interfaces
 CQ-API
 JDBC
 Web Services
 HTTP
 Excel RTD
 Excel Web Query
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Low event throughput + complex analytics
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Customer in manufacturing sector wants to improve delivery chain
efficiency
Business problem
 Plant manager visibility into how the well the delivery chains are operating
 Measure the fill ratios of trucks
 Measure order miss rates
 Identify fill ratio trends and identify outliers
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Event data
 Truck fill data
 Delivery time, perfect order
 Labor hours
 Data is fetched from Oracle
 Loaded once a day. Expected to go to once every hour
 1000 named users expected to use the system
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Low event throughput + complex analytics
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Analytics
 Temporal analytics: sliding and tumbling windows.
 Vehicle fill percent/week
 Vehicle fill efficiency by week
 Perfect order over last 13 days
 Perfect order trends
Property of Celequest Corporation Proprietary and confidential. All rights reserved.
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High event throughput + simple analytics
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Customer in the service industry who uses internet channels
for acquiring customers
Business problem
 Determine the effectiveness of the channels in securing business
 Identify the profile of requests which are being denied service
 Identify services mining the site for fares/availability
 Day to day operational trending
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Revenue impact
 Want to enable occupancy based pricing by tracking occupancy rates
 Keep track of SLA compliance
 Site uptime and response to site down situation
 Identify reasons for denial of request and track the failure codes when
the request is denied
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High event throughput + simple analytics
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Event data
 Web reservation requests from more than one site
 Coming through the Tibco bus
 Context stored in Oracle RAC
 3 channels and 15 messages
 15 event streams
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Analytics
 Aggregate data based on brand and time
 Aberrations in service (peaks/valleys in demand)
 Transaction processed/sec
 Aggregation of requests per channel
Property of Celequest Corporation Proprietary and confidential. All rights reserved.
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