TECHNOLOGY
Vital Analytix
VITAL ANALYTIX
Flexible and Modular
- Architecture: Three-tier cloud-enabled architecture with Application, Web, and DB Servers. Built on J2EE design patterns with business logic and data access separated
- Works with all industry standard operating systems, application servers and databases
- Mobility: Web-based access from desktop, mobile or any web-enabled device
Analytical
- Multi-dimensional Analysis enabled by creation of smart data marts and OLAP Cubes
- Master Data Management enabled via front-end access to users for editing, updating and deleting
- MDX engine enables business users to perform multi-dimensional analysis using a Slice and Dice interface
Scalable and Reliable
- Ability to handle large data sets without compromising on performance
- Easily manage large number of concurrent users
- Role-based data access and extensive audit trails
Workflow Engine
Workflow Engine
Core Engine
- Based on industry standard JBPM framework
- Possible to customize business process rules
- Integration with email engine for alerts
- Includes Data Entry screens and front-end uploads
- Extensive logs for audit and other purposes
Application
- Integrate into your Business Process: Capture tactical knowledge inputs which are not currently being captured by business processes or transaction processors
- Case Management: Intelligence for decision making such as approve, reject, escalate, forward, etc.
Use Case examples
- Budgeting and Planning
- Case Manager for Abnormal Transaction behavior such as Anti-Money Laundering and Fraud Analytics
- Data upload for Master Data Maintenance
Big Data
Big Data
VITAL CLUSTER
- A load balanced OLAP architecture to scale up processing capability
- In-memory computing and custom pagination to project large datasets to the end user
IN-MEMORY CACHE
- Fast Cache grid implementation using Redis
- Stores large datasets for the MDX queries
- Significant improvement in performance when data is preloaded as part of the BoD/EoD ETL run
NoSQL based OLAP
- Move past the OLAP engine constraint of querying RDBMSes by implementing NoSQL querying capability
- MDX to NoSQL translation will bring to the table the Big Data framework benefits
- MongoDB document stores and HBase based solutions
- Hadoop/Spark frameworks used to aggregate large data-sets, to service end user queries
Visualization
Visualization
Dashboard Designer
- Design-it-yourself: Create custom dashboards with 100+ customizable charts
- Interactive: Dig deeper using dimension filters and drill-down capabilities
- Favorites: Add important KPIs to the page for a running indicator
Slice and Dice
- Create data pivots that include sub-totals, filters, conditional formatting, data sorting
- Paginate datasets to simplify navigation
- Save and Schedule views to reach multiple users
- Download to Microsoft Excel, CSV, PDF
Decision support and Reporting
- Access on the desktop browser, mobile device and through plug-ins for Microsoft Excel and Outlook
- Decision support capability including alerts and exception reports
- Report designer functionality
Vital Portal
- An add-on module, that provides single view to multiple indicators of the business
- Combines and harmonizes data from diverse and multiple data sources to present complex KPIs
- Custom-designed user interface
- Drill-down capability to reach the atomic data level
ETL
ETL
Connects and Reads from diverse sources
- Extract from disparate sources such as structured databases, flat files, XML, unstructured data and web/FTP servers
- Standard and custom validation and cleansing capabilities including entity resolution
- Data storage techniques include Normalization, Encryption and Decryption
Extensive Transformational Capabilities
- Logical, statistical, mathematical functions for complex transformational capabilities
- Generate new fields or values based on aggregate data, or defined functions
- Store calculated values for faster retrieval
- Combine data from multiple sources to create new data sets
Smart Execution
- Batch job execution for parallel ETLs
- Scheduled as well as on-demand transformations with detailed logs and post-transformation alerts
- Automated mails to specific lists
- Auto-delete after a process
- GUI-based interface for ease of design
Data Modeling
Data Modeling
Supported on Vital Analytix
- Proprietary models to predict likely business outcomes
- Embed these models as part of the ETL process using VA capabilities and proprietary coding
- Integrated visualization using Slice and Dice, and dashboard modules of Vital Analytix
Industry Tools
- Build models on industry standard tools- R Language, Weka, SPSS, etc.
- Incorporate machine learning techniques
- Where feasible, integrate the results into the Vital Analytix framework
Use Case Examples
- Scoring
- Probability Estimation
- Co-relation analysis
- Association Analysis
- Clustering and Segmentation