This document discusses options for indirect discovery and data visualization. It describes indirect discovery and how it works. It also discusses limitations of direct discovery approaches like long development processes and database vendor dependencies. The document proposes using SQL, NoSQL, JDBC and MDX queries to enable real-time querying of various data sources like social media. It also describes using the NVD3.js library for real-time visualization triggered by Qlikview or Qlik Sense and supporting over 36 chart types. Finally, it mentions the option of commercial editions with additional features and a live demo.

1. External Discovery and Analytics
INDIRECT DISCOVERY

2. Indirect Discovery
▪ Why we need ?
▪ How it works ?
▪ Simple Demo

4. SOLUTION
DIRECT DISCOVERY or DataVirtualization

5. Data
Virtualization
Limitations
▪ Long Development Process
▪ Hard to implement

6. Direct Discovery
Limitations
▪ Dimension Refreshing Issues
▪ Database vendor specific functions commands
▪ noSQL support ? Couch DB , Mongo DB similar

7. Poor Man
Solution
SQL
noSQL
JDBC
OLAP MDX …..
▪ Need RealTime Query Process
▪ Support social media sources
▪ XML Data Set support for Qlik - Excel
▪ JDBC Support for Hadoop Components
▪ TAJO - HBase – Cassandra
▪ OLAP MDX support
▪ Data Source for QVD

8. Visualization
NVD3.js
▪ RealTime visualization
▪ Triggered by Qlikview - Sense
▪ Implemented 2 chart types
▪ NoTable support
▪ Need it help for development 

9. NVD3.js
ChartTypes

10. Visualization
▪ RealTime visualization
▪ Triggered by Qlikview - Sense
▪ 36+ 2d – 3d ChartTypes
▪ Mapping Support
▪ Table , PivotTable support sort.
▪ Data order , filter , summary support
▪ * Used Commercial component

11. Commercial
Edition

12. Commercial
Edition

13. Viz Engine
Free or CommercialData Engine
SQL , noSQL , JDBC,
ODBC, OLAP MDX

14. Live Demo

15. Questions ?
INDIRECT DISCOVERY
Viz Engine
Free or
Commercial
Data Engine
SQL , noSQL ,
JDBC, ODBC,
OLAP MDX