Gen Z BI Paradigm would be a state-of-the-art framework, with customized, interactive , rich visualization integrated with competitive analytics, Natural Language Processing, social media Sentiment Analysis, online news feeds building a collaborative BI framework that is accessible on all devices, whether on the web or mobile.
Customized, interactive ,Real-Time, Rich visualization integrated with data discovery ,competitive analytics, Natural Language Processing, social media Sentiment Analysis, online news feeds .
Gen Z BI Paradigm
GEN Z BI PARADIGM
- A Scalable , hybrid and collaborative
Visualization Architecture using Spark, No
SQL and RESTFUL API
◦ What is Gen Z BI?
◦ Key features of Gen Z BI
◦ How is it structured - Architecture?
◦ How does data flow?
◦ Real-life examples
◦ Challenges in implementation
◦ Key takeaways
What is Gen Z BI?
INTEGRATED INTELLIGENCE : BI WITHOUT LIMITATIONS
◦ Operational / Informed Intelligence – Data discovery in Real time with interactive Capabilities
◦ Social Intelligence – Social Media Sentiment Analysis , Online Feeds
◦ Competitive Intelligence – Competitive Strategies by correlation of external data
◦ Machine Intelligence - Search Capabilities powered by NLP and ML
◦ Conversational Intelligence – Personalized Chat bots
Key Features of Gen Z BI
◦ Customized, interactive, Real-Time, Collaborative Rich Visualization framework integrated
with competitive analytics, Natural Language Processing, social media Sentiment Analysis,
online news feeds
◦ Stand alone plug and play REST FUL APIs to integrate with existing Applications and UI
◦ Highly scalable , reliable and flexible hybrid architecture
◦ Multiple caching layers in API, DAO
◦ Available anytime , anywhere - Hybrid model in Web, iPad and Mobile form factors.
How is it Structured?
Files Tables Social Media &
MID - TIER
LIVE Stream Data
How does Data Flow?
• Detects the Data layer
• Converts to Queryable format
• Runs the Explain plan
• Takes the most Optimal Path
• Redirects to Cache
Cache (May Fly/EH/Mem)
• Accepts requests from Optimizer
• Based on the Key passed by
Optimizer looks up the cache
• Returns the output as Response
(Key: Value Pair)
Un- cached (Huge Volumes)
◦ In-built Management Information Systems
◦ Showing Monthly/Daily snapshot of the Performance of our company with Top vital KPI’s.
◦ Curated huge terabytes of data with response time < 5ms
◦ Master Product Dashboard
◦ Whole list of Products from an organization
◦ Details about subscriptions, targets and performance
◦ Suggested new avenues to grow
◦ Competitive insights from external data, online feeds etc.
◦ Customer insights
◦ Tailored for different segments and by industry, understanding their growth model
◦ Enabling the company to provide highly customized data spread across the globe
◦ Self Service Monitoring tool
◦ Monitoring all the operational processes inside the organization , SLAs ,tracking effort , performance, budget
Challenges in Implementation
◦ In-Memory Analytics
◦ Batch Vs Data Streaming
◦ Usage Stats
◦ How to overcome:
◦ Choosing apt Data Ingestion / Mid-Tier tools for in-memory analytics and data processing
depending upon use cases.
◦ Blending traditional BI Tools with cutting edge technologies to take advantages from
◦ Gen Z BI will help unleash the power of Big data technologies , NoSQL databases.
◦ Gen Z BI can draw upon the best of existing technologies to provide new ways of
visualizing real-time and interactive data in a flexible, scalable and reliable manner.
◦ It is structured as a plug-n-play architecture upon which varied cross functional / cross
platform / self service portal can be built on.
◦ The full stack architecture allows for seamless data flow with fast response times.