Embedded analytics: The future of Business Intelligence
- 1. Embedded Analytics The Future of Business Intelligence Anil Kumar Saini Data Visualization, Srijan Technologies
- 2. What next? Agenda ● Business Intelligence vs Embedded Analytics ● Some examples of Embedded Analytics ● Ways to Approach Embedded Analytics ● Benefits of Embedded Analytics ● Stats related to Embedded Analytics ● Trends Driving Embedded Analytics
- 3. About Srijan- Capabilities Overview Insights & Integration Content & Commerce Connected Assets Predictive & Big Data Agile / SCRUM Consulting Dynamic Infrastructure Outsourced Engineering API & Enterprise Integration Scalable Web Apps Agile & DevOps Experience & Engagement Digital Business Platform UI/ Experience & UX/ Engagement
- 4. About Srijan- Emerging Tech Stack Conversational Interfaces/ Chatbot Deep Learning / Machine Learning Data Visualization Augmented Reality/ Virtual Reality ● Visual Analytics & BI ● Chatbots & Voice Recognition ● Natural Language Processing ● Machine Learning ● Robotic Process Automation (RPA) Enabling Enterprises to stay ahead of the curve…
- 5. Gathering of data from multiple sources to present it in a way that allows executives to make better business decisions What is Business Intelligence 1 “I have all this data, what should I do with it?” 2 “How my data helps me in Analyzing my business to improve revenue?”
- 6. What is Business Intelligence BI Systems allow a company to Gather Store Access Analyze Accelerate Decision-Making
- 7. Integration of analytic content and capabilities inside software applications. What is Embedded Analytics 1 “ Application like your CRM, ERP, marketing automation, and/or financial systems ” 2 “Bring additional awareness, context, or analytic capability to support decision- making related to very specific tasks”
- 8. ● Limited reach within organization ● Pre-defined analytics ● Information Silos Business Intelligence vs Embedded Analytics Traditional Business Intelligence Embedded Analytics ● Longer time to delivery ● Easy to reach customers ● Support Agility ● Ease to use ● Real time operational access ● Stream Analytics within existing applications
- 9. KPMG - KODE (KPMG Online Decision Engines) for Healthcare Embedded Analytics Example MegaStore Portal
- 10. Ways to Approach Embedded Analytics
- 11. Embedded Analytics Maturity Model Source: Logi Analytics Embedded analytics report(2016)
- 12. Let’s Understand Maturity model Independent GPS device Embedded GPS Navigation Integrated Functionality GPS as a core Component Stage 0 Stage 1 Stage 2 Stage 3 When to Use: • Product has no business UI e.g.: Google Analytics When to Use: • When users have sophisticated analytics needs and/or the competition’s analytics implementation is mature When to Use: • When users demand easy and frequent access to analytics. • Analytics shares the same look & feel as the core application UI When to Use: • You’re working with hybrid architectures • Analytics is a distinct offering that customers purchase separately
- 13. Embedded Analytics is the future of Business Intelligence
- 14. Why Embedded Analytics? 2 Improve User-Experience 3 Reduce Ad Hoc Support Requests 5 Increase the value of hardware or create packaged offerings 6 As it provide analytical solution into existing application, so no need to go to other application for Analytics 1 Create competitive differentiation 4 Enhance cost saving and improve efficiency
- 15. Want Analytics embedded inside application they use everyday. Stats Source: Logi Analytics Embedded analytics report 87% Embedded Analytics is Preferred Driving Revenue with Embedded Analytics Median value of how much they charge on top of their core offering. 24% Up from 15% in 2014 of commercial ISVs and SaaS providers say Embedded Analytics has helped them increase revenue 93%
- 16. In Forrester’s 2013 Global Tech Market Outlook report, Forrester explains that software companies looking to deliver analytic capabilities should not rely on general business intelligence tools, since these tools often require users to create their own reports, which doesn’t help them to work smarter. Enter embedded analytics, where software companies take care of “the last mile.” Trends Driving Embedded Analytics
- 17. Trends Driving Embedded Analytics(contd.) Factors responsible Increased Data Volume, Velocity & Varity Consumer Apps that utlize Analytics Data in the Hands of Novice Users
- 18. Adoption of Embedded Analytics: Overall Adoption of BI/Analytics: Embedded Analytics is Expanding Source: Logi Analytics Embedded analytics report Today In 1-2 years 43% 52% 22% Adoption of embedded analytics doubles that of traditional BI
- 19. Assess the Market 1. Are your customers asking for analytics? 2. Are your competitors offering analytics? 3. Will you customers pay more for analytics? 4. Can you grow your total addressable market? 5. How ready are you today to support an analytics initiative?
- 20. What else in this Summit
- 21. Q&A Thank You