1. Big Data For Indian SMEs

2. Small And Medium-sized Enterprises
SME
Small And Medium-sized Enterprises

3. Indian SME Sector 50 Million SMEs 40% of India’s workforce
SME account for over 37% of India’s GDP

5. Reasons Access to finance Adoption Rise of SME focused B2B ecommerce
Second generation entrepreneurs eager to enhance their revenue by bringing in operational efficiency and transform customer experience!

6. SMEs in India touted to be a $25.8 billion market by 2020!

7. Problems Faced By Indian SME’s Lack of market intelligence
Lack of finance
Lack of technology
Lack of market intelligence

8. Emerging technologies will have big impact on $25.8 billion SME market!

9. Big Data Is For Big Players Only!
Myth
Big Data Is For Big Players Only!

10. Indian SMEs are not ready for Big Data.
Myth
Indian SMEs are not ready for Big Data.
Over the last couple of years, small and mid-size Indian companies have seen more big data deployments than the big competitors.

11. Big Data is exuberant and takes ages for implementation.
Myth
Big Data is exuberant and takes ages for implementation.

12. Why Indian SMEs should adopt Big Data?
Competitive Landscape
Hence essential to have actionable insights and intelligence in business
Emergence of new businesses
dependent on technology
Big Data and Business
Analytics go hand in hand
Big Data can empower SME’s
journey to next level

13. Big Data: Reinventing SMEs Business Processes
Retailers Claiming Business Back
Flubit.com, an online marketplace which generates competitive offers based on interest in a designated product, essentially diverting customers away from Amazon back to small, independent retailers.
The analysis of accounting documents
Properly prepared and interpreted information can bring
profit on every possible level
Data collection, Use of information, Conclusion
Create better marketing campaigns
Hypermarkets perform daily analysis of data on transactions using their loyalty card – for better promotion of specific client segments

14. Industrial Asset Monitoring Using Big Data Business Outcome Expected
Solution Architecture
Reduce the total cost of IoT infrastructure.
Migration to a data store capable of handling large data volume
HBase data store on IBM Cloud
Cloudera 5.4 platform
16.5 million records / hour
Pentaho 5 reporting
Data Lake
Analytics Engine
Reporting Solution
Data Load Engine
R analytics engine
2000 Analytical functions configured
Data quality + business rules
Data streaming from machines
Business Benefits
Scalable architecture for growing business
Oracle license cost saved
Capacity to offer unstructured data analytics to their end clients

15. Leveraging Big Data For Low Cost Data Archival
23000 Tables
50 + Reports
Benefits
Exposure to secure cloud environment.
Translated Business Logic to Simplified tables.
Better performance of Reports and dashboards.
No impact on Business As Usual (BAU).

16. Our Experience As hierarchy is not rigid, decision makers are easy
to approach
CXOs in SMEs are aware of tech trends
Next generation entrepreneurs are more proactive towards tech
They are open to adopt tech!

17. Our Learnings POC Start With Proof of Concept
Solutions should be cost effective
Understand business problem
and focus on pain areas
Usage of Cloud
Agile Method
Become partners rather than
vendors

18. Future Generic and easy to deploy Big Data solutions
Rise of managed services
Rise of SMEs contribution towards data analytics market