Big Data For Indian SMEs
Small And Medium-sized Enterprises SME Small And Medium-sized Enterprises
Indian SME Sector 50 Million SMEs 40% of India’s workforce SME account for over 37% of India’s GDP
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!
SMEs in India touted to be a $25.8 billion market by 2020!
Problems Faced By Indian SME’s Lack of market intelligence Lack of finance Lack of technology Lack of market intelligence
Emerging technologies will have big impact on $25.8 billion SME market!
Big Data Is For Big Players Only! Myth Big Data Is For Big Players Only!
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.
Big Data is exuberant and takes ages for implementation. Myth Big Data is exuberant and takes ages for implementation.
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
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
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
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).
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!
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
Future Generic and easy to deploy Big Data solutions Rise of managed services Rise of SMEs contribution towards data analytics market