Your SlideShare is downloading. ×
  • Like
SAP HANA & HADOOP Implementation - Predictive Analytics – CPG and Retail on Unstructured (Social Media) & Structured Data (SAP COPA)
Upcoming SlideShare
Loading in...5
×

Thanks for flagging this SlideShare!

Oops! An error has occurred.

×

Now you can save presentations on your phone or tablet

Available for both IPhone and Android

Text the download link to your phone

Standard text messaging rates apply

SAP HANA & HADOOP Implementation - Predictive Analytics – CPG and Retail on Unstructured (Social Media) & Structured Data (SAP COPA)

  • 2,272 views
Published

• Objective of this demonstration is to provide enough functional and technical details about our pre-configured SAP HANA enabled predictive analytics on SAP COPA and social media data - “Big …

• Objective of this demonstration is to provide enough functional and technical details about our pre-configured SAP HANA enabled predictive analytics on SAP COPA and social media data - “Big Data”

• In this demonstration we will be presenting the out of the box analytics capabilities of SAP HANA. Viewers will learn on how our pre-packaged solutions will cut-down the implementation time, and risk with low predictable cost

• An ideal Advanced Analytics solution should have the capability to extract business values from unstructured information and convert that into actionable insight. We will show how to analyze and integrate an un-structured social media data to provide valuable insight on customer behavior and sales trends. All these on our hosted solutions over an Amazon cloud infrastructure

• Our readily deployable solutions uses the new features of SAP HANA 1.0 SPS5 including the new Text Analysis engine for entity extraction (for example persons, locations, products), and "Voice of Customer" fact extraction (for example sentiments, requests, topics)

Published in Technology , Business
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Be the first to comment
No Downloads

Views

Total Views
2,272
On SlideShare
0
From Embeds
0
Number of Embeds
0

Actions

Shares
Downloads
104
Comments
0
Likes
1

Embeds 0

No embeds

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
    No notes for slide

Transcript

  • 1. BIG Data Implementation Predictive Analytics – CPG and Retail on Unstructured (Social Media) & Structured Data (SAP COPA) SAP HANA & HADOOP Implementation Jothi Periasamy Chief SAP HANA Architect and Big Data Scientist
  • 2. Predictive Analytics – CPG and Retail on Unstructured (Social Media) & Structured Data (SAP COPA) An Accelerated SAP HANA & HADOOP Implementation Executive Summary • Objective of this demonstration is to provide enough functional and technical details about our pre-configured SAP HANA enabled predictive analytics on SAP COPA and social media data - “Big Data” • In this demonstration we will be presenting the out of the box analytics capabilities of SAP HANA. Viewers will learn on how our pre-packaged solutions will cut-down the implementation time, and risk with low predictable cost • An ideal Advanced Analytics solution should have the capability to extract business values from unstructured information and convert that into actionable insight. We will show how to analyze and integrate an un-structured social media data to provide valuable insight on customer behavior and sales trends. All these on our hosted solutions over an Amazon cloud infrastructure • Our readily deployable solutions uses the new features of SAP HANA 1.0 SPS5 including the new Text Analysis engine for entity extraction (for example persons, locations, products), and "Voice of Customer" fact extraction (for example sentiments, requests, topics) Jothi Periasamy Chief SAP HANA Architect & Big Data Scientist (916)-296-0228 JoeSaran@gmail.com
  • 3. Predictive Analytics – CPG and Retail on Unstructured (Social Media) & Structured Data (SAP COPA) An Accelerated SAP HANA & HADOOP Implementation Our Solution Reference Architecture Jothi Periasamy Chief SAP HANA Architect & Big Data Scientist (916)-296-0228 JoeSaran@gmail.com
  • 4. Predictive Analytics – CPG and Retail on Unstructured (Social Media) & Structured Data (SAP COPA) An Accelerated SAP HANA & HADOOP Implementation Our Solution Flow Jothi Periasamy Chief SAP HANA Architect & Big Data Scientist (916)-296-0228 JoeSaran@gmail.com
  • 5. Predictive Analytics – CPG and Retail on Unstructured (Social Media) & Structured Data (SAP COPA) An Accelerated SAP HANA & HADOOP Implementation Our Pre-Configured Analytics • Sentiment Analytics • Customer Rating Analysis • Customer Feedback Analysis • Customer Segmentation Analysis • Product Comparative Analysis • Competition Analysis • Revenue Predictive Jothi Periasamy Chief SAP HANA Architect & Big Data Scientist (916)-296-0228 JoeSaran@gmail.com
  • 6. Predictive Analytics – CPG and Retail on Unstructured (Social Media) & Structured Data (SAP COPA) An Accelerated SAP HANA & HADOOP Implementation Social Scorecard and Sentiment Analysis Jothi Periasamy Chief SAP HANA Architect & Big Data Scientist (916)-296-0228 JoeSaran@gmail.com
  • 7. Predictive Analytics – CPG and Retail on Unstructured (Social Media) & Structured Data (SAP COPA) An Accelerated SAP HANA & HADOOP Implementation Customer Feedback and Rating Analysis Jothi Periasamy Chief SAP HANA Architect & Big Data Scientist (916)-296-0228 JoeSaran@gmail.com
  • 8. Predictive Analytics – CPG and Retail on Unstructured (Social Media) & Structured Data (SAP COPA) An Accelerated SAP HANA & HADOOP Implementation Product Comparative and Competition Analysis Jothi Periasamy Chief SAP HANA Architect & Big Data Scientist (916)-296-0228 JoeSaran@gmail.com
  • 9. Predictive Analytics – CPG and Retail on Unstructured (Social Media) & Structured Data (SAP COPA) An Accelerated SAP HANA & HADOOP Implementation Sales Volume Forecasting and Analytics Jothi Periasamy Chief SAP HANA Architect & Big Data Scientist (916)-296-0228 JoeSaran@gmail.com
  • 10. Predictive Analytics – CPG and Retail on Unstructured (Social Media) & Structured Data (SAP COPA) An Accelerated SAP HANA & HADOOP Implementation Revenue Predictive Analytics Jothi Periasamy Chief SAP HANA Architect & Big Data Scientist (916)-296-0228 JoeSaran@gmail.com
  • 11. Predictive Analytics – CPG and Retail on Unstructured (Social Media) & Structured Data (SAP COPA) An Accelerated SAP HANA & HADOOP Implementation Real-Time Twitter Feeds Jothi Periasamy Chief SAP HANA Architect & Big Data Scientist (916)-296-0228 JoeSaran@gmail.com
  • 12. Predictive Analytics – CPG and Retail on Unstructured (Social Media) & Structured Data (SAP COPA) An Accelerated SAP HANA & HADOOP Implementation SAP COPA and GL Financial Posting Jothi Periasamy Chief SAP HANA Architect & Big Data Scientist (916)-296-0228 JoeSaran@gmail.com
  • 13. About the Innovator Jothi Periasamy Chief SAP HANA Architect & Big Data Scientist Recent Clients    Industry Focus   Jothi Periasamy is a national practice director and global innovation leader at KPMG’s big data and analytics practice. Jothi has deep “hands-on” subject matter expertise in big data, predictive analytics, cloud technology and in-memory computing. Jothi has around 17 years of expertise in SAP, and his expertise includes project delivery, practice development, thought leadership and sales & pre-sales. He specializes in several industry processes including finance transformation, retail, point of sales, smart grid analytics, performance improvements and data governance. He focuses on creating client opportunities and values through business analytics, planning, forecasting, and cost allocation, profitability and cost management, activity based costing, and management/statutory reporting. Jothi’s most recent experience includes working with clients on global big data driven analytics implementation initiative to develop a worldwide rollout strategy and deployment plan, enterprise reporting architecture, data management and governance framework. Jothi works very closely with organizational senior leaders, business process owners to develop an approach, methodology, and accelerators to standardize data and analytics process across enterprise. Jothi has been regarded by fortune 500 company CIO’s and CFO’s as a world’s best data and analytics subject matter resource (SMR) and delivery expert. Jothi has written numerous articles on finance, and SAP (BI,EPM,EIM,HANA), and he has been engaged on several speaking engagement at various industry conferences and events, including SAP reporting and analytics, AICPA, SAP Insider, SAP TechEd, BPC bootcamp, Oil & Gas, Retail and global Power & Utility events Key Accomplishments: Project Delivery: Employment History         Four(4) Cloud implementation Three(3) Big Data implementation Two(3) SAP HANA implementation Seven(7) SAP BPC full lifecycle implementation Ten(10) SAP BOBJ full lifecycle implementation Ten(10) SAP BI/BW full lifecycle implementation Seven(7) EIM (Enterprise Information Management) Implementation Three(3) enterprise portal solution implementation
  • 14. About the Innovator Jothi Periasamy Chief SAP HANA Architect & Big Data Scientist Publications Big Data and Analytics Innovation:       Speaking Engagements  SAP HANA Book, In the process of publishing a Big Data use case book, titled “SAP HANA for Financials” through SAP press. Predictive Analytics, Designed and developed SAP HANA financial predictive analytics solution to predict financial performances in real-time. Advanced Analytics, Integrated structured and unstructured data using SAP HANA and HADOOP platform for SAP COPA based advance analytics. Driver Based Analytics, Designed and developed a financial planning, budgeting, and real-time forecasting solutions called “Driver Based Performance Management”. Financial Fast Close, Designed and deployed a SAP BPC financial consolidation (Investment & Intercompany) solutions across 53 countries and 19 currencies Smart grid Analytics, Architected and developed Smart grid analytics solutions on SAP HANA, AIM and MDM platform to process massive volume of energy data in real-time. Accelerators, Developed tool kits to accelerate client engagements and solutions development. Leadership Accomplishments:    Training  Strategy Management – Worked collaboratively with stakeholders to establish a business driven vision for the future of data management and information technology systems, processes and a roadmap to achieve that vision Project Management – Acted as both a technical contributor to key initiatives and portfolio manager for all data management and analytics projects; ensure support transition. Engagement Management – Internal champion of data management/governance/risk to peers and partners in IT and business management groups; develop and maintain strong external perspective to keep up with new developments in the industry leading practices. Staff Management – Direct people manager for project and operations staff, overseeing team performance, providing coaching and mentoring to the team regarding accountabilities and longer-term career planning; owns rewards, financial benefits and ranking for the team perspective to keep up with new developments in the industry.