Getting Started with BI Analytics on HANA


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Dickinson + Associates hosted an ASUG Affiliate Webinar entitled "Getting Started with BI Analytics on HANA." Rob Jerome and Tim Korba presented alongside John Zwack, Senior Channel Development Director at SAP.

This webinar introduced attendees to the power of SAP BI Analytics on SAP HANA. A few things you can take away from the webinar slides:

• Overview of the HANA Enterprise architecture
• Integration touch points with SAP systems
• Direct integration with the BI 4.0 suite of analytical solutions
• Introduction to development concepts of HANA Studio, focusing on schemas, analytical and calculation views

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  • Getting Started with BI Analytics on HANA

    1. 1. 1 Getting Started with BI Analytics on HANA August 28, 2013 With: • Rob Jerome (Dickinson + Associates) • John Zwack (SAP) • Tim Korba (Dickinson + Associates)
    2. 2. SAP HANA Faster, Simpler, Smarter John Zwack Sr. Director Platform & Analytics Alliances
    3. 3. © 2013 SAP AG. All rights reserved. 3 Real-time Operational Intelligence is the new frontier Window of opportunity to lead your way Social In-memory Cloud Mobile Real-Time Empowerment Consumerizatio n of IT Big Data Sensing and Responding Sentiment Intelligence Predictive Analytics Personalized Insights Real-Time Analysis New Signals ?
    4. 4. © 2013 SAP AG. All rights reserved. 4 Customer Service Risk Management Team Finance and Operations Account Administration Executive Management Customers Channel Suppliers Accounting ForecastingInventory Products Pricing Planning Vision across entire business process is a must Legacy of stove-piped fragmented operational data views OLAP DB OLTP DB
    5. 5. © 2013 SAP AG. All rights reserved. 5 Your Reality with SAP HANA Groundbreaking In-Memory Innovations 300x Faster Analytics ??? Real-Time Access to Transactional Data Scale Speed Flexibility
    6. 6. © 2013 SAP AG. All rights reserved. 6 SAP’s In-Memory Data Management innovation Providing real-time platform for enterprise analytics & applications A common Database Approach for OLTP and OLAP using an In-Memory Column Database Hasso Plattner Transactions + Analysis directly in-memory VS Transact Analyze Accelerate SAP In-Memory cacheETL
    7. 7. © 2013 SAP AG. All rights reserved. 7 Delivering across all dimensions of information processing End-to-end support on a single unified platform Broad Deep High Speed SimpleReal-Time Complex and interactive questions on granular data Big data, many data types Fast response- time, interactivity No data preparation, no pre-aggregates, no tuning Recent data, preferably real-time Tweets
    8. 8. © 2013 SAP AG. All rights reserved. 8 Enabling real-time operational intelligence across business processes  Accelerate business decisions  Automate decisions and responses  Innovate business processes  Lower TCO SAP HANA
    9. 9. © 2013 SAP AG. All rights reserved. 9 SAP HANA Live for SAP Business Suite The operational analytics engine for best-run businesses Derive new business value with the most proven and modern suite of applications Empower people to decide and act in the business moment Simpler Drive your business at the speed of the market Faster Unlock new growth opportunities before your competitors do Smarter
    10. 10. © 2013 SAP AG. All rights reserved. 10 The information in this presentation is confidential and proprietary to SAP and may not be disclosed without the permission of SAP. This presentation is not subject to your license agreement or any other service or subscription agreement with SAP. SAP has no obligation to pursue any course of business outlined in this document or any related presentation, or to develop or release any functionality mentioned therein. This document, or any related presentation and SAP's strategy and possible future developments, products and or platforms directions and functionality are all subject to change and may be changed by SAP at any time for any reason without notice. The information in this document is not a commitment, promise or legal obligation to deliver any material, code or functionality. This document is provided without a warranty of any kind, either express or implied, including but not limited to, the implied warranties of merchantability, fitness for a particular purpose, or non-infringement. This document is for informational purposes and may not be incorporated into a contract. SAP assumes no responsibility for errors or omissions in this document, except if such damages were caused by SAP´s willful misconduct or gross negligence. All forward-looking statements are subject to various risks and uncertainties that could cause actual results to differ materially from expectations. Readers are cautioned not to place undue reliance on these forward- looking statements, which speak only as of their dates, and they should not be relied upon in making purchasing decisions. Legal disclaimer
    11. 11. Thank You! Contact information: John Zwack Sr. Director Platform & Analytics Alliances 303-350-7038
    12. 12. 12 Getting Started with BI Analytics on HANA August 28, 2013
    13. 13. 13 Agenda  HANA Overview  HANA Integration with BI Analytics tools  Implementation and Deployment Options  HANA Implementation Components  Development Demonstration  Questions
    14. 14. 14  “ Big data will spell the death of customer segmentation and force the marketer to understand each customer as an individual within 18 months or risk being left in the dust “ – Ginni Rometty, CEO, IBM  “Being locally relevant has always been the core of success in retailing, going back 100 years to the town general store whose owners knew what their customers wanted, liked and would like to try. Social is like the ultimate customization vehicle, giving us back the local relevance we had lost in trying to get scale and lower cost. It makes that era of 100 years ago really possible again.” – Stepen Quinn – CMO, Walmart  “ It used to be top down. Where companies would go out and conduct a survey and collect data. Now we are walking around with devices that log everything we like, picture we take, store we visit. You don‟t have to go out and find data. It is now coming and finding us. “ – Jake Porway – National Geographic
    15. 15. 15 What is SAP HANA?  SAP HANA is a data source agnostic database  In Memory Analytics  Historical View  TREX, Live-Cache, BWA (NetWeaver)  Real-Time Data  Operational (ECC or Custom)  SAP NetWeaver BW on HANA (near real-time)  Predictive and Text Analysis  Big Data  Large volumes of data  Structured and Unstructured
    16. 16. 16 SAP HANA Is not..  Reporting Tool  BI Suite is the presentation layer for SAP  ETL Tool  SAP Business Objects Data Services or other ETL tool needs to extract, transform and load the data into HANA  Data Modeling Tool  SAP HANA Studio  SAP Information Composer  SAP HANA is not BW  SAP HANA is not another functional module of ERP
    17. 17. 17 SAP HANA on AWS Architecture
    18. 18. 18 SAP HANA and Integration with end users
    19. 19. 19 HANA Implementation Options  3 primary architecture options:  HANA Standalone  New HANA installation (acts as appliance solution)  Variety of source options  Resolves a specific solution or multiple solutions  AWS  BW on HANA  Improve performance of current BW system  Create a secondary BW system that runs on HANA for specific solutions  SAP Business Suite on HANA  ERP solution  Possible future merge OLTP and OLAP solutions
    20. 20. 20 HANA Deployment Options  On Premises HANA  Appliance on premises  Cloud  AWS  SAP HANA One  SAP HANA One Premium  SAP HANA Developer  Pay as you go  SAP Enterprise Cloud  BW on HANA  Business Suite on HANA  HANA Standalone
    21. 21. 21 SAP HANA - Modeling  Overview  Definition of Tables and Views  Attribute, Analytical and Calculation Views  New terminology (attribute, measure)  SAP HANA Studio  Central SAP Developer tool  Administration of the data model  Information Composer  Easy to use Web based interface  Power Users  2 main functions, Upload and Compose
    22. 22. 22 SAP HANA – Extraction, Transformation, Loading  4 Main Data Provisioning tools  SLT – SAP Landscape Transformation Tool  ERP Integration – real time  Non-SAP data – near real-time  SAP Business Objects Data Services  SAP acquired during Business Objects acquisition  Non SAP and Non BW systems  Sybase Replication Server  Real-Time replication  No Transformations  Direct Extractor Connection(DXC)  Leverage BW DataSources from ECC  Microsoft Excel Flat Files
    23. 23. 23 SAP HANA – Presentation Layer  SAP BusinessObjects  Dashboards (Xcelsius)  Web Intelligence  Explorer  Analysis  Design Studio  Crystal Reports  Lumira  BI Launch Pad - Portal  Presentation Layer Connectivity  JDBC vs. ODBC
    24. 24. 24 SAP HANA Stand alone Implementation Example Steps  Determine Deployment option  Determine SAP HANA size and attain licenses  Determine presentation BI Tool and attain licenses  SAP HANA installation and build  Model SAP HANA  Identify and configure ETL tools  Build presentation layer  Release to end users
    25. 25. 25 SAP HANA Use Case  Social Media  Millions of records that occur daily  How can we harness this type of data and what value can be received by it?  What is the ROI from social media marketing?  Who are the people that are interacting with our social media content, websites, etc…  What type of products are doing the best and what user community is that focus group?  Do we have seasonal products and what are they?  Real time sentiment – who likes and who does not like the product, post or comments?
    26. 26. 26 SAP HANA on AWS Architecture for Demo
    27. 27. 27 Demo: Getting Started with SAP Analytics on HANA  SAP HANA AWS – Standalone  SAP HANA Studio – Modeling  How to create a table  How to create views (attribute and analytic)  Microsoft Excel Flat Files – ETL  How to load a flat file  SAP Business Objects WEBI – Presentation  How to create a simple Web Intelligence report  SAP BI Launch Pad – Portal  Execute report  Simple navigation
    28. 28. 28 Demo: Getting Started with SAP Analytics on HANA  Dickinson + Associates interacts in the following social media mediums:  Facebook  Twitter  Linked In  Dickinson + Associates would like to understand the following metric:  „Social Connections‟ by Age Group and Demographic  Subscription = Follow, Like, Subscribe  3 separate pages for each social media medium
    29. 29. 29 Demo: Getting Started with SAP Analytics on HANA
    30. 30. 30 SAP HANA Other Considerations  Predictive Analytics  Predict future results  Uses historical and real-time data  Compare relationships, trending  Identify anomalies, forecasting  Business Planning and Consolidation (BPC)  Leverages SAP NetWeaver BW on HANA  Text Analysis  Social Media likes/dislikes, etc…  Medtronic  RDS Solutions and Accelerators for ERP and BI
    31. 31. 31 Recommended Material  Fall 2013 free course   More information on SAP HANA 
    32. 32. 32 Dickinson + Associates Tim Korba Lead Architect, Business Intelligence 216-577-9676 @tim_korba Robert Jerome Director, Business Intelligence 703-851-1198 @rob_jerome
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