Best practices in HANA implementations - real client experience

Transcription

1 Best practices in HANA implementations - real client experience Penny Silvia, IBM June 2013

2 Content The SAP HANA Current Market IBM s Approach to SAP HANA IBM s Experience in SAP HANA

3 SAP HANA is addressing key needs of current leaders

4 Global Trends that are impacting Business Analytics Everywhere Mobility Growth of Social Networks and Collaboration Big Data Increasing pervasiveness of Analytics Everywhere Mobility Social Networks and Collaboration Big Data Pervasiveness of Analytics How do you enable BI for mobility How does that impact access and security? How does this impact your strategy? What new opportunities will arise to exploit BI? How will your clients collaborate differently? What new use cases will develop? How will you take advantage of sources? Can you leverage real time analytics? What is the impact to your architectural strategy? In- Memory? Cloud? How will you embed analytics into your business process? How do you deploy simpler, faster and cheaper? What will self service mean for you?

5 Customer Data Data Repositories Product Data Network Topology Data Change Capture Data Quality / Validity / Security - Privacy Format / Unit Conversion Consolidation / De-duplication Continuous Feed Sources The New Architectural Analytics Framework The new market drivers are driving new analytics architectural requirements to capitalize on the opportunities of integrating the front and back office Big Data Advanced Analytics High Performance Historical analysis (Big Data Platform) Model Based Analytics - behavioral scoring, micro segmentation, correlation detection analysis Real-time scoring, classification, detection and action Visualize, explore, investigate, search and report Take action on analytics Actionable Insight Operational Systems Network Data Streaming Data Sense Analyze Act Usage Data Stream Processing Rules Engine Customer Behavior Data Historical Analysis Data Predictive Model Deployment Marketing Campaigns Behavioral analysis Propensity Scoring End-use Applications Model Creation Outcome Optimization Predictive Analytics Search / Explore Demographics Segmentation Location Past Actions Propensity scores Behaviors Reports Drill-Downs Reference Data Structured / Unstructured Data Dashboards KPIs Data Governance Data Integration ETL Big Data Analytics Warehouse Advanced Analytics Platform Analytics Visualization

6 Game Changer: BusinessSuite on HANA Suite on HANA (SoH) is the latest offering of HANA from SAP, bringing into the mainstream application space for the first time. It follows the launch last year of HANA for standalone applications running in sidecar mode, and of BW on HANA. SoH is in ramp-up currently. ECC, CRM and SCM can run directly on HANA as a database. HANA replaces Oracle, DB2 or MS-SQL as the underlying database software for the SAP application. SoH at the moment has no functional changes or enhancements, but does incorporate some optimization of specific functions to run on HANA (accomplished by re-writing the underlying code to run at the HANA database level, rather than within the ABAP stack in the SAP system). At one level, therefore, use of HANA with SAP Business Suite is a straightforward technical database decision. BUT the differentiating value, comes from the specific optimization of business transactions, and the potential use of HANA as a platform supporting memoryoptimized applications in a range of SAP environments. During 2013 SAP launced SAP HANA Live to provide a logical view of the data structures in a way that is accessible to analytics tools such as Business Objects. SHLive will provide more capability to define and execute both operational and analytical reports directly from the ERP system, without use of BW.

7 Possible Areas of Value for SoH Current situation Client has difficulties with long-running batch processes Analysis is based on summaries, categories and aggregates Reporting is periodic and after-the-fact Data is out-of-date because of latency in populating reporting systems Analysis is based on periodic single runs (e.g. MRP) Reports are used to support transaction processing, providing secondary information Reporting is backward-looking Reports are the main tool for monitoring the business New way of thinking, with Suite on HANA Accelerate batch processing and remove operational problems Analysis can be done at a granular level, by transaction Reporting can be on-demand and immediate Can perform analysis on operational data in SAP ERP Can execute multiple, iterative runs to fine tune analysis Reports aren t needed. Critical analysis can be done in-line, as part of transaction processing Analysis is forward-looking, with predictive analytics enabling modelling and planning The business can monitor itself, looking for key exception conditions, patterns, triggering events and alerts that in turn initiate new processes

8 (REAL) Examples of outcome from HANA-enabled solutions Object Type DSO 2 key fields 0 Navigation attributes DSO 2 key fields 210 Navigation attributes DSO 8 key fields 0 Navigation attributes Test Case Conventional SAP BW 7.3 on Oracle 10 SAP BW 7.3 on HANA 1.0 SP03 Full load of 3.5 mio records from PSA 18 min 3.5 min Activation of 3.5 mio records 34.5 min 0.3 min Activation of 3.5 mio records not tested 2.5 min Full load of 3.5 mio records from PSA 18 min 9 min Activation of 3.5 mio records 38 min 2.5 min Infocube Full load of 1.5 mio records 60 min 12 min Info Object Selective Update of 14.6 mio master data records not possible 90 min SAP BW on HANA will speed up the access to information, with limited investments to the current landscape. IBM has experience in migrating current BW environments to HANA, both technical as functional Also we see clients taking it on as a technical project and clients who use the migration as a opportunity to clean up the data structures in BW, as they typically have grown over the years. The latter get the best results.

9 IBM s Approach with SAP HANA

10 Data Factory Analytical Solutions IBM s Data and Analytics Factory for a Maturity Leap IBM Data and Analytics Factory enables higher reusability and standardization with embedded Leading Practices Path to World Path to World Class Business Analytics Analytics Step Year 1: Data Efficiency Step Year 2: 2: Reporting Mobility & Metrics Step Year 3: 3: Mobility Predictive & Real Insight Time Step Year 4: Predictive Optimization Insight Data Quality Data & Quality Data Visibility & Embedded Real Time Analytics Operational Analytics Real Predictive Time Analytics Algorithms on & device Predictive Embedded Algorithms Analytics & Pattern Information Data Governance, Visibility Use Case Dev Reporting on Device Packs by Facility HANA Pattern Enabled Recognition Used Cases Recognition Process Supply Embedded Chain Optimization Analyticspower by ILOG Cascading Executive Dashboards Executive Dashboards, BDR Embedded Analytics, Self Service Model Real Time Metrics on device, Real time Analytics Powered by HANA Information Consolidation Testing Data Operational Support (COE) Data Governance Data Intelligence Management Data Technology Management of of Master Data Data Process Management Data Services Analytics Services Testing IBM s Data and Analytics Factory offers: Labor Arbitrage applied to Data Management and Operational BI Factory Model allows for maximum allocation of resource capacity Platform standardization allows for higher reusability Cloud based infrastructure Pre-configured IBM content to accelerate capability deployment Standard KPIs, Drilldowns and Benchmarks for accelerated data visibility Industry Use Cases for Real Time reporting Predictive Algorithms for Process Optimization Pre-defined mapping for fast data integration Standard Mobility deployment model

11 IBM Client Center Lab for SAP Solutions (LSS) SAP continues to evolve and extend their application platform in key areas such as mobility, analytics, HANA, and the cloud. These capabilities can drive new business outcomes, but cannot be looked at in isolation. The LSS serves as a focal point for all of IBM s capabilities to enable SAP customers to understand what is possible AND how they can get there. Goals & Requirements Virtual Briefings Clients On Premise IBM Centers Pre-built Assets & Tailored Solutions Programmatic Collaboration with IBM Research Fully integrated mulit-nodal architects Vision, Roadmaps, & Solutions Full SAP Business Objects, Enterprise HANA, BW on HANA, SAP Mobility, SAP ECC, and SAP LOB solutions Integration Production level, multi-node infrastructure powered by IBM Business Analytics & Optimization Services and Solutions Industry Specialists IBM SAP Services IBM Research IBM Global Delivery Centers 11

12 IBM In Memory Solutions through HANA Services 12 Strategy In Memory Analytics Advisory Services/IBM Research HANA Roadmap and Assessment In Memory Workshops and Value Identification services Analytics Mobility Planning Analytics Competency Center/Factory Information Governance Infrastructure Infrastructure Planning Solution Architecture System Optimization/Modernization High Availability and Disaster Recovery Installation Services Hosting & Support IBM Confidential Do Not Disclose Innovate Design Govern Operations Sustain Application Management Strategic Outsourcing Infrastructure Management Data & Analytics Factory Sustain Deploy IBM is the only provider with competencies and experience across the full spectrum from physical transformation layer to algorithm design to ongoing operations Design/Build SAP Mobility & Analytics Innovation Center HANA POC/Pilot/Implementation Visualization and Analytics Design & Development BW Upgrades & HANA Migration Solution Accelerators # 1 Ranked SAP Practice Enterprise Information Management IBM Ready-to-launch Data Governence & Security Data Security Performance Optimization Enhanced Workflow- and Tracking systems Data Modeling Data Provisioning

13 Selective IBM Experience in SAP HANA

14 1. Improving Procurement Analytics through Enterprise HANA Implementation Challenge The client is one of the major US based manufacturer of thin film photovoltaic (PV) modules. Client had performance issues with existing reporting solution and decided to deploy a new solution with enhanced reporting capabilities & improved performance Flexible with changing business requirements Big data & real-time reporting capabilities Detailed line item level reporting The first phase of the project focused on supply chain management. Finance and inventory models are planned in later phases. Solution IBM implemented a scalable in-memory business analytics solution with SAP HANA, BusinessObjects 4.0 and SLT to provides real-time reporting to support key business decisions Solution focused on prioritized business use cases Team structure 1 onsite SME, 3 offshore resources (Technical Architect, HANA Developer & BO Developer) 14 6/19/2013 Function Areas Covered Procurement Analytics - Provide vendor delivery performance - Enhanced variance analysis and detailed procurement analytics - Real-time analysis of goods movement. -Material& vendor master reporting including audit & adhoc reporting IBM India involved in end-to-end implementation of the SAP HANA solution Used Agile Methodology Performance of complex reports in Procurement Analytics and Material/Vendor master has improved remarkably

15 Enterprise HANA Implementation Technical Overview Technical Components ECC (NetWeaver 701 Support Package 135) SLT (NetWeaver 702 Support Package 300) HANA (SP4, Revision Level 41) BO 4.0 (IDT, Web Intelligence and BO Explorer) System Landscape Challenges Faced Complex logic for GR Date and IR Date created through SQL. SQL Script the implementation in HANA context different Single Sign On (SSO) using Kerberos and Windows AD authentication for HANA Data Loading through SLT sometimes stopped, the problem solved through applying SAP notes Lessons Learnt BO Dev BO QA BO Prod DEV QA SAP HANA Prod SAP HANA SLT Dev SLT QA SLT Prod ECC Dev ECC QA ECC Prod SAP HANA is evolving, frequently check SAP Notes for new features and fixes Expert functions in SLT monitoring dashboards do not do everything, housekeeping is required HANA SQLScript Implementation is different compared to other SQL scripting languages, only Read Only procedures are supported in Calculation view Currency Conversion supported only for base measures, calculated attributes and calculated measures are not supported 15

16 Enterprise HANA Implementation Methodology Overview Realization IBM India offshore team involved in every stage Evaluation Preparation Blueprint Detail Desig n Develo p Final Preparatio n Go-Live Hypercare Test & Validat e Methodology used Modified Agile (with discipline) methodology has been adopted Scope finalized during the Blueprint phase Iterative approach followed during the realization phase Master data reporting (3 weeks) Procurement Analytics (4 weeks) Lessons Learnt Perform a complete assessment of the landscape, not just for upgrade or migration but from Data Volume optimization, HA/DR strategy, Archiving Strategy, Reporting Strategy Maintain flexibility in the plan Business transformation and IT should be closely aligned Process knowledge is mandatory for proper HANA modeling

17 Business Analytics is important to First Solar First Solar panels produce power at a cost of $0.75 / watt. This is the ultimate measure of the company s success. Drive down manufacturing costs Use real-time tactical information to drive value Analyze all data sources pertaining to panel performance to maximize output Analyze manufacturing data to glean insights into how yields can be improved and processes optimized Get real-time information related to manufacturing performance by line and by plant, and quickly spot and resolve manufacturing performance problems and implement corrective action Ensure that sales related information is available real-time Empower Finance with the capability of doing rapid variance analysis to quickly understand why costs are higher than expected Improve the overall efficiency through which operational information is disseminated throughout the organization Large volumes of data from services installations must be analyzed to help understand how to maximize power outputs and minimize service disruptions Help predict when failures are imminent Link environmental conditions to panel performance and reliability

18 Several business value cases have been identified SCM Analytics Rapid access to tactical information Enhanced variance analysis and detailed procurement analytics Power Generation Data Analysis Continuous Improvement Analysis Customer Service Enablement Finance Analytics Analyze large volumes of information gathered from the field, pertaining to panel installations Gain an understanding into what conditions affect power output Enable continuous improvement of professionals to perform data analysis against large volumes of manufacturing data quickly and effectively, to drive improved yields and manufacturing efficiency Integrate data from Sales orders, Contracts, Warranties, Rebates, and Manufacturing Gauge the efficiencies in Customer Service, and enable analysis Implement RDS for operational reporting Leverage finance models and bring G/L reporting onto HANA to facilitate faster month-end closing processes BPC Acceleration Accelerate BPC on HANA Project future potential roadmap for FSLR

19 2. Inventory Management Implementation on BW on HANA for a Retailer Challenge UK s leading retailers, few million people visiting their 700 UK stores each week. Products sourced from around 2,000 suppliers globally. Daily data load were about 20 million stock movements. Query runtime for sites was running for couple of hours and Users were not able to run it Refresh of stock position to external systems for all 720 sites were taking 3 to 4 days. Solution BW on HANA implemented for Inventory report with Non Cumulative Key Figures only modelled in Info cubes & HANA Optimized IBM & SAP jointly executed this POC Material Movements loaded into the cube a round 1.3 billion. Reduction of Application Level maintenance - No Performance / Rollup Tabs in the Manage screen. No DB statistics / Index/ Compression Roll Up required. Faster data loads million records from PSA to Info cube 4hours 34 minutes. Faster Standard DSO Activation times. Results All 720 Sites drill down on Non Cumulative Key Figures at site level took 1.24 Seconds on 1.3 billion records. A comparative analysis with BW 7.0 showed 6 times faster APD runs on BW- On-HANA.

20 3.Emergency & In-patient Services Run better in A Spanish Healthcare Scenario details: Business problem: In order to get answers to specific questions that can arise related to one or several healthcare areas, reporting over large tables with high granularity becomes a need for healthcare managers. For this POC, Emergency and Inpatient Services are the two key areas identified where data availability becomes a must in order to grant the best performance at the right time. Proposed Solution: The solution is created on a HANA Enterprise and covers both queries over millions of records and Real-Time Data acquisition. Queries run 85 90% faster Patients diagnosed with diabetes who needed dialysis and were admitted during the last month (60M records) Home hospitalization patients admitted to emergency and destination at discharge is not conventional hospitalization (30 M records) Load incremental data every 30 minutes HANA Dashboard Details for Emergency

21 4. HANA Support for a Medical devices major in USA Client Overview Our client is the world s leading medical technology company, developing products that help patients with a wide variety of chronic diseases. Challenges The CRM-BW project is very critical for the client as the FDA and other regulatory body reports from different countries will be generated by using this data. Multiple SAP and Non-SAP sources used for extracting data both into ECC and BW systems causing heavy duplication and thus adding up to data volume optimization scenarios (point in time 15 Tb data in BW). DSO Activation in Business layer taking lot of time & Reporting performance problems - reports both in ECC and BW taking up to 40 minutes. Solution SAP HANA as Side Car implemented : complex reports in CRM & Global sales reporting area has been improved remarkably. BW on HANA being implemented for some of the problematic reports. IBM is currently supporting their Analytics landscape which includes HANA, BODS and HANA-Admin work. SAP CRM Legacy Data Source BW BODS ETL BODS ETL HANA 1.0 BO Universe BO Reports (WebI, Dashboards)

22 5. Sales Order Reporting Gets Faster on HANA for a leading international paper and packaging group Initial situation Client has BW with BWA on top of four SAP ECC and other 3rd party ERP systems Reporting front end is BOBJ and BW BEx Biggest SAP kernel has extensive reporting in BW and BOBJ Issues ETL processes take a lot of time (night too short) Reporting on critical sales data has a time lag of up to 24 hours Client sales orders are created but results not immediately available for reporting no fast reaction on price changes possible Report refresh takes up to 30 Minutes Solution Phase 1 in IBM Lab copy of productive customer ERP system HANA PoC based on sales data Online replication using SLT PoC based on IBM hardware, and IBM consulting services

23 5. Sales Order Reporting Gets Faster on HANA for a leading international paper and packaging group contd.. Performance Functionality which was done by BW, BW OLAP, MDX Interface and BOBJ Report was moved to HANA DB. Navigation time reduced from up to 30 Minutes to 5 10 seconds Online Data Set up Online replication via SLT for all data needed in HANA Each change in SAP ECC Data is immediately replicated to HANA DB BOBJ reports No impact on ECC performance Compression HANA compresses ECC tables with an overall ratio of 8 10.

24 6.Profitability Analysis for a Canadian Food Processing company Runs in few Seconds on SAP HANA Enterprise Challenge For a mid-sized Canadian food processing company with annual sales of $5.2 Billion. The SAP program at this client consists of a 4.5 year roadmap designed to provide a common ERP-based framework across its Agribusiness, Bakery, and Meat Products groups. 3 years into their program, MLF was still unable to effectively extract profitability information and produce crucial analytical reports. Due to a high volume of records, the existing Business Intelligence architecture was taking nearly a full day to extract the data; often, the system would crash during report generation. With a week s worth of billing documents totaling up to 109 million records, MLF needed a way to quickly extract this data from the system and turn it into valuable business information. Solution As MLF s systems integrator, IBM partnered closely with SAP to deliver the first SAP HANA go-live in Canada in December The pilot implementation extracted profitability and trade spend data from ECC and CRM into SAP HANA and presented this information in a user-friendly manner through BOBJ Web Interface (WEBI). With the enhanced SAP HANA solution, the same information that now takes 6-10 seconds to extract. MLF intends on continuing to partner with IBM and SAP to implement SAP HANA across many other Business Units and reporting areas

25 7. Client Reference SAP HANA POC in collaboration with SAP Background A US-based bank had problems with the BW loading time as well as report performances and wanted to use the SAP BW on HANA capabilities The need was to demonstrate the capabilities and migration context of introducing HANA in the Bank s DB layer with the ultimate purpose of improving performance, scalability and reporting flexibility. IBM Solution / Results As the client s systems integrator, IBM partnered closely with SAP to demonstrate the following successfully in June 2012 Demonstrate performance improvement in data load to BI through the substitution of DB layer through HANA Provide benchmark of effort related to migration from DB2 to HANA based on POC so that Client can have a reliable estimate on overall effort to migrate Demonstrate scalability of HANA solution to a data volume and landscape that is reasonably representative of the Bank s production Demonstrate SLA improvement in data flow source to report Demonstrate reporting capabilities form HANA available through SAP BO Key Findings Loading time decreased by a factor of 5 Reporting time decreased by factor of 48 Solution Components SAP BW on HANA SAP BOBJ /19/2013

26 8. Client Reference SAP HANA PoC in collaboration with SAP Background A major European Automobile manufacturer Over 360 Million Records had been loaded into HANA IBM Solution / Results IBM partnered closely with SAP to execute the HANA POC as well as do HANA Basis maintenance and support It was also done using IBM s Data centre Ca. 356 Million Records are used in and utilized by the Data Model and Explorer shows all Line Items of GLPCA Posted Data was faster replicated into HANA Solution Components 26 SAP HANA 1.0 SAP BO 4 SAP ECC SAP PI SLT 26

27 9. Implementation of SAP HANA at MLF The Company: Maple Leaf Foods (MLF) is a mid-sized Canadian food processing company with annual sales of $5.2 Billion. The SAP program at MLF consists of a 4.5 year roadmap designed to provide a common ERPbased framework across its Agribusiness, Bakery, and Meat Products groups. The Issue: 3 years into their program, MLF was still unable to effectively extract profitability information and produce crucial analytical reports. Due to a high volume of records, the existing Business Intelligence architecture was taking nearly a full day to extract the data; often, the system would crash during report generation. With a week s worth of billing documents totaling up to 109 million records, MLF needed a way to quickly extract this data from the system and turn it into valuable business information. The Resolution: As MLF s systems integrator, IBM partnered closely with SAP to deliver the first SAP HANA go-live in Canada in December The pilot implementation extracted profitability and trade spend data from ECC and CRM into SAP HANA and presented this information in a user-friendly manner through BOBJ Web Interface (WEBI). With the enhanced SAP HANA solution, the same information that now takes 6-10 seconds to extract.

28 Implementation of SAP HANA at MLF (2) The Business Details: This solution is an SAP Business Warehouse (BW) BEx Query and is primarily used to extract invoice sales details from BW for analysis. The end-user reports are extremely flexible and user-friendly with over 90 dimensions to leverage for different views and visualization. The implementation took 15 people and roughly 8 weeks. The Technical Details: Costing, trade, freight, and logistics data comes from ECC and CRM through BW. This data is sourced from BW Data Store Objects (DSOs) and Cubes and goes through BW Open Hub and SAP HANA. The data goes through a Universe and eventually into BOBJ. Reports are static, tabular, and come through WEBI. The WEBI report is used to identify business rules to highlight anomalies and help the end-users easily process the millions of records. This was based upon 21 reports that were identified for the implementation. BOBJ/WEBI (List Invoice and Key Figured) Universe SAP HANA BW Open Hub Data Services MLF intends on continuing to partner with IBM and SAP to implement SAP HANA across many other Business Units and reporting areas. Business Warehouse

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30 From a business perspective HANA enables faster access to data (near real-time) HANA enables access to detailed data (DSO reporting) Performance Improvements Data loading up to 30% faster Reporting (all reports; not just BWA) A positive NPV project lower development costs Support organization and project delivery LSA++ reduces maintenance burden: Fewer objects to maintain compared to standard LSA 30

31 References Recent projects and proof of concepts (for internal use) Use Case The recent acquisition of Carlton United Breweries (CUB) by SABMiller has provided an opportunity for CUB to begin the transition to SABMiller operating practices which require the adoption of global reporting standards. Business Challenge CUB is challenged by existing legacy assets that are under performing with a relatively high cost of ownership and significant complexity across its financial reporting. Move key business intelligence reporting functions onto the latest SAP Business Warehouse (BW) and SAP Business Objects software running on the SAP HANA inmemory database platform. Solution IBM will be responsible for performing iterative capability builds in the SAP BI (Business Warehouse and Business Objects) on the SAP HANA in-memory database platform. Benefit IBM will add value to CUB's business by providing a Business Intelligence technology and tools platform that is 100% aligned with the SABMiller application roadmap, self -service data mining capabilities and improved report performance with the SAP HANA database. 31

32 32 IBM Confidential