SAP Analytics. Blaž Zabukovec SAP

Transcription

1 SAP Analytics Blaž Zabukovec SAP

2 Analytics and this is what we do! Quiz: What is the difference between EFFICIENCY and EFFECTIVENESS? With our Analytics portfolio, we help companies and organizations run their business more EFFECTIVELY! 3

3 Agenda The Scope of Today s workshop Challanges Analytics Information presentation Planning, forecasting & cons. The Workshop 4

4 The importance of measuring 5

5 Our business environment is changing Elevating the strategic importance of Analytics Dynamic markets driving data-driven business Advanced information needs becoming mainstream Increasing competition and rapidly changing industries New business models and revenue opportunities Pressure on margins; more demanding customers New information sources driving data explosion Online interaction and cloud computing Social media and digital communication Mobile devices and location information Machine and sensor data Technology innovation driving new IT Lower hardware cost, lower storage cost Faster CPU and memory New data storage and processing architectures 6

6 Analytics General

7 Information Requirements Operational Strategic Regulatory 8

8 Competitive Advantage Analytics Maturity Sense & Respond Predict & Act Optimization Raw Data Cleaned Data Standard Reports Ad Hoc Reports & OLAP Generic Predictive Analytics Predictive Modeling Why did it happen? What is the best that could happen? What will happen? End-to-end Easy adoption Fast implementation Business focused Enable storytelling What happened? Analytics Maturity 9

9 Reporting (width) Analytics: Content Creators and Content Consumers High Pixel-perfect reports Standard reports Stakeholders (Clients, Suppliers, Shareholders) Dircetors, Management, Employees Consumers IT Developers Dashboards Advanced Users Advanced users OLAP, Excel, AdHoc Query, Analysis Analysts Analysts Creators Data Scientists Forecasting, Statistics, Predictive Low Analysis (depth) High Source: Wayne W. Eckerson, Performance Dashboards 10

10 Analytics Use Case Personas

11 SAP Analytics solutions Agility for analysts Agile Visualization Advanced Analytics Instant insight for decision makers Enterprise Business Intelligence Trust and scale for IT 12

12 Analytics Use Cases High Level View Agility Data Discovery Analyze and visualize data from multiple sources Data analysis and visualization in Microsoft Excel Self Service exploration and analysis of corporate data Dashboards and Apps Enable end users to compose their own interactive dashboards from predefined components Interactive BI applications with a highly visual, interactive user experience Interactive, professionally authored dashboards for executive consumption Interoperability Sharing Security Scalability Reporting Standards Self service query and reporting Publish reports to a dynamic list of recipients Highly formatted reports like invoices, purchase orders 13

13 SAP Analytics Solutions Optimized for Different Use Cases, Yet Interoperable Professionally Authored Where there is a significant complexity to the BI content Standardized formats, sophisticated design, complex data mashups, or high levels of governance. Separates the creation environment from the consumption environment. Interoperability Data Discovery Agile Visualization Professionally Authored Dashboards and Apps Reporting Interoperability Self Service Self Service Not a product, but a way of working with software Business user, analyst, or executive answering their own questions Mobile or web based self service Combines the creation and consumption environment into a single seamless experience 14

14 Dashboards

15 Dashboarding Definition (by Stephen Few): A dashboard is a visual display of the most important information needed to achieve one or more objectives; consolidated and arranged on a single screen so the information can be monitored at a glance. 16

16 Visualization and presentation of quanitative information Hey, this is simple, everybody knows how to do this. Underestimated in terms of required time. Nobody pays extra attention, because: consultants/vendors are saying it s just drag and drop, we run out of resources (for example, after a lengthy( ) data warehouse implementation project), we run out of time. 17

17 What is the most visible object in this dashboard? 18

18 What can you read from the visualization bellow? QTD SALES Americas Asia Europe Sales 19

19 Implementation of reporting/visualization standards Few* is more Decoration/design (graphs, tables, shapes, colors, fonts) Used objects (graphs and tables): design, types, which object to use in which scenario (ACT vs. PLN, time series, ranking, etc.), marking/ highlighting the meaning of red, yellow and green color Used terminology: abbreviations, time (also relative like YTD, PYTD), scenarios, alerting, units. *Reffering to the visualization guru Stephen Few 20

20 We have to be carefull, what we put in front of users A Christmas Tree Design Lean and Usefull Design 21

21 Dashboarding Definition (by Stephen Few): A dashboard is a visual display of the most important information needed to achieve one or more objectives; consolidated and arranged on a single screen so the information can be monitored at a glance. One page report Visual display of quantitative information/kpis Data visualization Dashboard forces user to TAKE ACTION Dashboard offers CLEAR OVERVIEW of our business Dashboard is CONNECTED to other analytical content 22

22 A game of numbers Time consumption while working with infos Dashboard Christmas tree VS. Dashboard Few is More Assumptions: Average gross salary of SLO managers in 2012 was cca yearly (source: Dnevnik). Number of working days/year: 350. Working day duration = 10h. Three board members. Time consumption working with Christmas tree = 15min daily. Time consumption working with Few is More =3min daily. Calculation ( ): Christmas tree =1,267 *15min*350*3= Few is More =1,267 *3min*350*3= DIFF=

23 SAP Digital Boardroom Vision 24

24 SAP Digital Boardroom Reality 25

25 Reporting

26 Reporting What do we do? Quickly build formatted reports on any data source Securely distribute reports both internally and externally Minimize IT support costs by empowering end users to easily create and modify their own reports Enhance custom applications with embedded reports 27

27 Data Discovery

28 Data Discovery The fact is today we have an information driven market where business users prefer access to data discovery tools that enables them to quickly query and understand data Data Discovery Filling the gap created by traditional BI: Business driven Provides Ease of Use and Flexibility in the hands of the business user Allows interactive and sophisticated Visualizations 29

29 What End-Users really want Self-Service - What if? Local files Copy from clipboard SAP BW and BI 4.1 What if you could bring data in local files in your analysis? What if you could copy data from your clipboard in your analysis? What if you could connect to SAP BW BEx Queries and BI Universes? What if you could create new groups and hierarchies in your analysis? What if you could easily build visualizations and put it together in one view? What if you could create compelling Infographics to tell a story? What if you could analyze your data online and offline and on any device? Prepare data Visualize information Infographics Online, Offline & Any Device 2015 SAP SE. All rights reserved. 30

30 Data Discovery What do we do? Access, cleanse, and combine data from multiple sources Discover patterns, trends and outliers Tell your story with visualizations and analytics Answer any business question from a browser or mobile device Optionally provide a layer of security and governance for added trust 31

31 Data Management Perception

32 Analytics vs. Data Management (business view) Dashboards Reports Ad- Hoc Analysis Data Discovery Data Integration Data Cleansing Data Transformation Data Quality Master Data Management 33

33 Analytics vs. Data Management (realistic view) Dashboards Reports Ad- Hoc Analysis Data Discovery Data Integration Data Cleansing Data Transformation Data Quality Master Data Management 34

34 Data Management Situation

35 Semantic Wall Situation today: OLTP and OLAP separated, one-way streets only OLTP- System of Records: Information in only OLAP - System of Engagement: Information out only No write-back No real-time reporting Relational table design Data replication: Usually not real-time, long-running ETL-Jobs (Extraction-Transfer-Load) Redundant data storage

36 Effort for implementation, training, The Spectrum of Analytics Use Cases was separated as well Reports using generic BI-clients Pixel-perfect report Multi-dimensional report Dashboards (in-place) MS Office Planning Application Simulation Application Operational/ transactional Planning Insight-to-Action and decision support Decision automation and exception handling Analytical Apps with specific logic and UIs Simple List Read-only Planning/Simulation (writing data to non-operational stores) Write operational/transactional data

37 But in reality, business processes are often a sequence of transaction analysis transaction Enter Order Create new employee master data Check Customer Churn Probability Analyze yield and scrap of plants Check updated salary projection for cost centers Adjust discount percentage Send to all plant managers above/below certain thresholds

38 SAP HANA as a Database OLTP and OLAP together Transaction s Traditional: OLTP andolap Separate ETL 24hr Old Data Transaction s Stream s OLTP + OLAP in SAP HANA Multiple Data Sources ETL Smart Data Access Stream s 10:00AM StagingDB ETL 24+ Hours Lots of separate ETLprocesses! 10:00AM Multiple Data Sources available with Live Access 10:00:00 AM Immediate 10:00:00 AM Simplified: Eliminates staging DBs or intermediate calculation, aggregates and storage Accelerated: Pure-memory performance for real-time access and applications Internal

39 SAP HANA, the great simplifier of enterprise software SAP HANA SAP Business Warehouse powered by SAP HANA SAP Business Suite powered by SAP HANA SAP Simple Finance powered by SAP HANA In-memory platform Real-time analysis Real-time reporting Real-time business OLAP and OLTP together SAP HANA Enterprise Cloud for SAP Business Suite on SAP HANA Instant financial insight No aggregates Single source of truth Simplified data model New user experience Advanced processing Choice of deployment Internal

40 The Built-in Analytics Vision for S4/HANA User Experience Consuming Analytics Use Cases through tightly embedded Analytics in application UI (example) Consuming Analytics Use Cases through stand-alone BI-Tools Simple List Pixel-perfect report Multidimensional reporting KPIs/ Dashboards In-place MS Office Simple List Pixel-perfect reporting Operational/ transactional Planning Planning Application Simulation Application Operational/ transactional Planning Decision support Apps Rule-based decision automation and exception handling Multi-dimensional report KPIs/ Dashboards Decision support Apps MS Office Planning Application Simulation Application Rule-based decision automation and exception handling Consistent Analytical Features, independent of built-in or stand-alone Personalization, Sharing/Collaboration, Pivoting, Filtering, Office integration, Insight-to-Action, Navigation, Role-based access, Printing, Virtual Data Model HANA Platform Specific Models (Analytical Queries, Search Models, ) One Semantic Model For Search, operational and analytical processing Application Tables Customer Extensions Customer Extensions External Sources / IOT

41 Data Management Data Warehouse, Data Integration, Data Quality, Master Data Governance

42 E2E Target Architecture - Example Data Sources EIM Next Generation BI Clients Enterprise BI Predictive Analysis Advanced Analytics Analytics on SAP HEC Planning SAP Enterprise data SAP LT Replication SAP BW 7.4 on HANA Non-SAP Enterprise data Social,Weather, Demographics, CPI Index, other 3 rd Party Data Smart Meter Data Streaming (Meter, Sensors, Logs) SAP MDG SAP Information Steward & Data Services SAP ESP Near Line Storage DSO DSODSO BW Schema Extended/Near Line Storage for BW and HANA Sybase IQ SAP HEC SAP IQ on HEC HANA Engines (Predictive, Planning, R-Integration, Text) Agile & Operational DataMarts Virtual access Smart Data Access or data transfer Low Cost Storage Table View HANA Schema Virt. Table Lumira server Historical Data, Offline Batch Processes, Model Training etc. SAP HEC

43 The Workshop SAP Lumira

44 Thank you! Presentation contact Blaž Zabukovec Jaka Črnivec SAP Presales, Analytics SAP University Alliances 2015 SAP AG. All rights reserved.

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