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1 Intelligent Business Operations and Big Data 1

2 What is Big Data? Big data is a popular term used to acknowledge the exponential growth, availability and use of information in the data-rich landscape of tomorrow. Gartner, 2011 < 1% is analyzed < 20% is protected Measure of all the digital data created, replicated and consumed in a single year. 2

3 What is Big Data? Volume: Caused by transaction volumes and other traditional data types, as well as by new types of data. Variety: More types of information to analyze mainly coming from social media and mobile (context-aware). Velocity: How fast data is being produced and how fast the data must be processed to meet demand. While big data is a significant issue, [ ] the real issue is making sense of big data and finding patterns in it that help organizations make better business decisions. Gartner,

4 Relationship between Data, Information, Knowledge and Wisdom I better stop the car Wisdom The traffic light I am driving Knowledge towards has turned red Data Insight South facing traffic light on corner of Pitt and Information George Streets has turned red Red, , v2.0 Meaning Context Is the effective use of knowledge in decision making Is what we understand based upon information Potentially valuable concepts based on data. Raw unorganized facts. Is in and of itself worthless DIKW Pyramid 4

5 Data Mining Intelligent Business Operations Management Support Systeme Business Process Management Process Performance Management Real-time Data Warehouse Big Data Business Intelligence OLAP Complex Event Processing Decision Support Systeme ETL Corporate Performance Management Real-time Analytics Streaming Analytics 5

6 What is the problem? Lack of visibility into the business Opportunities to optimize operations are missed Negative Sentiment Risk Call Details Opportunity Public Safety Alert Risk! External factors directly affect the business Opportunities/ threats are not managed Data is getting faster and bigger Time window to analyze and act is decreasing Many transactional and operational activities that run the business Loyalty Scheme Opportunity CRM ERP Traffic Data! Risk BUSINESS SYSTEMS Location Data Opportunity News Opportunity Weather! Risk 6

7 What is the problem? The Internet of Things In Memory Compute Industrial Internet Location Sensing Wearable Devices Mobility Social Media Streaming Internet Big Data, Fast Data, Process Data, Transaction Data Time window to analyze & act ibpms Event Driven SOA / BPM Distributed Computing Client Server Mainframe 7

8 IBO and the Software AG Vision Intelligent Business Operations (IBO) is a style of work in which realtime analytic and decision management technologies are integrated into the transactional and operational activities that run the business Gartner, March 2011: W. Roy Schulte, Janelle B. Hill, Nigel Rayner We extend the this vision with proactive intelligent execution of right-time actions to seize opportunity or mitigate risk Software AG s IBO both a vision our clients strive towards and a platform that leverages process & business data 8 Gartner s definition focuses on operational effectiveness

9 Why is this relevant? Our customers need to innovate at ever increasing pace to hold back competition and gain market lead They are unable to halt IT operations & business-as-usual activities while this is done IBO allows incremental change to improve business effectiveness while leaving their critical systems running Real-time Visibility Seize Real-time Revenue Opportunities Continuous Optimization Continuously Manage Risk 9

10 IBO: Intelligence Layer On Top of Operations Dashboards & Visualization Proactive Alerts Real-time Decisions Optimize Intelligent Actions PPM Historical Pattern Discovery Streaming Analytics Continuous Analytics Process Analytics In-Memory Data Management & & Connectivity Financial Custom ERP CRM M2M Transactions, Events, Big Data, Process Data 10 The Building Blocks of IBO

11 IBO: Intelligence Layer On Top of Operations 4 IBO combines 1, 2 & 3 to enhance the business with improved decisions and intelligent actions (at speed and scale) 2 BPMS orchestrates and improves activities (aka Processes) 3 However, external factors directly affect these activities 1 transactional and operational activities that run the business CRM ERP BUSINESS SYSTEMS 11 Improved decisions and intelligent action

12 Improve Response Time to Problems & Opportunities Link real-time insights with the right actions Business event Value Data captured Information delivered Action time Action taken Time Source: Richard Hackathorn The BI Watch: Real Time to Real Value 12

13 Observe, decide, act in real-time Traditional BI, statistical analytics, data mining, etc. for historical analysis Reporting Traditional BI and off-line analytics Data Warehouse Ad-hoc BI analytics Strategic and tactical decisions Store data Observe Situational Awareness Data in motion Decide Faster & Better Decisions Running business operations Act Dynamic Actions Improve Source: W. Roy Schulte, Gartner Inc. Intelligent Business Operations 13

14 14

15 Ditching the Disk for unprecedented Speed 90% of Data in Database Memory MODERNIZE 90% of Data in Memory Database App Response Time Milliseconds App Response Time Microseconds 15

16 BigMemory In-Memory Data Management Speed Up Scale Up Scale Out Elastic Scale In the Cloud Increase Data in Memory App Server App Server App Server App Server App Server Ehcache Ehcache Ehcache Ehcache Ehcache App Server Ehcache BigMemory BigMemory Server Array BigMemory Server Array Database Database Database Database Reduce Database Reliance 16

17 17

18 CEP Advantage Difference between Database and CEP based processing Collected Data Event Streams Data goes into the database Analyzed after it is (indexed and) stored Events go through CEP engine Analyzed as they happen Results instantly usable 18

19 Complex Event Processing and Event Stream Processing Streaming Analytics Continuous re-calculations on a continuously moving window of events matching a particular query Transaction Card ID Calculate the sum of the 7 days historical data of all transaction payments for this customer Sum (payment.amount) 7 days Sum of Transaction payments from t in Transaction (card = ID) within (7 * DAY) select sum(t.payment) 19

20 Apama CEP Platform Processing Core: Event Correlator Events are processed by one or more Correlators Logic can be created in Java, EPL or the visual Event Modeler (Scenarios) Events enter a Correlator through a input channel (queue) and exit via a output channel (queue) Correlators host monitors and listeners within a context Monitor / listeners react on events relevant to them Events may be routed to different / multiple context(s) Contexts are used to logically split the processing of events Contexts may be used for parallel processing 20

21 Apama and Low Level Virtual Machine (LLVM) Apama Faster than C and Java Modern CPUs have optimized instruction sets Only code complied for a specific CPU can make use of these instruction sets General purpose C and Java compilation is not aware of the exact CPU + Java has JVM overhead and garbage collection Apama EPL is compiled at run-time to native machine code that is optimised for the exact CPU it executes on Apama EPL executes more instructions per second than C or Java (and therefore any CEP engine written in C or Java) LLVM optimization applies to EPL and Event Modeller Code on Linux since Apama LLVM is wildly used, see: 21

22 Throughput Performance Sneak preview on 5.2 Hardware: 4 * Intel Xeon E74890 v2, 15 cores + HT 22

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