BIG DATA AND ANALYTICS

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1 BIG DATA AND ANALYTICS Björn Bjurling, Daniel Gillblad, Anders Holst, Swedish Institute of Computer Science

2 AGENDA What is big data and analytics? and why one must bother Examples of big data for vehicles Summary and take away lessons

3 BACKGROUND: PARADIGM SHIFTS Advances in hardware and computer systems Cheaper storage, faster CPUs, and faster networking Parallel computing, Cloud computing Abundance of data Sensor systems revolution Internet services, Social media Mobility and connectedness Improved Data collection capabilities Data analysis Scale and complexity enable/require new algorithms Success stories Facebook, Google,

4 BIG DATA: MANY CHALLENGES Computations and platforms Hardware / Infrastructure / Data Centers Storage/communication/networking Programming concepts Code/ Compilation/ Scheduling Algorithms Scalability Complexity Decentralization Time requirements Data analysis Representation / Modelling Domain knowledge Visualization Deployment Business models / Services Security / Privacy / Legal aspects Power / Environment

5 (BIG) DATA ANALYTICS IN PRACTICE Data cleaning Representation Neural Networks Logical Inference Casebased Statistical Methods Validation Deployment

6 BIG DATA PROMISES Extraction of valuable information from large data sets Increasing volumes of data lead to increasing value of extracted information Uncovering of otherwise hidden and valuable information Connected vehicles + big data analytics Novel services Improved efficiency and productivity Competitive edge

7 TRENDS IN BIG DATA RESEARCH Strategies for surviving the data flood Learning Representation Taking advantage of structure: Graph Processing Big data transformed to Small data Platform/algorithm interplay Local vs global computation Streaming data Store and communicate models

8 REAL TIME TRAFFIC AWARENESS High availability of traffic reports and collection of vehicle-based positioning data Allows modelling and prediction of traffic situation for individual vehicles Toyota will launch its Big data traffic information system for providing services for optimal routes predictions of travelling times

9 FLEET MANAGEMENT ARI Fleet collect thousands of data types from each vehicle in its fleet (a million vehicles) Applying state-of-the-art big data analytics helps ARI Fleet make substantial savings through timely and precise maintenance scheduling improved transport scheduling

10 MANUFACTURING Collecting and anlysing data from Driver behavior Vehicle behavior Service and maintenance cycles Range Rover s Best Suv of the year (2012) model can give manufacturers Evoque was designed taking valuable insights into how to into account extensive improve driving experience simulations based on and security aspects already analysis of collected data in design stage from the performance and behavior of earlier models

11 THE DATA DRIVEN SYSTEMS STACK, EXAMPLES OF WORK AT SICS Stream processing, Pig Ja Be Ja Graph Clustering Anomaly / change detection Traffic and mobility modeling Domain specific MapReduce Stratosphere Spark Frameworks Resource management Information Centric Networking, SDN SicsthSense HOPS as Platform As a Service Scalable HDFS Network Search SDN Monitoring Autonomous RAN Text and Social Media Computing Storage Networking Data collection

12 TAKE AWAY LESSONS Big data analytics does not come out of the box Need domain knowledge for meaningful data analysis Every domain of application of BDA requires unique analysis, modelling, and deployment Paradigm change in ICT and Society 1. Information is power extracting value from data is becoming the crucial competitive advantage 2. ICT is becoming data and service centric Application driven; compute, storage and communication viewed as services 3. ICT is becoming an integrated part of products and services

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