bigdata (1)
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This document discusses big data applications in engineering. It begins with an introduction to big data and its 3 V's (volume, velocity, variety). It then discusses how big data is important for design engineering, providing Boeing as an example. Key reasons why big data is important include increasing innovation, improving customer satisfaction, and gaining competitive advantages. The document also covers how big data relates to cloud computing, ecommerce, and product lifecycle management. It concludes that big data is an important and growing area that can provide benefits across many industries including manufacturing.
bigdata (1)
- 1. BIG DATA IN ENGINEERING APPLICATIONS BY JASTI ASWINI 206513
- 2. Overview • Introduction • Why Big Data • Big Data(globally) • Big Data: 3 V’s • Big Data challenges • Big Data in Design Engineering • Reasons for the importance of Big Data • Cloud and Big Data • Big Data in Ecommerce • PLM in Big Data • Advantages • Conclusion
- 3. INTRODUCTION • Big data is the term for a collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications. • The challenges that we face with dbms tools and other tehnologies is capture, curation, storage, search, sharing, transfer, analysis, and visualization.
- 4. Why Big data • Key enablers for the appearance and growth of ‘Big-Data’ are: + Increase in storage capabilities + Increase in processing power + Availability of data
- 6. Bigdata: 3 V’s • Bigdata is usually transformed in three dimensions- volume, velocity and variety. • Volume: Machine generated data is produced in larger quantities than non traditional data. • Velocity: This refers to the speed of data processing. • Variety: This refers to large variety of input data which in turn generates large amount of data as output.
- 7. REF:2
- 11. The Evolution of Business Intelligence scale scale 1990’s 2000’s 2010’s https://www.google.de/search?q=evolution+of+business+intelligence&newwindow=1&tbm=isch&tbo=u&source=univ&sa=X&ei=gEGoU5KX BuTb4QSGsoH4BQ&ved=0CDsQsAQ&biw=1366&bih=64
- 12. OLTP: Online Transaction Processing (DBMSs) OLAP: Online Analytical Processing (Data Warehousing) RTAP: Real-Time Analytics Processing (Big Data Architecture & technology)
- 13. Big data in design and engineering • Engineering department of manufacturing companies. • Boeing’s new 787 aircraft is perhaps the best example of Big Data, a plane designed and manufactured. • Big Data needs to be transferred for conversion into machining related information to allow the product to be manufactured.
- 14. Reasons for the importance of Big Data • Increase innovation and development of next generation product • Improve customer satisfaction • Sharpen competitive advantages • Create more narrow segmentation of customers • Reduce downtime
- 15. Cloud and big data • In fact from a Cloud perspective I believe that the transfer and archiving of Big Data will become a key capability of a manufacturing focused cloud environment. • Servers based on the Intel® Xeon® processor E5 and E7 families are at the heart of infrastructure that supports both cloud and big data environments. • Ideal for storing and processing large volumes of data • Web based tools will allow you to upload your Big Data to the manufacturing cloud,
- 16. Bigdata in Ecommerce • Collect, store and organize data from multiple data sources. • Bigdata track and better understand a variety of information from many different sources(i.e., inventory management system, CRM, Adword/Adsence analytics, email service provider statastics etc).
- 17. PLM in Big Data • Big data grows ridiculously fast • Most Big data is ephemeral by nature • Out-of-date Big data can undermine the results of your business analytics
- 18. PLM adopts Big Data? • Too big and too abstract. • This is not simple and will not happen overnight for most of manufacturing companies using PLM systems. • PLM data size may reach to yotta bytes
- 19. Advantages • Dialogue with consumers • Redevelop your products • Perform risk analysis • Keeping data safe • Customize your website in real time • Reducing maintenance cost
- 20. Conclusion • Silicon valley and through social media is making Big Data a global phenom. • Not only Big Data is “cool” it happens to be a huge growth area as well.
- 21. Resources : 1. https://www.google.de/search?q=evolution+of+business+intelligence&newwindow=1&tbm=isch&tbo=u&source =univ&sa=X&ei=gEGoU5KXBuTb4QSGsoH4BQ&ved=0CDsQsAQ&biw=1366&bih=64 2. https://www.google.de/search?q=big+data+TRANSACTION+INTERACTION+OBSERVATION+EXAMPLE&newwindo w=1&source=lnms&tbm=isch&sa=X&ei=DkaoU-H4K4Xe4QSO1oDwAg&ved=0CAgQ_AUoAQ&biw=1366&bih=643 3. http://www.tcs.com/SiteCollectionDocuments/White%20Papers/Knowledge-Big-Data-Analytics-Product- Development-1213-1.pdf 4. http://www.meltinfo.com/ppt/ibm-big-data 5. http://wwwiti.cs.uni-magdeburg.de/iti_db/forschung/index.php#projekte 6. http://datascienceseries.com/stories/ten-practical-big-data-benefits 7. http://www.intel.com/content/dam/www/public/us/en/documents/product-briefs/big-data-cloud-technologies- brief.pdf 8. http://www.bigdatalandscape.com/news/why-big-data-is-a-must-in-ecommerce 9. http://www.intel.com/content/dam/www/public/us/en/documents/product-briefs/big-data-cloud-technologies- brief.pdf 10. http://www.gxsblogs.com/morleym/2011/10/how-the-cloud-helps-manufacturers-address-%E2%80%98big- data%E2%80%99-challenges.html 11. http://www.itbusinessedge.com/blogs/integration/three-reasons-why-life-cycle-management-matters-more- with-big-data.html 12. http://www.forbes.com/sites/siliconangle/2012/02/29/big-data-is-creating-the-future-its-a-50-billion-market/ 13. http://plmtwine.com/tag/big-data/ 14. http://www.3dcadworld.com/big-data-will-important-manufacturers-future/