Presentation on theme: "BIG DATA IN ENGINEERING APPLICATIONS"— Presentation transcript:
1BIG DATA IN ENGINEERING APPLICATIONS BYJASTI ASWINI206513
2Overview Introduction Why Big Data Big Data(globally) Big Data: 3 V’s Big Data challengesBig Data in Design EngineeringReasons for the importance of Big DataCloud and Big DataBig Data in EcommercePLM in Big DataAdvantagesConclusion
3INTRODUCTIONBig 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.
4Why Big dataKey enablers for the appearance and growth of ‘Big-Data’ are:Increase in storage capabilitiesIncrease in processing powerAvailability of data
6Bigdata: 3 V’sBigdata 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.
11The Evolution of Business Intelligence scalescale2000’s2010’s1990’shttps://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
13Big 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.
14Reasons for the importance of Big Data Increase innovation and development of next generation productImprove customer satisfactionSharpen competitive advantagesCreate more narrow segmentation of customersReduce downtime
15Cloud and big dataIn 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 dataWeb based tools will allow you to upload your Big Data to the manufacturing cloud,
16Bigdata in EcommerceCollect, 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, service provider statastics etc).
17PLM in Big Data Big data grows ridiculously fast Most Big data is ephemeral by natureOut-of-date Big data can undermine the results of your business analytics
18PLM 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
19Advantages Dialogue with consumers Redevelop your products Perform risk analysisKeeping data safeCustomize your website in real timeReducing maintenance cost
20ConclusionSilicon 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.