The big data value chain r1-31 oct13

4. How big is BIG? Twitter users send out 277,000 tweets Facebook processes 350GB of data EVERY MINUTE 100 hours of new video are uploaded on YouTube Google processes more than 2 million seach queries

5. Each hour, enough information is consumed online to fill 7 million DVDs Source: http://events.sap.com/sapphirenow/en/session/2310 The current global storage capacity for digital information requires stacking a pile of CD-ROMs on top of one another, would stretch 80,000 km beyond the moon

6. The 500,000 data centers are large enough to fill 5,995 football stadiums Source: http://realcomm.com/advisory/advisoryPrint.asp?AdvisoryID=544

7. Source: http://dailyreckoning.com/the-six-most-fascinating-technology-statistics-today/

8. The Big 101

9. Source: http://blogs.msdn.com/b/data__knowledge__intelligence/archive/2013/02/18/big-data-big-deal.aspx WHERE IS BIG DATA?

10. The 3Vs of Big Data

11. THE BIG FUSS

12. The Tip of the Iceberg Big Data

13. Big Data Value Healthcare and Medical discoveries • Prediction and preventive analysis bird flu – prevent mass outbreaks of the virus Retail and service industries • Purchase behaviour and preference tracking, real-time personalisations Transportation and Logistics • Mapping and route planning Government • Cost savings

14. Big Data Market Forecast ($US BILLIONS) $53.4 $48.0 $32.1 $16.8 $10.2 $5.1 2012 2013 2014 2015 2016 2017

15. BIG DATA CHALLENGES

16. Big Data Landscape

18. V VAGUE

19. THE BIG QUESTION

20. The Big Question • Big Data is here to stay. • How and where do you begin your journey?

21. Big Data, Small Steps •Data Storage •Data Management & Workflow •Data Movement

22. De-Brief IT System and Infra-Structure Appliances CLOUD Programming Analytics Data Mining Automation WorkFlow SMIs/SME s Government/PLCs/MNCs BIG DATA Value Chain Social Media BYOD RFID

23. IT System and Infra-Structure With OPEX Model and the Sentinels, it is now available for ALL

24. Conclusion

25. THANK YOU VERY MUCH Presented by Rei Lim Transtel Technology (M) Sdn. Bhd 21/11/ 2013

26. References • http://www.galaxyhealth.net/ • www.mckinsey.com/insights/strategy/are_you_ready_for_the_era_of_big_data?p=1

Editor's Notes

Big Data – I willadress just 4 crucial areasWhy is it considered the big bang?What is the big question?Why is there so much buzz about it?Why is it all about data? What part of the data is it all about?*Under storing – managing and maintaining.We will go into more details where our…spec n sgl…will give you their insights.Our r and d director Mr. Lim will talk abit about DigiFlowStoring Data – That is where our principal Spectra will come in to store data – More to storing data – follow up by our other principlesIntroduce the data (managing and moving data – SGL)
Big Data is for Big BoysData is growing – costly, difficult, struggling to implement. What are you doing in this area?*sounds good but cannot implement.Attend big data seminar at tm – application – I was there.If you’re not an MNC – high hanging fruitOne day going to be big. Know about it.Know about it – cost, complexity, come down which happen to a lot of it base servicesi.t. becoming commoditize – see the big diff?Big expensive, becomes big and affordable…..
InterestinginfographicEvery minute~~~350Gb = whole of library’s books provide a reference5000 ebooks EVERY MINUTE – 60 secondsImagine 15 0s of what?Convert it something relatable1 hour HD of videoHow many hollywood films?
Need to redo the infographic – bad colouringIceberg analogy
-Game changing effects of big data (McKinsey)-Big data could potentially change competition – transform processes, radically alter corporate ecosystems, facilitate innovation-Already we are experiencing this effects – Google, LinkedIn, FB – change how we search, look for informatio.
What did the big guys see?Our PM saw it – put it up
Retail-Tracks purchases and sales, offers insights and clues about how customers behave (McKinsey & Company)-Real-time personalisation possible – big data – track the behaviour of individual customers from internet click streams, recognise when customers are nearing a purchase decision – also pose some problems, which we will see later.-Widely available data- internet purchases, social-network conversations, location specific interactions GeneralUse business analytics to guide decision making – experience higher returns on investments,Enable networked organisations to gain a competitive edge by opening up information silos internally – by engaging customers and suppliers strategically through web based exchanges of into. (McKinsey)Key basis for competition:
Business value – in total is going to come to this amount in the future. Just some examples of what the big boys are doing. This is what they are doing now.Source???According to who…??Credibility
VOLUMEPresence of vastand massive quantities of data-New storage technology-Distributed storage -Classical storage: File base-SAN storage – becomes block base-Distributed storage – object base-*very deep into technology – if interested, hope you have registered your email – send you whitepapers. We hope we can hold a more technical base seminar for all of you in the near future.VELOCITYDemand for high velocity data streamsTo do with distributed storage-physically – hardware wise, gotta do with storage software wise, you need new algorithms – hearing hadoop python, hive. Pig…etc.VARIETY-Primarily unstructured data that requirescomplex pre-processingandcleansing.Algorithms and programming – hear things like R, new professions like Data Scientist, statisticians, data analyst.All this in Msia, we have yet to develop into this big data area.
LINKWe say its vague, because big data is like the blind men and the elephant.Different people see different partIf today, you don’t see, I don’t blame you….^^
-Key competition – MckinseyCompanies need to act and start thinking whether to organise and exploilt big data’s potential and the threats it can poseDemands new skills which is now insufficient – graduates are ill equiped.’Effect and disrupt existing data and information management models – disruptive business models Is Big Data only for the big boys –Already organisations are making big data as part of the core element of strategy.Already implementingChallenge is to look a flexible infra that can integrate info, scale and meet the massive deluge of data.Have algorithms, analytics in space to make sense of the data.Not all industres are created equal – some industries are more “ready” than most, and are able to reap the benefits sooner. Or have stronger benefits to do so.*if you have a lot of big big data, the first thing you do, is how to store themWe have spectra logic to come and present to store the data *how do you manage them – SGL*move them thru small pipes – Signiant
Back to spectra – this is where in today’s programme, we have manufacturers in the different areas to share with you the knowledge.For data storage and management we have Spectra from USA(LOGO)The emcee will introduce the company on board. What you see in the picture, are already installed in some premises in msiaWho?Not right for us to mention names, but you will know.Moving data-all digital Adidas Carry data in portable drive, thumbdrive, everywhereSend it by courierNow moving internally via the network infrastructure ethernetglobally – internetEven internally within the ethernet we get traffic jamsIm sure all of you face this issue – over the internet, despite all the fiber connection, still got traffic jam.Buffering? During video playbackHow many times, a friend said you send an email, reply have not receive? Or an sms?Whether you have receive or spam.All this issues are related to data transferClever solutionsHow would you like a technology, when you send a file, it ensures that it gets to its destination? That it will bypass the traffic jam? This is where signiant has got the answer.Unfrotunatelykc cannot make it, they were here a few days earlier, have other things to work on, so they cram all the info into kc.Technology – what it is, some clever people will come up with solution to come up the best as they can.

The big data value chain r1-31 oct13

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Editor's Notes