Big Data and Analytics:

Transcription

1 responsive, credible, flexible Big Data and Analytics: New data sources create transformation opportunities Mike Davis Principal Analyst All images acknowledged msmd advisors Ltd

2 Running order Why all the fuss about big data? So who uses big data? (and why) How has it helped business to date? Where else can it help? CIO concerns? WIIFY (what's in it for you) 2

3 Running order Why all the fuss about big data? So who uses big data? (and why) How has it helped business to date? Where else can it help? CIO concerns? WIIFY (what's in it for you) 3

4 Information management is about USING information to make a decision 4

5 Decision making requires effective information That s delivered: At the right place and in context At the right time and complete / credible / trusted To the right person(s) who have authority to make decisions 5

6 The need for precision 6

7 Small decisions big effects 7

8 Understanding data 8

9 Understanding data 9

10 Understanding data 10

11 Understanding data 11

12 Understanding data 12

13 It's all his fault 13

14 5 Terabytes of electronic data under management 14

15 Big data and the challenge of decision making Size Scope Speed 15

16 There's simply too much data to deal with The petabyte is the new data norm Tsunami of human and machine generated data Multiple formats Democratisation of data 800 Tweets per second (12 gigabytes) Facebook generates 100 TB of data per day Organisations are struggling to store, access and process data efficiently Structured and unstructured information is processed in separate systems Some formats are difficult to process 16

17 So where's the value in big data? 17

18 So who uses big data? And what's in it for your organisation? Internet Google, Amazon, ebay, AOL everything Mobile Gaming On line betting, multi user games Marketing Social Network Analysis, Digital Advertising Telcos Call Routing Management, Subscriber Churn Retail Tesco customer segmentation, Netflix - everything Utilities Smart Grid for meters Insurance Telemetrics on cars Banking Fraud detection 18

19 Big data in marketing Social network analysis World s biggest marketing focus group Who s talking about you? What are they saying? Why? Who are the opinion leaders? Highly contextual text analytics Classic many-to-many relationship problem Map & measure relationships & flows between people, groups, computers, URLs, etc. Facebook adds TB/day to DW 19

20 Big data and mobile gaming/on line betting Billing Demographic info Mobile device,location, time Usage What s hot, what's not Levels of play/betting Customer segmentation ID top players/punters, leaders Social Media comment Trending and sentiment 20

21 Big data in telco/isps Call routing optimization 200 GBytes compressed CDRs uploaded daily (from 1 Tbyte raw data) Constraints: tower location, interconnection agreements Customer churn analysis & prevention Traditionally: Look at call quality Today: Social community analysis Who s calling who? Security issues?? 21

22 Big data in retail - Tesco Major use of BI and loyalty program Outsourced to Dunnhumby for analysis 80% of customers are Clubcard members Constantly updating data every transaction improves data quality Targeted promotions both direct and sponsored by suppliers (revenue stream) 22

23 Big data in utilities SINGLE RESIDENTIAL METER a 6 digit reading Every quarter =4 Every day = 365 Every hour = 8760 Every 15 minutes = 35,040 Every 5 minutes = 105,120 Every minute = 525,600 Every 30 seconds = 1,501,200/per meter/per year The UK has 26 million household meters PG&E added 1.2 Pbytes storage to support 700k SMART meters in They have 10x that today 23

24 Big data in insurance the single view and the spy in the car 24

25 Should you have concerns? Who owns the data? Who can access the data? How quickly does it need to be processed? How easily can it be understood? Who s running the IM department anyway? 25

26 WIIFY? - we do not need to be afraid of big data You will not be the first Big data brings value not traditional ROI (unless it is your business) We have the tools we may need to bring them together We have the skills we may need to bring them together We need to see an organisation s information assets as a whole We do however need the organisation to mature in its understanding of the role and value of information Big data should mean BIG opportunities 26

27 responsive, credible, flexible Thank you 27