Technology Office Challenge. (Why numbers rock!)

Transcription

1 Technology Office Challenge (Why numbers rock!)

2 Context 800,000+ customers 280+ branches 300 ATMs 1,100 staff $14.4bn assets 2 data centres 350 production servers (50% virtual) 0.5PB storage (10% structured)

3 My Technology Office Challenges Product / Marketing / Operations 1 Architecture Narrative what, why Technology Delivery 2 3 Make the Right Decisions Capability Development 4 Derive Value from Data

4 2. Making the right decision Forces for control Processes and tools Comprehensive documentation Plans Forces for creation Individuals and Interactions What works beats theory Change is everywhere

5 Sound familiar? it s the Agile Manifesto

6 My observations Our best work has happened when 3 things were true: 1. We give it a go 2. With a supportive business team that s not scared to understand the little details 3. And a committed and passionate technical lead 4. That ensures people work together.

7 (Collaborative) 3. Capability Development ^ Architecture Briefing Forum Analytics Forum (soon!) Enterprise Information Forum

8 Architecture Briefing Forum Distributed configuration across Internet Banking servers Federated Identity Anti-Money Laundering Operations Management with System Center Web Service Gateways Application Build and Deployment Storage Pre-Production Update NoSQL logging design comparing MongoDB and RavenDB Crypto 101

9 4.Gaining value from information Key insight has been that multiple groups are required to gain full benefit. Why? Differing skills and knowledge. Analytics platform Enterprise Information platform Data Platform IT has a role across all

10 Our Data Platforms Storage Hitachi Virtualised Storage ½ PB of data = 7 years of HD-TV 1/5 th is database storage High growth rate Shared Storage (TB) Database Microsoft SQL Server NoSQL: Universe, RavenDB, MongoDB Staging 65GB exposed to systems every day >1000 data jobs / day

11 NoSQL?????

12 Our Enterprise Information Platform Key strategy is to unlock information assets Make data available into Analyst Playpens Through improved data acquisition / transformation / delivery Currently in progress

13 Our Analytics Platform Data Microsoft Excel (+ VBA/.NET) Tibco S+ Microsoft SQL Server (DMX) Analyst s Playpen(s) Sungard ALM All different. All with strengths. All suited to different users.

14 And Analytics Means What Exactly? 1. Optimisation Optimal decisions under competing constraints. 2. Understanding connectivity Connectivity between attributes leading to a decision ie market basket analysis ; or understanding clustering of outcomes. 3. Predicting the future Predicting future outcomes based upon history.

15 A rapidly changing landscape

16 Analytics = $++ It s not just the licensing it s the infrastructure.

17 So go cloud, but take care

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19 How is this useful? Classic bank examples are Risk analysis Market risk Credit risk Operational risk Proactive optimised marketing Market basket analysis Prioritisation of campaigns Portfolio optimisation Customer needs analysis

20 Bit of fun: @WestpacNZ

21 Bit of fun: ORM sentiment Online Relationship Sentiment

22 Understanding content Strictly speaking latent semantic analysis Relate terms to documents: Term Document Frequency Matrix Uncover frequent terms: Uncover associations:

23 Wordcloud

24 Connectivity

25 Online buyer behaviour Is online purchasing more or less important in the regions versus the cities? My hypothesis is yes High Low Can t disprove it

26 Mapping our transactions

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28 How does your energy bill stack up?

29 What do we see? Large variances across companies Minor regional differences Colours = Companies $0 $50 $100 Key data is power company avgbill Optimisation possibility of about $15/month or $180/year $80 $90 $100 $110 $120 $130 $140 $150 $160 $170

30 Metrics and Analytics for IT Summer of Tech project To build digital signage that displays metrics across operations, delivery, and the business. Focused on the IT consumer

31 Summary We build narratives to explain what and why. We work with all of IT to grow capability and ensure we re collectively making the right decisions. We support analysts by ensuring they have the platforms, tools, and skills to succeed.