Analysing and Understanding Putting big data to work Total Global - - PowerPoint PPT Presentation

analysing and understanding putting big data to work
SMART_READER_LITE
LIVE PREVIEW

Analysing and Understanding Putting big data to work Total Global - - PowerPoint PPT Presentation

Analysing and Understanding Putting big data to work Total Global Data 2011 - 2013 90% Before 2011 Source: IBM Data Analytics, 2013 Graphics Reveal Data Edward Tufte Perception Understanding is essential Simplify for more


slide-1
SLIDE 1

Analysing and Understanding Putting big data to work

slide-2
SLIDE 2

Total Global Data

2011 - 2013 90% Before 2011

Source: IBM Data Analytics, 2013

slide-3
SLIDE 3

“Graphics Reveal Data”

Edward Tufte

slide-4
SLIDE 4

– Understanding is essential – Simplify for more accurate reading

Perception

slide-5
SLIDE 5

– Understanding is essential – Simplify for more accurate reading

Perception

Source: Cleveland & McGill, 1984

slide-6
SLIDE 6

Four key objectives: – Provide overview – Adjust perspective – Detect pattern – Match mental model

Insight

slide-7
SLIDE 7

Source: The Guardian, 2011

slide-8
SLIDE 8

Visual appeal is determined within 0.5 seconds Therefore, optimise by selecting: – Low – medium complexity – Medium – high colourfulness

Appeal

slide-9
SLIDE 9

Visual appeal is determined within 0.5 seconds Therefore, optimise by selecting: – Low – medium complexity – Medium – high colourfulness

Appeal

Source: CDP Cities, 2015

slide-10
SLIDE 10

London: The Information Capital

slide-11
SLIDE 11

John Snow, 1854

Source: The Visual Display of Quantitative Information, 2009

slide-12
SLIDE 12

John Snow, 1854

Source: The Visual Display of Quantitative Information, 2009

slide-13
SLIDE 13

London Data Store

– Population – Dwellings – Energy – Transport – Health – Education

slide-14
SLIDE 14

Mapping London

LSOA Map Source: GLA LSOA Atlas, 2014 Residents per Dwelling

slide-15
SLIDE 15

Buildings: Big Data Potential

slide-16
SLIDE 16

– Energy consumption – System peaks – Automated controls – Occupant comfort – Maintenance requests – Secure access – File storage

Building Data

slide-17
SLIDE 17

Granular energy data and dynamic pricing – Reduced supplier costs – Deferred network investment – Cheaper energy bills

Example: Domestic DSR

Source: UK Power Networks, 2014

slide-18
SLIDE 18

Significantly more complex systems – Predict demand reductions – Respond to automated network signals – Deliver agreed demand reduction – Monitor building performance – Communicate benefits to engage occupants

Example: Non-domestic DSR

slide-19
SLIDE 19

“Big Data Is Not About The Data”

Garry King

slide-20
SLIDE 20