Deloitte is a large professional services firm with over 7,000 people worldwide focused on big data analytics. They have data laboratories, visualization environments, and predictive analytics centers. Some key challenges for big data include over-reliance on technology, selecting the wrong data, and mistaking correlation for causation. Deloitte identifies seven trends in big data: ensuring the right talent, using visualization techniques, machine learning finding applications, data discovery platforms, using data for social good, rise of predictive analytics, and the declining need for traditional data warehouses.

1. © 2014 Deloitte LLP. Private and confidential.
Trends in big data
Key challenges for skills
© 2014 Deloitte LLP. Private & Confidential
Dr Harvey Lewis, Deloitte Analytics
Big Data for Security and Resilience: Challenges and Opportunities, 7 March 2014

2. © 2014 Deloitte LLP. Private and confidential.
Deloitte and big data
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3. © 2014 Deloitte LLP. Private and confidential.
Deloitte and big data
• 7,000 people worldwide in the
Deloitte Analytics community
• 700 people in the UK
• Gartner ‘magic quadrant’ for
Global BI and Performance
Management
• Dedicated analytics facilities,
including data ‘laboratories’,
visualisation environments and
training suites
• Predictive Analytics Centre of
Excellence
• Technology-independent
− IBM, Microsoft, Oracle, SAS, Tibco,
Tableau, QlikTech, SAP, R, etc
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Big data definitions
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Big data
Small data
Any data
Real-time
Velocity Volume Variety
Large data
“Data that is too rich or complex to analyse
well in a spreadsheet and without concepts
from university-level statistics”

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Retailing in a hurricane
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Crowd monitoring at a major event
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0
100000
200000
300000
400000
500000
600000
1 5 9 13 17 21 25 29 33 37 41 45 49 53 57 61 65 69 73 77 81 85 89 93
ObservedVolumes
Time
Observed crowd estimate along river zones
Royal Naval
College
Zone 10
Zone 9
Zone 8
Zone 7
Zone 6
Westminster
Bridge
Vauxhall Bridge
Lambeth Bridge
ODA Zone 4
ODA Zone 3
Chelsea
Embankment
Zone 1 Zone 2 Zone 3 Zone 4 Zone 5 Zone 6 Zone 7 Zone 8 Zone 9 Zone 10 Zone 11
Zone 1 40% 44% 29% 1% 1%
Zone 2 65% 27% 27% 2% 1%
Zone 3 30% 19% 40% 25% 4% 2% 1%
Zone 4 1% 1% 26% 55% 19% 5% 1%
Zone 5 5% 20% 37% 43% 6% 1%
Zone 6 1% 3% 20% 35% 44% 3% 1%
Zone 7 3% 51% 45% 5% 2%
Zone 8 9% 15% 63% 22%
Zone 9 2% 3% 12% 57% 29%
Zone 10 33% 66%
Zone 11 2% 1% 2% 1% 1% 1% 94%
Zone 1 Zone 3
Zone 4
Zone 5
Zone 6
Zone 7 Zone 8 Zone 9
Zone 10
Zone 2
Zone 11

8. © 2014 Deloitte LLP. Private and confidential.
Identifying sentiment, emotion, indicators and warnings
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0 1 2 3 4 5 6 7 8 9 10 11 12
Social Media CDC Timeline News Media
Maturity / Investigation Complete
Pre-conditions
for Takeoff
Timeline in Weeks
DevelopmentalStages
Takeoff
Infancy Stage
What How
Source Where

9. © 2014 Deloitte LLP. Private and confidential.
Finding influencers in organisational networks

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(Skills) challenges for security and
resilience
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Over-reliance on technology
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Proprietary big data
technologies
Open source big data
technologies

12. © 2014 Deloitte LLP. Private and confidential.
Leaving no stone unturned
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13. © 2014 Deloitte LLP. Private and confidential.
Selecting the wrong data
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14. © 2014 Deloitte LLP. Private and confidential.
Believing more data = more information
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15. © 2014 Deloitte LLP. Private and confidential.
Mistaking correlation for causality
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Number crunching not data-backed insight
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𝑦 𝑥 =
𝑒 𝑏0+𝑏1 𝑥
1 + 𝑒 𝑏0+𝑏1 𝑥
𝑏0 = 2.298057
𝑏1 = 30.023823

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Not recognising the creepy line
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Trends
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Big data return-on-investment
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‘Bigness’ of data
Marginal Value
Positive ROI
Source: Deloitte LLP
Marginal ROI Negative ROI

20. © 2014 Deloitte LLP. Private and confidential.
Seven big data trends
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Right talent doing
the right things
A picture is worth a
thousand numbers
Machine learning
finds its niche
Data discovery
platforms
Doing good with
data
The rise of
predictive data
The death of the
data warehouse

21. © 2014 Deloitte LLP. Private and confidential.
Dealing with big data (1)
21 Source: Deloitte LLP
Right talent
Machine learning
‘Bigness’ of data
Marginal Value
Death of the data
warehouse

22. © 2014 Deloitte LLP. Private and confidential.
Dealing with big data (2)
22 Source: Deloitte LLP
Data discovery
‘Bigness’ of data
Marginal Value
Visualisation
Doing good with
data
Predictive data

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Image source: NASA/courtesy of nasaimages.org.

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About Deloitte
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detailed description of the legal structure of DTTL and its member firms.
Deloitte LLP is the United Kingdom member firm of DTTL.
This publication has been written in general terms and therefore cannot be relied on to cover specific situations; application of the
principles set out will depend upon the particular circumstances involved and we recommend that you obtain professional advice
before acting or refraining from acting on any of the contents of this publication. Deloitte LLP would be pleased to advise readers
on how to apply the principles set out in this publication to their specific circumstances. Deloitte LLP accepts no duty of care or
liability for any loss occasioned to any person acting or refraining from action as a result of any material in this publication.
© 2014 Deloitte LLP. All rights reserved.
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office at 2 New Street Square, London EC4A 3BZ, United Kingdom. Tel: +44 (0) 20 7936 3000 Fax: +44 (0) 20 7583 1198.
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