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Big Data Analytics
Ben Fountain
May 2016

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What is Big Data?
“The dynamically linked super set of multiple significant
scale discrete data sets.”
-Oscar Wilde
Characteristics include
• Large volumes, typically adding terabytes of data daily
• Aggregation of many historically discrete data sets
• Dynamic links between the data sets
Consequently
• Any analysis is a point in time position

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Why care?
• Better intelligence which can be leveraged in business, healthcare etc. to
target efforts;
• Cost of a DNA analysis has reduced by around 5 orders of magnitude
since the process became possible, making personalised medicines a
reality in the near future.
• If you are investing in Big Data projects, the risk of data loss doesn’t
necessarily change. The Volume of loss is potentially colossal with impacts that
aren’t understood for an extended period.
• Customers hold concerns about companies taking a role of Orwellian Big
Brother.

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There’s no Best Practice…yet
Breaches
• Snowden showed that Government organisations with specific focus on
security struggle to control Big Data and the associated risks.
• Panama Papers showed that legal firms with an inherently high level of
confidentiality in their practices struggle.
Compliance issues
• Harder to define the purpose of data exploration.
• Big Data breaches tend to be….bigger.
• Regulators will expect technology to be used equally to exploit and
control Big Data.

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Key Controls for Big Data
1. Track all access that collects, views, and manipulates sensitive data, and ensure that it is
encrypted at each point.
2. Encryption keys for sensitive data can't be stored at the same location as the data.
3. All access and processing of data must be logged. These logs must be subject to human and
automatically monitoring.
4. Use automated scanning to constantly monitor systems for vulnerabilities and malware.
5. Monitor network egress for anomalies in traffic.
6. Create a number of "false flag“ records. Configure alerts and blocks to identify and prevent
data breaches.

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How to use Big Data Analytics?
Prescriptive Analytics
How can we influence the future?
Predictive Analytics
How can we plan for the future?
Diagnostic Analytics
Why did this happen?
Descriptive Analytics
Do we know what happened?
AnalyticsMaturity
HistoricalAnalyticsProactiveAnalytics

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Police use of Predictive Analytics
The California city of Fresno is just one of
the police departments in the US already
using a software program called “Beware”
to generate “threat scores” about an
individual, address or area.
As reported by the Washington Post in
January, the software works by
processing “billions of data points,
including arrest reports, property records,
commercial databases, deep web
searches and the [person’s] social media
postings”.
Photo: Nick Otto/For The Washington Post
Quote :https://www.theguardian.com/technology/2016/feb/04/us-police-data-analytics-smart-cities-crime-likelihood-fresno-chicago-heat-list

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How to do it well
Staff appropriately
• Specialist Skills are in demand;
• Big Data
• Data Management
• Have a plan to recruit and retain them!
Data Quality
• Big Data Leaders show maturity in data quality

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Final Point
Big Data is a pre-requisite of the desire for better
analytics, the desire to better understand. Of itself, its
just a large data set waiting to breach.

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Points of contact
Ben Fountain
Senior Consultant
M: +44 (0) 7545 503 311
E: ben.fountain@nccgroup.trust
NCC Group Blogs
https://www.nccgroup.trust/uk/about-
us/newsroom-and-events/blogs/
TED Talks on Big Data
https://www.ted.com/search?q=big+data

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Experiment
“The dynamically linked super set of multiple
significant scale discrete data sets.”
-Oscar Wilde
Well that’s a lie.

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NCC Locations
Europe
Manchester - Head Office
Amsterdam
Basingstoke
Cambridge
Copenhagen
Cheltenham
Delft
Edinburgh
Glasgow
Leatherhead
Leeds
London
Luxembourg
Madrid
Malmö
Milton Keynes
Munich
Vilnius
Zurich
Australia
Sydney
North America
Atlanta
Austin
Chicago
Kitchener
New York
San Francisco
Seattle
Sunnyvale