How big data is and will effect us especially where security and privacy are concerned and how we may proceed to deal with crisis.

1. Big Data & Analytics:
What is Ahead?
Panel, WEDA Symposium
@ 40th COMPSAC
June 14th, 2016,
Atlanta, GA, USA
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2. Agenda
• Big Data Analytics is in Your Future!
• Don’t Give Me Data!
• BDA in Your Health
• Workplace 2026
• 100 BDA Predictions Through 2020
• BDA Futures in APEJ through 2020
• Big Data Digs Big Holes:
• Of Security & Privacy
• Privacy Preserving Analytics
• Lapses/Cases
• How to Approach the Issues?
• So what?
• BDA: tool or outcome?
• How-to Guide
• Advanced Analytics
• A Little Help from AI
• Edge BDA?
• BDA Goes Better with Semantics
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3. BDA is in Your Future!
• “Never give me data. Only provide me with information.”
Anon. (http://www.clevity.com/it-is-not-analytics/)
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4. BDA in Your Health
• "Medicine in the near future will be predictive, preventive, and
personalized thanks to big data-driven analysis. " SI in Omics-Based
Medicine
• Healthcare technology in 2026 will facilitate access to GP and
hospital records online by patients routinely- just as online
banking today.
• Individuals’ health will be linked to:
• Environmental data obtained through monitors of public transport,
airports, hospitals, rural location and other places of interest for the
appearance and evolution of viruses.
• Compared to continuously collected vital data from millions of
patients around the world.
• Medical conditions will be diagnosed in that perspective.
IDG Connect: What will health tech mean…
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5. Workplace 2026?
• “The workplace of the future will be 360 degrees and 24/7…”
• “In 2026 the work place will be smart.”
• “The biggest transformation will be change in mindset. ”
• “Data analytics and visual analytics tools will be as ubiquitous
as word processors are today, and there will be a seismic shift
in working culture whereby it will be unacceptable for
decisions to be made based simply on assumption or ‘gut
instinct’.”
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«What will the workplace of 2026 look like?»

6. 100 BDA Predictions Through 2020ByGartner
• Of Core Analytics Predictions:
• Advanced Analytics and Data Science: Advanced Analytics Are at
the Beating Heart of Algorithmic Business:
• «Advanced analytics solutions are becoming increasingly popular in
driving business innovation and experimentation, and creating
competitive advantage. Analytics leaders must now exploit new
business models and ecosystems that will drive the operation of
algorithmic business.»
• Business Intelligence: Changes Coming in How We Buy Business
Analytics Technology:
• «Changes to the business intelligence and analytics platform market
will include further bundling of next-generation capabilities along
with a major emphasis on product trials in the vendor selection
process.»
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7. BDA Futures in APEJ through 2020ByIDC
1. Cloud BDA
2. Cognitive
3. Labor Shortage
4. In-Memory Computing
5. Distributed Micro Analytics
6. Self-Service
7. Data Monetization
8. Analyzable Data
9. Actionable Information
10. BDA Value
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7Li, Zhang, & Chua, Dec. 2015

8. 1. Cloud BD&A. Spending on cloud-based BDA technology will grow 3x faster
than that for on-premises solutions; open source technology will be core.
2. Cognitive Computing. 40% of all business analytics software will
incorporate prescriptive analytics built on cognitive computing functionality.
3. Labor shortage of data scientists to architects and experts in data
management; Big Data–related professional services will have a 29% CAGR.
4. In-Memory Computing. 75% of databases will be based on memory-
optimized technology.
5. Distributed Micro Analytics. Distributed micro analytics and data
manipulation will be part of 80% of Big Data and analytics deployments.
6. Self-Service. Spending on self-service visual discovery and data preparation
market will grow 2.5x faster than traditional IT-controlled tools for similar
functionality.
7. Data Monetization. Enterprises will pursue digital transformation
initiatives, increasing the marketplace's consumption of their own data by
100-fold or more.
8. Analyzable Data. The high-value data that is worth analyzing to achieve
actionable intelligence will double.
9. Actionable Information. 40% of information delivered to decision makers
will be considered by them as always actionable, doubling the rate from the
current (2015) level.
10. BDA Value. Organizations using BDA will achieve an extra US$65 billion in
productivity benefits over their less analytically-oriented peers.
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9. Big Data Digs Big Holes
• Of Security & Privacy
• Privacy Preserving Analytics
• Lapses/Cases
• How to Approach the Issues?
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10. Of Security/Privacy
• «These days, when people over 80 in Beijing take a bus, see a
doctor or spend money, their activities are digitally tracked by
the government, as part of an effort to improve services for
the country's rapidly growing elderly population.» Wat, 2016.
• Today’s initiative, tomorrows standard: ‘Smart homes’:
appliances, utility consumption, security systems, all media
sources are all connected and monitored via our smartphones,
tablets and smartwatches not to mention remote
management service sites. How to maintain a privacy-
preserved safe environment? (Vickery, 2016)
• «A service like IBM's Personality Insights can build a detailed
profile of you, moving well beyond basic demographics or
location information.» Ryoo, 1016.
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11. Of Security/Privacy
• The President’s Council of Advisors on Science and Technology
(PCAST):
• Indicated that «the privacy challenges big data poses in a world
where technologies for re-identification often outpace privacy-
preserving de-identification capabilities»
• Recommended «adopting policies that stimulate the use of
practical privacy-protecting technologies» PCAST 2014.
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12. Lapses/Cases
• «Big data for categorizing people should be used with caution»
• «… big data could result in patterns that distracted from core issues and
could be open to politically-influenced interpretation.» Gillingham et al, 2016.
• «For data analytics to be useful, it needs to be theory- or problem-
driven, not simply driven by data that is easily available.»
• ‘Street light phenomena’: Twitter users are atypical compared with the
rest of humanity:
• "WEIRDO" problem of data analytics: most people are not Western,
Educated, Industrialized, Rich, Democratic and Online. Moritz, 2016.
• Data breach cases: too many to list here but a few examples follow:
• eBay: 145 M users
• LinkedIn confirms 2012 hack exposed 117M user passwords
• Report: Three of five Californians may have had data stolen in 2015
• And, …
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13. Big Data - Big Numbers
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It’s in the news: The Wall Street Journal, Sect. D-
Technology, June 10,2016:
33 M Twitter account PWs are announced on
LeakedSource!

14. Optimism or Wishful-ism
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15. How to Approach the Issues?
• According to CompTIA's 2016 report titled "The International Trends
in Cybersecurity", about three fourths of organizations have
experienced at least one security breach or incident in the past year,
with about 60 percent of breaches categorized as serious.
Cybersecurity 2016.
• What can then companies do to protect information assets?
«Countermeasures such as encryption, access control, intrusion
detection, backups, auditing and corporate procedures can prevent
data from being breached and falling into the wrong hands.»
Security should promote privacy.
• «Banning large-scale data collection is unlikely to be a realistic
option to solve the problem. Whether we like it or not, the age of
big data has already arrived. We should find the best way of
protecting our privacy while allowing legitimate uses of big data,
which can make our lives much safer, richer and more productive.»
Ryoo,2016.
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16. How to …
• «For example, when used legitimately and securely, big data
technology can drastically improve the effectiveness of fraud
detection, which, in turn, frees us from worrying about stolen
identities and potential monetary loss.
• «Transparency is the key to letting us harness the power of big
data while addressing its security and privacy challenges.
Handlers of big data should disclose information on what they
gather and for what purposes.
• «In addition, consumers must know how the data is stored,
who has access to it and how that access is granted. Finally,
big data companies can earn public trust by giving specific
explanations about the security controls they use to protect
the data they manage.» Ryoo,2016.
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17. So What?
• BDA: tool or outcome?
• How-to Guide
• Advanced Analytics
• A Little Help from AI
• Edge BDA?
• BDA Goes Better with Semantics
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18. BDA: tool or outcome?
• BDA may be in need of a How-to Guide.
• Here are two examples
• Apparently they are not generic nor universal
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19. BDA: How to Go About It? (Parsons,2015)
• Many confuse data collection and data utilization as the same thing, or at
least being very similar.
• What is the impact of spending too much time trying to utilize the new
pile of information?
• Time suck
• Dwelling on details that do not impact the business
• The anchoring effect
• “That is what the numbers say ….”
• Does the tool save your time or steal your eyeballs?
• Hire a dedicated analysis person
• Ask discrete questions
• Plan your logs in advance for utilization, not collection
• Focusing
• FIND THE RIGHT TOOL!
• Discover what is happening, what is not happening, and what is out of
normal.
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20. Advanced Analytics:
A Use Case
• Gartner advises(Customer Engagement, 2015):
• Use Analytics to Measure the Present State of Affairs
• Determine Improvements , Where and How
• Select the Technologies to Drive Advanced, Predictive Capabilities
• Select the Technologies to Drive Prescriptive Capabilities
• Find the Business Analysts With the Advanced Analytics Skills
Required
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21. Case: Customer Service Benefits From
Advanced Analytics (CustomerEngagement,2015)
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22. Case: FocusAdvancedAnalyticson
Measurementsand Goals(CustomerEngagement,2015)
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23. Advance Analytics
Advanced analytics may mean several approaches in different
cases:
• Predictions/Forecasting/Deep Learning/Scoring –
Predicting/projecting to future values:
• Through statistics,
• By AI / machine learning models
• Experiment Design & Testing –
• Understanding the cause/variance, the drivers of variability,
• In order to improve a process or a task
• Optimization – Finding the optimal solution.
(Hariharan 2016)
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24. Edge BDA?
• The Internet of Things (IoT) promises to change everything by
enabling “smart” environments which is destined to generate
huge data.
• «For example, the current Airbus A350 model has close to
6,000 sensors and generates 2.5 Tb of data per day, while an
even newer model – expected to be available in 2020 – will
capture more than triple that amount!»
• We will need to develop distributed micro analytics and data
manipulation, a.k.a. ‘analytics at the edge’!
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25. A Little Help from AI
• A little help from AI will go a long way! (Q&A: AI & The “Industrial Revolution” in
IT):
• “AI can also help humans manage the immense increase in data
available in order to make better business decisions."
• "In the next five years, a majority of enterprises will adopt – if
they haven’t already – expert systems, robotics and virtual agents
or assistants. Within five to ten years, it is unlikely anyone will not
interact with these technologies on a daily basis at work."
• "Initially, AI adoption will focus on making the business processes
we use today far more efficient and equip us to manage higher
volumes of data, as well as customer interactions. The next five
years will see the development of radically different business
processes as the potential of AI is better explored.”
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26. BDA Goes Better with Semantics
• Big Data is transformed into “Smart” Data when processed and
analyzed properly, thus reveal huge amounts of useful information.
This in turn avails better-founded, more robust predictions and
hugely improved decision-making. New predictive and prescriptive
analytic approaches help realize this outcome.
• Real meaning and relations of the data are still hard-coded to data
formats and applications with concomitant difficulty of repurposing
the data.
• Semantic technologies on the other hand encode meaning of data
explicitly and independent from its consumer application thus
enabling machines and people alike process it.
• Semantic technologies provide a semantics-rich abstraction layer on
top of data and processes which facilitate dealing with high amounts
of heterogeneous data.
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CFP BDSDST 2016

27. BDA Goes … continued
• "… using Big and Smart Data as well as methods and tools
based on semantic technologies will provide more
transparency, enable precise and well-founded decisions and
improve planning processes, which will result in more efficient
and user-centric processes and systems …"
• "Integrating things, data and semantic opens opportunities for
knowledge discovery, and further makes it possible to provide
advanced and intelligent services." CFP SI Big Data Fusion in IoT.
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CFP BDSDST 2016

28. Best Semantics Tool
• PROTÉGÉ :
• «A free, open-source ontology editor and framework for
building intelligent systems»
• Developed by the Stanford Center for Biomedical Informatics
Research (BMIR) at the Stanford University School of Medicine.
• «As healthcare and biomedicine overflow with more data than
we can deal with, and as the knowledge base of medicine and
biology expands exponentially», BMIR focus on developing the
tools and methods needed to translate biomedical data into
actionable insights.
• And, attachable reasoner and visualizer APIs.
• Most commonly and extensively used semantics tool by
ontology engineers for ANY domain of interest.
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http://protege.stanford.edu/about.php

29. Questions? Comments?
• Welcome!
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30. References
• SI in Omics-based Medicine (2016). http://www.hindawi.com/journals/bmri/si/503682/cfp/
• Q&A: AI & The “Industrial Revolution” in IT. IDG Connect. Aug. 21, 2014.
http://www.idgconnect.com/abstract/8669/q-a-ai-the-industrial-revolution-it
• What will the workplace of 2026 look like? http://www.idgconnect.com/abstract/13248/what-
workplace-2026-look
• Qiao Li, Chris Zhang, & Chwee Kan Chua (Dec. 2015). IDC FutureScape: Worldwide Big Data and
Analytics 2016 Predictions. APEJ Implications. An IDC Excerpt.
http://thefutureofanalytics.com/idc-futurescape-predictions/
• What will health tech mean for ordinary people in 2026?
http://www.idgconnect.com/abstract/15263/what-health-tech-mean-ordinary-people-2026
• 100 Data and Analytics Predictions Through 2020. Gartner Report preview, 24 March 2016, Doc
#G00301430. https://www.gartner.com/doc/3263218/-data-analytics-predictions
• CFP: 2nd International Workshop on Big Data, Smart Data and Semantic Technologies – BDSDST
2016. http://www.informatik2016.de/1171.html
• CFP Special Issue on Big Data Fusion in Internet of Things.
http://www.journals.elsevier.com/information-fusion/call-for-papers/special-issue-on-big-data-
fusion-in-internet-of-things
• Louise Wat (May 30, 2016). Beijing tracks the elderly as they take buses, go shopping.
http://phys.org/news/2016-05-beijing-tracks-elderly-buses.html
• Jungwoo Ryoo (March 23, 2016). Big data security problems threaten consumers' privacy. The
Conversation. http://phys.org/news/2016-03-big-problems-threaten-consumers-privacy.html
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31. References …
• Philip Gillingham et al. Big Data in Social Welfare: The Development of a Critical Perspective on
Social Work's Latest "Electronic Turn", Australian Social Work (2016). DOI:
10.1080/0312407X.2015.1134606
• Mark Moritz (May 17, 2016). Big data's 'streetlight effect'—where and how we look affects what
we see. The Conversation. http://phys.org/news/2016-05-big-streetlight-effectwhere-
affects.html
• Trevor Parsons (Jan. 12, 2015)· How to Avoid the Big Data Black Hole. Big Data Zone.
https://dzone.com/articles/how-avoid-big-data-black-hole
• Drive Customer Engagement With Advanced Analytics. Gartner Report, 14 May 2015, Doc #
G00277298. https://www.gartner.com/doc/3053417?refval=&pcp=mpe#-1890094435
• PCAST (2014). PCAST Releases Report on Big Data and Privacy. May 1, 2014.
https://www.whitehouse.gov/blog/2014/05/01/pcast-releases-report-big-data-and-privacy
• Ramesh Hariharan (2016). Data Analytics: Past, Present and Future. Blog.
http://www.latentview.com/blog-data-analytics-past-present-and-future/
• Nate Vickery (June 6, 2016). Smarthome Security Concerns: The Question of Privacy.
http://www.iotcentral.io/blog/smarthome-security-concerns
• Bill Schmarzo (June 7, 2016). The Internet of Things (IoT) and Analytics at The Edge.
http://www.gladwinanalytics.com/blog/the-internet-of-things-iot-and-analytics-at-the-edge
• Cybersecurity Breaches Hit Nearly Three in Four Organizations.
http://www.securitymagazine.com/articles/87104-cybersecurity-breaches-hit-nearly-
three-in-four-organizations
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32. Training Sources on BDA
• https://www.coursera.org/
• https://www.udacity.com/
• http://bigdatauniversity.com/
• Udemy: https://www.udemy.com/
• https://www.edx.org/
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