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Ten 2015 Technology Predictions
1. Ten 2015 Technology Predictions
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Dr. Rado Kotorov
Chief Innovation Officer, Information Builders
Rick F. Van der Lans
Independent Analyst, R20/Consultancy BV
15 January 2015
2. 1: IoT Gains Momentum
Prediction: IoT Will expand
significantly in manufacturing,
energy sector, healthcare,
logistics, and other industries.
Fact: GE has generated $1 billion
in incremental revenues form IoT
and PaaS in 2013.
Action: IoT data can be cost
effectively gathered in columnar
high performance databases (like
Hyperstage) for quick analysis,
discovery, and experimentation.
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Imagine the possibilities in a hyper-connected world…..
3. 1: IoT Gains Momentum
Connected devices include
thermostats, cars, lights,
alarms, shoe insoles
Car industry example
Currently each vehicle has
60-100 sensors
Future: 200 sensors per car
2020: Total 22 billion sensors
used in the automotive
industry
Cisco: 37 billion new things will
be connected by 2020
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Imagine the possibilities in a hyper-connected world…..
4. 2: Dealing with the data deluge
Prediction: Most data will be
analyzed before it is fully processed
and put into a data warehouse.
Social and unstructured data are
becoming more analytically
accessible.
Fact: The volume of business data
worldwide, across all companies,
doubles every 1.2 years.
Action: Adopt a data lake approach
– access and analyze first, and
integrate later. Use search-BI tools
to create apps for structured and
unstructured data analytics.
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Imagine when data flows in from everywhere…
5. 2: Dealing with the data deluge
Tools must allow us to sort and
find quickly
Complex, multi-step
architectures are not flexible
enough
Integrated solutions required
to avoid reinventing the wheel
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Imagine when data flows in from everywhere…
6. 3: Apps and self-service
Prediction: Most companies will
implement different self service
for different stakeholders – tools
for the analysts and apps for front
line employees.
Fact: BI has a less than 30
percent adoption rate in the
enterprise today.
Action: Turn analysis and insights
into custom InfoApps for on-the-
job decision support.
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Analysis and insights
create opportunities!
Operational apps create
value by changing behavior!
7. 3: Apps and self-service
Self-Service for the masses
Self-service is moving
upstream and must move
downstream
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Analysis and insights
create opportunities!
Operational apps create
value by changing behavior!
8. 4: The analytics skills gap
Prediction: Companies will not
be able to fill the skill gap.
Therefore, CDOs and CAOs will
try to commoditize analytics.
Fact: The demand for people
with deep analytical skills is 10
times greater than supply.
Action: Commoditize analytics
with infoapps and appstore
like portals for employees.
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Finding and hiring good data scientists…
9. 4: The analytics skills gap
Data is still considered a by-
product
Data is produced for internal
consumption only
Data must be regarded as a
key product
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Finding and hiring good data scientists…
10. 5: Machine learning
Prediction: To bridge the skills
gap and to cope with highly
dimensional data deluge
companies will adopt machine
learning
Fact: IBM Watson is here and
ready for business
Action: Use machine learning
in combination with data
discovery to explore the field
and provide faster time to
market analytics
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“Robots will be smarter than humans within 15 years,
Google’s new chief on artificial intelligence has claimed.”
11. 5: Machine learning
Many BI systems only do
reporting
ROI of reporting hard to
calculate
Analytics is the way to go
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“Robots will be smarter than humans within 15 years,
Google’s new chief on artificial intelligence has claimed.”
12. 6: Master data management (MDM)
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The quest for the golden record…
Prediction: The implementation
cycles for MDM will shrink
drastically from a couple of years
to a few months with new and
innovative approaches.
Fact: Miscoding and billing errors
from doctors and hospitals
totaled $20 billion in USA.
Fact: The average billion-dollar
company is losing $130 million a
year due to poor data
management.
Action: Adopt an MDM platform
with built in templates, wizards &
best practices approach.
13. 6: Master data management (MDM)
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The quest for the golden record…
MDM will only be a success if
it’s setup in a flexible way,
technologically and
organizationally
15. 7: Data warehouse decline
Prediction: Unmodelled data
analytics will grow due to
competitive pressure. NoSQL,
Columnar and in-memory offer
alternatives to DW for many use
cases.
Fact: Relational databases still
dominate the market, but 30% to
35% of enterprises have invested
in big data. Is it a tipping point?
Action: Conduct powerful
analytics against columnar, in-
memory, and Hadoop using
standard query and analysis tools.
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Imagine how quickly data can be analyzed if data modeling
and schemas were not necessary….
16. 7: Data warehouse decline
The future is for the Logical
Data Warehouse
Multiple data sources using
different storage
technologies together
forming one logical database
Big data is too big to move
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Imagine how quickly data can be analyzed if data modeling
and schemas were not necessary….
17. 8: Tech gets personal
Prediction: The benefits of
predictive analytics are great, but
many companies will be lured to
buy easy to use tools, ignore the
pitfalls, and fail.
Fact: Deloitte research shows
more than 60% of companies
have experienced project failure.
Action: Implement verification
processes and commoditize
analytics with expert certified
InfoApps.
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Is your prediction scientifically sound?
19. 9: Mobile workforce
Prediction: Gartner predicts that
over 50% of BI users will be
mobile users.
Fact: BI Scorecard: “BI adoption as
a percentage of employees
remains flat at 22%, but
companies that have successfully
deployed mobile BI show the
highest adoption at 42% of
employees.”
Action: Offer self-service BI with
an appstore like portal and
InfoApps.
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If BI and analytics could be downloaded from an appstore?
20. 9: Mobile workforce
The ROI of mobile analytics is
not clear
Mobile analytics and
consumer-driven analytics
could become a marriage
made in heaven
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If BI and analytics could be downloaded from an appstore?
21. Vote:
What percentage of your users do you think will
be accessing BI on mobile devices in 2 years
time?
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22. 10: The CIO transformed
Prediction: Successful CIOs will
transform their roles into
business leadership roles and
eventually become CEOs.
Fact: Of 384 hospitals only one
selected the CIO as the next CEO
in 2014.
Fact: GE CEO says, “Every
company will be a software
company.”
Action: Use software to transform
processes, organizational culture,
customer facing experience, and
to monetize data.
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The rise of the techno-leader
23. 10: The CIO transformed
More in-depth knowledge of
technology needed on c-level
What can we learn from the
CEOs of Google, Facebook, and
Twitter?
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The rise of the techno-leader
25. Further Resources
Blog post: Gartner’s 2015 Tech Trends Lead To
Pervasive BI
Webinar: Big Data + Enterprise Data = Big
Information, 15 January 2015, 14.00 GMT /
15:00 CET
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26. Questions?
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Rick F. van der Lans, R20/Consultancy BV
@rick_vanderlans
Rado Kotorov, Information Builders
@rado_kotorov