Go to http://www.Gartner.com in the upper right hand and you will be able to get access to some of Gartner’s free research.This assignment involves one of Gartner’s webinars. There are 2 files associated with the webinar. One is an audio file and the other is the presentation. You will need to start the audio file and then follow along with the presentation.Note: both files are on the P drive in the Commerce AccountingMacDougallAcct 3323 Fall 2016ST and BC assignments folder.Key Trends and Emerging Technologies in Advanced Analytics Gartner Webinars.mp3key_trends_in_advanced_analytics_alinden_v3_71739.pdfDeliverable: SideTrip #2: Identify three issues or challenges surrounding Advanced Analytics that you think will be the most important for management to address and explain why you think so. 1-2 paragraphs on each issue. (250-300 words total)
key_trends_and_emerging_technologies_in_advanced_analytics___gartner_webinars.rar
key_trends_in_advanced_analytics_alinden_v3_71739.pdf
sidetrip__2__key_trends_in_advanced_analytics__gartner.pdf
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© 2014 Gartner, Inc. and/or its affiliates. All rights reserved.
Gartner at a Glance
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Largest
Community
of CIOs
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Analysts
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in Nine
Industries
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Inquiries
per month
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Benchmarks
500
Consultants
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2,100
Consulting
Engagements
Key Trends in Advanced Analytics
Alex Linden, Research Director
Gartner‟s Information & Analytics – Team
CONFIDENTIAL AND PROPRIETARY
This presentation, including any supporting materials, is owned by Gartner, Inc. and/or its affiliates and is for the sole use of the
intended Gartner audience or other intended recipients. This presentation may contain information that is confidential, proprietary or
otherwise legally protected, and it may not be further copied, distributed or publicly displayed without the express written permission of
Gartner, Inc. or its affiliates. © 2014 Gartner, Inc. and/or its affiliates. All rights reserved.
Key Issues
1. Which are the areas of innovation in advanced
analytics?
2. What are some of its challenges?
3. What are some of the trends we see?
© 2014 Gartner, Inc. and/or its affiliates. All rights reserved. CONFIDENTIAL AND PROPRIETARY.
Key Issues
1. Which are the areas of innovation in advanced
analytics?
2. What are some of its challenges?
3. What are some of the trends we see?
© 2014 Gartner, Inc. and/or its affiliates. All rights reserved. CONFIDENTIAL AND PROPRIETARY.
Disruptive Uncertainty in Analytics
New processing technologies
New data sources
New data “storage” principles
New use cases
1000s of new vendors
© 2014 Gartner, Inc. and/or its affiliates. All rights reserved.
© 2014 Gartner, Inc. and/or its affiliates. All rights reserved. CONFIDENTIAL AND PROPRIETARY.
Internet of
Things
Courtesy of Intel
© 2014 Gartner, Inc. and/or its affiliates. All rights reserved. CONFIDENTIAL AND PROPRIETARY.
The Bounty: Machine Learning Use Case
Smart Traffic
Churn
Management
Predictive
Policing
Fleet
Optimization
Demand
IT Ops (Security)
Prediction
Workforce / HR
Workflow
Quality
Fraud
Management
Cognitive /
Smart Systems
drivers of
quality
fluctuations Self-Driving
Cars
& Robotics
Social Media
Recognition
Automation
Dynamic
Pricing
Recommender
Systems
Cross-Selling
Customer
Segmentation
B2B Propensity
to-Buy
Proxy Data
Failure
Prediction
Google Flu Trends
Inrix
© 2014 Gartner, Inc. and/or its affiliates. All rights reserved. CONFIDENTIAL AND PROPRIETARY.
Myths are prospering…
Big Data starts with 100 TB…
Great data scientists must have
a Ph.D in machine learning or so…
With so much data…
.. Data quality isnt so important any more
Hadoop will replace the
Data Warehouse
.. Domain knowledge is obsoleted
.. you can predict anything
Data Lakes will replace the
Data Warehouse
Tools will be so great,
that data scientists will be obsoleted.
Major Myths About Big Data’s Impact on Analytics 15 Sep 2014
Major Myths About Big Data’s Impact on Information Infrastructure 15 Sep 2014
© 2014 Gartner, Inc. and/or its affiliates. All rights reserved. CONFIDENTIAL AND PROPRIETARY.
Key Issues
1. Which are the areas of innovation in advanced
analytics?
2. What are some of its challenges?
3. What are some of the trends we see?
© 2014 Gartner, Inc. and/or its affiliates. All rights reserved. CONFIDENTIAL AND PROPRIETARY.
Advanced Analytics Definition
Advanced Analytics
Descriptive
Diagnostic
Predictive
Prescriptive
Why did it
happen
What is going
to happen?
How can we
make it happen?
What Is
Happening?
Analytics
Advanced Analytics
Simple arithmetics
Data Science
Reporting / Dashboards
Business Problem Solving
Common BI Platforms
Mathematic-based Tools
„Comfort level“
Creepy …
© 2014 Gartner, Inc. and/or its affiliates. All rights reserved. CONFIDENTIAL AND PROPRIETARY.
Key Challenges: Be use-case driven.
Challenge
Lesson learned
A.
How to find use cases?
•
•
•
B.
Make or Buy or Outsource?
Come to Gartner and tell us
about your use cases….
C.
Cloud or Premise?
…
D.
How to find Data Scientists?
Hire … or train or …
E.
How to organize a Data Science Lab?
IT, LoB, Innovation, Inhouse Consulting,
CDO / CAO, Virtual Team
F.
How to organize data supply?
Data Lakes vs Data Warehouses?
G.
How to evangelize the organization to
become „data-driven“?
See A.
H.
How to create a great „big data“
architecture?
•
•
© 2014 Gartner, Inc. and/or its affiliates. All rights reserved. CONFIDENTIAL AND PROPRIETARY.
11
Find the right team
Improve Communication
Networking
Skills trump technologies
Be use-case-driven (see A)
Where to Put the Data Scientists?
Data Scientists @ LOBs
LOB
LOB
LOB
Data Scientists @ IT
LOB
DS
Scattered Experts
• Agility
LOB
AA/DS
AA/DS
IT
LOB
LOB
LOB
DS
IT
AA/DS
LOB
DS
DS
LOB
LOB
Data Scientists as Separate BU
LOB
IT
• Cross-Functional View
• Knowledge Sharing
IT
ACE (Formerly BICC)
LOB
AA/DS
LOB
• Business Intimacy
• Proximity to Process
and Data
LOB
AA/DS
ACE
AA/DS
IT
Organizational Principles for Placing Advanced Analytics and Data Science Teams 04 Sep 2013
AA/DS = Advanced Analytics/Data Science; LOB = Line of Business; ACE = Analytics Center of Excellence
© 2014 Gartner, Inc. and/or its affiliates. All rights reserved. CONFIDENTIAL AND PROPRIETARY.
Key Issues
1. Which are the areas of innovation in advanced
analytics?
2. What are some of its challenges and lessons
learned?
3. What are some of the trends we see?
© 2014 Gartner, Inc. and/or its affiliates. All rights reserved. CONFIDENTIAL AND PROPRIETARY.
Key Trends in Advanced Analytics
new industrialization
C-level visibility
data science
New algorithms
Explosion in use cases
cognitive & smart systems
market places / „app“-stores
ensemble models
Crowdsourcing
(microwork)
hybrid
delivery models
open source
NOSQL
Citizen Data Science
Model & Decision
Management
new tools
data provider
Data
lakes
Cloud
HTAP
data
discovery
deep learning
IoT
3V
poly-structured data
new data sources
new processing
hadoop
multi-core servers
in-memory computing
skills trumps
“technology”
analytics
culture
Asking
Governance better questions
© 2014 Gartner, Inc. and/or its affiliates. All rights reserved. CONFIDENTIAL AND PROPRIETARY.
ethics
„data expeditions“
new thinking
Key Trends in Advanced Analytics
new industrialization
C-level visibility
data science
New algorithms
Explosion in use cases
cognitive & smart systems
market places / „app“-stores
ensemble models
Crowdsourcing
(microwork)
hybrid
delivery models
open source
NOSQL
Citizen Data Science
Model & Decision
Management
new tools
data provider
Data
lakes
Cloud
HTAP
data
discovery
deep learning
IoT
3V
poly-structured data
hadoop
multi-core servers
skills trumps
“technology”
Asking
Governance better questions
© 2014 Gartner, Inc. and/or its affiliates. All rights reserved. CONFIDENTIAL AND PROPRIETARY.
new data sources
new processing
in-memory computing
analytics
culture
ethics
„data expeditions“
new thinking
External
The Power of “More” Data Sources
WLAN
Economic Census
Weather
Open Data
Business Information
Crowdsourcing
Market Research
Credit Bureaus
Commercial Data
Twitter, Tumblr
Facebook,
LinkedIn
Social Media
Data
Public
Data
Geoinformation
Internal
Communities,
Blogs
Meter’s, RFID,
GPS
Sensor
Monitoring
Operational
Data
Data
Fusion
Transactions
Tabular
© 2014 Gartner, Inc. and/or its affiliates. All rights reserved. CONFIDENTIAL AND PROPRIETARY.
Customer
Interactions
Field Reports
Log-Data
Enterprise
“Dark Data”
Contracts
Non-tabular
More Data means way more junk
Big Data
~1.5 x
volume
© 2014 Gartner, Inc. and/or its affiliates. All rights reserved. CONFIDENTIAL AND PROPRIETARY.
noise
signal
~1.20 x
used
time
Trend: Signal-2-noise-ratio worsens
Reinforcing the need for better data
scientists, data management, software
tools, algorithms, governance &
industrialization!
© 2014 Gartner, Inc. and/or its affiliates. All rights reserved. CONFIDENTIAL AND PROPRIETARY.
The Rise of the Citizen Data Scientists
IBM Watson Analytics
Microsoft Azure ML
SAS Visual Statistics
By 2017, growth rates in
citizen data scientists will
outpace the growth in highly
skilled data scientists by a
factor of 5.
SAP
Lumira
Angoss
Predixion
Alpine
Ayasdi
Emcien
Beyondcore
•
•
•
Expert Data Scientists will remain rare
Tools are getting easier to use
Diagnostic Analytics, some
Predictive Analytics
Citizen data scientists will be well positioned to
“drive” data-driven culture
They can be recruited inhouse as well as
from many “adjacent” disciplines
© 2014 Gartner, Inc. and/or its affiliates. All rights reserved. CONFIDENTIAL AND PROPRIETARY.
Make vs Buy vs Outsource
BUY
MAKE
packaged apps
via workbenches
1. best ease-of-use
1. requires in-house skills
2. often “good enough”
2. analytics is differentiator
3. best time-2-solution
3. agility & control are key
4. little differentiation
OUTSOURCE
1. in-house skills not avail.
service providers
2. packaged apps not avail.
3. give up IP for sake of speed
© 2014 Gartner, Inc. and/or its affiliates. All rights reserved. CONFIDENTIAL AND PROPRIETARY.
20
Make vs Buy vs Outsource
BUY
MAKE
packaged apps
via workbenches
1. best ease-of-use
1. requires in-house skills
2. analytics is differentiator
3. agility & control are key
Hybrid
Delivery
OUTSOURCE
1. in-house skills not avail.
service providers
2. packaged apps not avail.
3. give up IP for sake of speed
© 2014 Gartner, Inc. and/or its affiliates. All rights reserved. CONFIDENTIAL AND PROPRIETARY.
21
2. often “good enough”
3. best time-2-solution
4. little differentiation
The Mechanics of
Analytics Marketplaces
App Store
External
Users*
In-Browser
Workbench
Residential
Users*
On-Premise
Workbench
“xyz” as-an-app
Analytics
Analytics Layer
Layer
Refinement /
Fusion
Data
Layer
Data Layer
Cloud
Infrastructure
Production
Model
Open Data
Data As App
© 2014 Gartner, Inc. and/or its affiliates. All rights reserved. CONFIDENTIAL AND PROPRIETARY.
Enterprise
Data
Business
Process
The Implications of
Analytics Marketplaces
App Store
“xyz” as-an-app
Monetization
World-Wide
Support
External
Users*
In-Browser
Workbench
Scale
Analytics
Analytics Layer
Layer
Residential
Users*
On-Premise
Workbench
Refinement /
Fusion
Data
Layer
Data Layer
Collaboration
Validation
Cloud
Infrastructure
Production
Model
Deployment
Monetization
Open Data
Data As App
© 2014 Gartner, Inc. and/or its affiliates. All rights reserved. CONFIDENTIAL AND PROPRIETARY.
Enterprise
Data
Business
Process
Recommendations
• Advanced Analytics will likely remain a hot segment
in the „Information & Analytics“ space for a long while.
• If Advanced Analytics or especially Big Data Explorations
are not happening, then try to consider the special
communication requirements.
• Don„t forget to look at your own staff, when recruiting
data scientists.
© 2014 Gartner, Inc. and/or its affiliates. All rights reserved. CONFIDENTIAL AND PROPRIETARY.
24
Events for
Business Intelligence &
Information Management
Professionals
Experience live analyst expertise plus much more at a Gartner event.
Gartner Business Intelligence & Analytics Summit
21 – 22 October, São Paulo, Brazil
Visit gartner.com/events
25
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OF CIOs AND SENIOR IT EXECUTIVES
Driving Digital Business
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network and advance their strategies
• Actionable take-aways for the next 6 to 12 months
and beyond
• Mastermind Interview and guest keynotes with industry
luminaries and proven leaders
• Networking opportunities that facilitate best-practice
sharing and leadership styles
• ITxpo exhibit floor with hundreds of solution providers
and emerging technology companies
September 10 – 12
Cape Town, South Africa
October 28 – 30
Sao Paulo, Brazil
October 5 – 9
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November 9 – 13
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October 14 – 17
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November 17 – 20
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October 27 – 29
Tokyo, Japan
Visit gartner.com/symposium
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27
Sidetrip #2 Big Data – Key Trends in Advanced Analytics
and access to Gartner.com (Estimated time 1.5–2 Hrs)
Go to http://www.Gartner.com in the upper right hand and you will be able to get
access to some of Gartner’s free research.
This assignment involves one of Gartner’s webinars. There are 2 files associated with the
webinar. One is an audio file and the other is the presentation. You will need to start the
audio file and then follow along with the presentation.
Note: both files are on the P drive in the Commerce AccountingMacDougallAcct
3323 Fall 2016ST and BC assignments folder.
Key Trends and Emerging Technologies in Advanced Analytics Gartner Webinars.mp3
key_trends_in_advanced_analytics_alinden_v3_71739.pdf
Deliverable: SideTrip #2: Identify three issues or challenges surrounding Advanced
Analytics that you think will be the most important for management to address and
explain why you think so. 1-2 paragraphs on each issue. (250-300 words total) Please
note when submitting assignments please only include your A# rather than your name.
…
Purchase answer to see full
attachment
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