TechWise with Eric Kavanagh, Dr. Robin Bloor and Dr. Kirk Borne
Live Webcast on July 23, 2014
Watch the archive: https://bloorgroup.webex.com/bloorgroup/lsr.php?RCID=59d50a520542ee7ed00a0c38e8319b54
Analytical applications are everywhere these days, and for good reason. Organizations large and small are using analytics to better understand any aspect of their business: customers, processes, behaviors, even competitors. There are several critical success factors for using analytics effectively: 1) know which kind of apps make sense for your company; 2) figure out which data sets you can use, both internal and external; 3) determine optimal roles and responsibilities for your team; 4) identify where you need help, either by hiring new employees or using consultants 5) manage your program effectively over time.
Register for this episode of TechWise to learn from two of the most experienced analysts in the business: Dr. Robin Bloor, Chief Analyst of The Bloor Group, and Dr. Kirk Borne, Data Scientist, George Mason University. Each will provide their perspective on how companies can address each of the key success factors in building, refining and using analytics to improve their business. There will then be an extensive Q&A session in which attendees can ask detailed questions of our experts and get answers in real time. Registrants will also receive a consolidated deck of slides, not just from the main presenters, but also from a variety of software vendors who provide targeted solutions.
Visit InsideAnlaysis.com for more information.
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How Can Analytics Improve Business?
1. Grab some coffee and enjoy
the pre-show banter before
the top of the hour!
2. “How
Can
Analy,cs
Improve
Business?”
TechWise
Webcast
|
July
23,
2014
3. +
Guests
Host: Eric Kavanagh
CEO,
The Bloor Group
Dr. Kirk Borne
Data Scientist,
George Mason University
Dr. Robin Bloor
Chief Analyst,
The Bloor Group
PLUS:
Will Gorman Chief Architect, Pentaho
Steve Wilkes CTO, WebAction
Frank Sanders Technical Director, MarkLogic
Hannah Smalltree Director, Treasure Data
4. Analytics Can Help a Business:
• Streamline operations
• Improve marketing
• Raise revenue
• Identify opportunities
• Assess plans
+
Executive Summary
8. The D2D Challenge**
1. Characterize and
!me
flux
Contextualize first.
2. Collect and Curate
each entity’s features.
…then Come to the
data-driven decision!
• Data-to-Discoveries
• Data-to-Decisions
• Data-to-Dollars
9. Characteriza,on
&
Contextualiza,on
Feature & Context Detection and Extraction:
• Identify and characterize features in the data:
– Machine-generated
– Human-generated
– Crowdsourced? (= Tapping the Power of Human Cognition
to find patterns and anomalies in massive data!)
• Extract the context of the data: the source, the channel,
the data user, the use cases, the value, the re-uses …
where, when, who, how, what, why = Metadata!
• Curate these features for search, re-use, and D2D!
• Find other parameters and features from other data
sources and databases – integrate all information to
help characterize & contextualize (and ultimately make
decision regarding) each new event.
10. Characterization via Tagging & Annotation
• Report entity’s features & characteristics back to the
database for search, retrieval, sharing, and reuse
• Individual (or groups of) entities (objects and/or
events) are tagged and annotated ...
– with new knowledge discovered
– with related data/information of any kind
– with common knowledge about those things
– with inter-relationships between entities and their properties
– with concepts
– with context
– i.e., assertions (e.g., classifications, interpretations, quality
flags, relationships, references, common knowledge,
learned knowledge, inter-connectivity with other entities)
– with data collection parameters
– with sensor channel descriptors
Semantics!
Data integration
Provenance
(for data curation)
11. Characteriza,on
&
Contextualiza,on
Feature & Context Detection and Extraction:
• Identify and characterize features in the data:
– Machine-generated
– Human-generated
– Crowdsourced? (= Tapping the Power of Human Cognition
to find patterns and anomalies in massive data!)
• Extract the context of the data: the source, the channel,
the data user, the use cases, the value, the re-uses …
where, when, who, how, what, why = Metadata!
• Curate these features for search, re-use, and D2D!
• Find other parameters and features from other data
sources and databases – integrate all information to
help characterize & contextualize (and ultimately make
decision regarding) each new event.
13. Then
what?
Get down to business with the Curated
Collection of Characterizations and
Contextualizations:
• Data Analytics:
– Outlier / Anomaly / Novelty / Surprise detection
– Clustering (= New Class discovery)
– Correlation & Association discovery
• D2D:
– Data-to-Discoveries
– Data-to-Decisions
– Data-to-Dollars
14. The
Business
Analyst-‐in-‐the-‐Loop
Tags,
annota,ons,
features,
and
context
–
– These
can
be
…
• measured
(by
observa,on),
or
• inferred
through
machine
learning,
or
• provided
by
human
analysts.
– The
resul,ng
synergy
yields:
• improved
or all 3 of these
processes
simultaneously.
training
sets,
more
accurate
predic,ve
models,
fewer
false
posi,ves/nega,ves,
ac,ve
learning,
efficient
human
interven,ons
– Combining
machine
learning
on
Big
Data
with
the
power
of
human
cogni,on
for
discovery
(e.g.,
using
Data
Visualiza,on,
Visual
Analy,cs,
Immersive
Data
Environments,
or
Crowdsourcing)
therefore
augments
and
accelerates
discovery,
insights,
and
D2D.
17. The Data Analysis Budget
u Data Analysis is
Business R&D
u The focus is on
business process
u The outcome of successful
R&D is a changed process
u Think of manufacturing for
a useful example
19. What is a Data Scientist?
u Project manager
u Qualified statistician
u Domain Business expert
u Experienced data
architect
u Software engineer
(IT’S A TEAM)
20. The Impact of Machine Learning
Machine learning is changing the process
(for the BUSINESS ANALYST & the DATA SCIENTIST)
BUT the analytics team needs to understand IT!!
21. Take Note!
You can know more
about a business
from its data than
by any other
means
22. There are Two Issues for the Business
Can you get the
Can you get the
TECHNOLOGY right?
PEOPLE right?
&
33. WebAction® delivers the leading
Real-time App Platform
enabling the next generation of
Data Driven Apps
for the Agile Enterprise
34. Acquire Store Process
Batch Reactive
RDBMS EDW BI / Analytics
Structured
Data
Machine
Data
Click Location
Stream
Structured
Data
Machine
Data
Real-time Proactive
Click Location
Stream
REALTIME BARRIER
Data Driven
Apps
RDBMS
Hadoop
Acquire Process in Memory Store
35. Distributed DIM
Processor
Distributed
WAction Cache
Metadata
High Speed Data Acquisition
WActionStore
Transaction Data
Social Feeds
Tungsten Device Data Visualization
RDBMS
Big Data
Infrastructure
Industry Data
Enterprise
Applications
Enterprise Data
Warehouse
Data Driven Apps
System/ IT Data
36. Security
Event
Processing
Cloud
Application
Control
Risk & Fraud
Alerting
Quality of
Service
Management
Consumer
Analytics
DataCenter
Management
