The Briefing Room with Dr. Robin Bloor and Modus Operandi
Live Webcast July 28, 2015
Watch the Archive: https://bloorgroup.webex.com/bloorgroup/onstage/g.php?MTID=efc4082d9b0b0adfcd753a7435d2d6a1b
The analytic bottlenecks of yesterday need not apply today. The boundaries are also falling thanks in large part to the abundance of third-party data. The most data-driven companies these days are finding creative ways to dynamically incorporate data from within and beyond the firewall, thus building highly accurate, multidimensional views of their business, customer, competition or other subject areas.
Register for this episode of The Briefing Room to hear veteran Analyst Dr. Robin Bloor as he explains the magnitude of change that's occurring in the world of data, why it's happening now, and how you can take advantage. He'll be briefed by Mike Gilger and Boris Pelakh, who will showcase their company's enterprise analytics platform, which combines a range of battle-tested functionality to deliver dynamic situational awareness that can leverage a comprehensive array of data sets. They'll explain how the platform's reasoner benefits from a highly scalable rules engine, and a flexible modeling capability that can optimize data storage virtually on the fly.
Visit InsideAnalysis.com for more information.
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Welcome
Host:
Eric Kavanagh
eric.kavanagh@bloorgroup.com
@eric_kavanagh
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Reveal the essential characteristics of enterprise
software, good and bad
Provide a forum for detailed analysis of today s innovative
technologies
Give vendors a chance to explain their product to savvy
analysts
Allow audience members to pose serious questions... and
get answers!
Mission
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Topics
July: SQL INNOVATION
August: REAL-TIME DATA
September: HADOOP 2.0
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Analyst: Robin Bloor
Robin Bloor is
Chief Analyst at
The Bloor Group
robin.bloor@bloorgroup.com
@robinbloor
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Modus Operandi
Modus Operandi offers Movia, a big data analysis platform
The platform includes semantic context capabilities that
enable rules-based pattern recognition and alerts
Movia uses a combination of rules and ontologies to foster
reasoning, inferencing and knowledge representation
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Guest: Mike Gilger
Mike Gilger is
Director of Intelligence
& Software Solutions at
Modus Operandi
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Perceptions & Questions
Analyst:
Robin Bloor
12. Semantics
Semantics: the branch of linguistics and logic
concerned with meaning. There are a number of
branches and sub-branches of semantics, including
formal semantics, which studies the logical aspects
of meaning; lexical semantics, which studies word
meanings and word relations; and conceptual
semantics, which studies the cognitive structure of
meaning.
13. Most Databases Simply Store the Nouns
Name Car
John Doe Porche
Janet Doe Prius
Lewis Hamilton Mercedes
u Database tables store subjects
and objects but omit
predicates
u Does John Doe “own,” “lease”
or “rent,” or has he simply
borrowed the Porche?
u Does Lewis Hamilton “drive”
or “race” the Mercedes?
u Hence triples….
14. Hey Jude – As a Graph…
Hey Jude
Na
your heart
your skin
be#er
be#er
made to
begin
start
her
let me down
be afraid
make it bad
a sad song
and
Meaning (human
expression) fits
naturally onto a
graph.
There are nouns,
pronouns, adjectives,
verbs, adverbs,
articles, prepositions,
etc. Also tenses.
They provide both
meaning and context.
15. Semantic Technology
1 Unfamiliarity (it’s obscure
because it’s obscure)
2 RDBMS do not store graphs
well, and SQL is inadequate
for querying graphs
3 No common semantic BI
applications; it’s mainly
analytics
4 Semantic technology has
taken a lifetime to evolve
16. High Level Summary
u Semantic data expresses important data
relationships (predicates and context)
u Semantic data is largely unexplored
u It is ideal for MDM (ontologies are far more
complete than metadata repositories)
u In a semantic data environment, there is no
“unstructured data,” nor can there be
u Semantic processing is becoming mature…
17. The Net Net
The ultimate goal is INFERENCING:
Knowledge discovery
(rather than pattern discovery)
through semantic processing
18. u What are the “low hanging fruit” (semantic
applications) – in your company’s experience?
u How would you characterize the limitations of
a triple store? Is it your view that an RDF
database is inadequate or simply limited? What
are the compelling differences?
u How would you characterize the “predicate
store” as a database? Can it handle SQL?
u Can it handle all types of data?
19. u How well does it integrate with other
technologies?
u What is your current “largest data volume?”
u Which companies/technologies do you compete
with directly?
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Upcoming Topics
www.insideanalysis.com
July: SQL INNOVATION
August: REAL-TIME DATA
September: HADOOP 2.0
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THANK YOU
for your
ATTENTION!
Some images provided courtesy of Wikimedia Commons and http://boggletondrive.com/2011/11/14/a-
matter-of-perspective/