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C O M E T 2 0 1 7 W E L C O M E T O

T E C H N I C A L P A P E R P R E S E N T A T I O N

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B Y J A S O N C . D E N N I S O N

TRENDS IN DATA ANALYSIS

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C R A I G S C H A U B C O N T R O L E N G I N E E R I N G M A N A G E R

A U S T I N E N E R G Y

A B O U T T H E A U T H O R

Craig Schaub manages a team of Engineers, Analysts and

Technicians who maintain Austin Energy’s real-time control systems

such as SCADA and ADMS.

He has more than 30 years’ experience in power system automation

as well as protection, telecommunications and metering.

J A S O N C . D E N N I S O N

M A N A G E R – L A B O R A T O R Y &

A N A L Y T I C A L S E R V I C E S

S D M Y E R S

A B O U T T H E A U T H O R

Jason C. Dennison manages the laboratory and analytical

services team at SDMyers, the world’s largest transformer

oil testing laboratory.

He has more than 14 years’ of wide experience in:

program management across multiple industries,

transformer and related equipment testing and

maintenance, software development, Internet of Things,

and technical education as an adjunct instructor. He has

his BS in Chemical Engineering with Polymer

Specialization from the University of Akron, is a Six Sigma

Black Belt, and maintains memberships with IEEE and

PMI.

BRIEF BIO

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ABSTRACT SUMMARY

O V E R V I E W &

In th is d iscussion, we look at t rends in data analys is .

Data avai lab i l i ty is exploding, s tat ic and st reaming data

are col l id ing, and re l iab i l i ty profess ionals need to be

prepared to address the rapid ly expanding data analys is

needs wi th c lar i ty and conf idence.

L E A R N M O R E “… the possibilities of computers are very interesting – if they could be made to be more complicated by several

orders of magnitude. If they had millions of times as many elements they could make judgments.”

– Richard Feynman, “There’s Plenty of Room at the Bottom” 1959

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TREND: DATA CHAOS

Honeywell: In 2017, we est imate that only 1% of IoT data is

currently used to add value.

By 2025 IoT devices wi l l be generat ing 136 terabytes of

data annual ly.

A lso, the market for IoT wi l l be $11 Tri l l ion USD .

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TREND: STATIC & STREAMING DATA

IDC Data Age 2025: By 2025 the s ize of the g lobal

datasphere wi l l reach 163 ZETTABYTES .

IoT / Real-Time Data wi l l compr ise near ly 30% of a l l

g lobal data in that t ime.

McKinsey Global Inst i tu te: IoT data is only being used

for detect ing anomal ies…not for opt imizat ion and

predic t ion, which prov ide the greatest va lue.

Today – we use a fract ion of a fract ion of avai lab le

data AND our decision-making hasn’t caught up with

the amount of data we do have.

163 Zettabytes represents >650% growth in the next 7 years

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DATA WAREHOUSE DATA LAKE

AGGREGATE

DATA SOURCES

STRUCTURE

REPORTING

COMPILE RAW

DATA SOURCES

STRUCTURE

REPORTING

?

?

GOOD: Structured data for wide usage by users of varying expertise BAD: Structuring the data takes definition, time, and developer resources

GOOD: No structure make acquisition simple, fast BAD: Structuring the data now the responsibility of the user/requestor

TREND: BLENDED DATA ARCHITECTURE

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TREND: DATA EXTRACTION and ABSTRACTION

Data storage is increasingly HYBRID – Data

warehouses, Data lakes, SQL/MySQL/Oracle/Mongo

Databases, Operat ional f i les (Excel , Access) , Cloud

Serv ices

Data ext ract ion is cruc ia l in al igning data f rom

disparate sources, so that analys is is truthful .

Good computer scientists and analysts wi l l be the

heroes of the Informat ion Age. Good designers wi l l be

the unsung heroes of the Informat ion Age.

Structured Data

Warehouses, Data Lakes

Org/Ops Functional Databases

(SCADA, M/O, Excel)

Could Services (Salesforce,

ConstantContact)

Visualization (Tableau, Qlik, PowerBI) Statics (R) Machine Learning AI Custom App

D ATA E X T R A C T I O N ( Q U E R I E S ,

S TO R E D P R O C E D U R E S , D L L S )

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EXAMPLE: STATIC VS STREAMING

With Single Point Data, personnel are tasked wi th

decis ion-making – lack ing facts, nature is to assume the

worst or ignore the possibi l i ty of an issue

With h igher quant i ty data (assumed to be of h igh

in tegr i ty) , t rends are more apparent , and the t iming on

the P-F curve can be orders of magni tude smal ler

MONTHS

MINUTES

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TREND: DATA SCIENCE GROWTH

The only non-heal thcare job growth area in the top 5 is

Mathemat ica l Science Occupat ions, re lated to analyt ics

and stat is t ics

In the TOP 10, a s tagger ing 8 of 10 are heal thcare

re lated; the other entry is o i l /gas/min ing serv ice uni t

operators

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TREND: IT GROWTH

Cyber secur i ty

NERC – Interpretat ion & Implementat ion

IT best pract ices

Regulat ion

“Once you are inside [the system], the assumption is that you are supposed to be there.”

– Richard Bejtlich, Chief Security Strategst @ FireEye

“Every budget is an IT budget.”

– Erwin Verstraelen, CIO @ AVEVE

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TREND: DECISION RIGHTS MANAGEMENT

Decis ion r ights management (DRM) isn ’ t brand

new, though the data explos ion that dr ives DRM

value is .

The key: Clear ly ident i fy who is / who needs to be

RESPONSIBLE for a decis ion/ task, and

EMPOWER them to make decis ions by way of due

process and c lear co l laborat ion path.

Resp

onsibility

VP

Director

Manager

Supervisor

Subject  M

atter  Expert

Task  DescriptionTask  1 I I C RA CTask  2 R A C CTask  3 R A CTask  4 I ITask  5 R CTask  6 I A RA C

R Responsible  for  ensuring  completionA Accountable  for  task  or  providing  informationC Consulted  for  the  task  and/or  informationI Informed  of  the  task

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THE HORIZON

Machine learn ing & AI

Natura l language processing

SCADA … in the c loud!

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SUMMARY

The dawn of the INFORMATION AGE is here and in i t ’s

in fancy; the natura l order is DISORDER .

We’re now able to have fa i lure data near ly

INSTANTANEOUSLY , and whi le h igh value, is creat ing

chaos.

Manpower, Machines, Measurements, Methods must be

robust to address new information quick ly and

EMPOWER exper ts to take decisive, intel l igent act ion

Star t wi th the end in mind, and GET STARTED - 80%

effect iveness NOW is more valuable than 100% LATER

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P A P E R Q & A C O M E T | C O L L A B O R A T E | S H A R E

K N O W L E D G E | P R O G R E S S

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3 3 0 . 2 8 9 . 3 4 2 1 j a s o n . d e n n i s o n @ s d m y e r s . c o m linkedin.com/in/ jasoncdennison

JASON C. DENNISON

MANAGER OF LABORATORY & ANALYTICAL SERVICES

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