wayne eckerson: secrets of analytical leaders webinar
DESCRIPTION
In this Wayne Eckerson delivers an overview of his new book "Secrets of Analytical Leaders: Insights from Information Insiders." Imagine spending a day with top analytical leaders and asking any question you want. In this book, Wayne Eckerson illustrates analytical best practices by weaving his perspective with commentary from seven directors of analytics who unveil their secrets of success. With an innovative flair, Eckerson tackles a complex subject with clarity and insight.TRANSCRIPT
© 2009 VMware Inc. All rights reserved
Big Data Thought Leadership Webinar
Web: www.cetas.net Twi)er: @CetasAnaly/cs Blog: www.cetas.net/blog YouTube: www.youtube.com/CetasAnaly/cs
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Introductions
David Morris, Host Big Data Analytics Marketing – Cetas, By VMware
@jdavidmorris
Please submit your questions at anytime throughout the webinar via the chat tool.
The Secrets of Analy;cal Leaders:
Insights from Informa;on Insiders
Wayne W. Eckerson President, BI Leader Consul/ng
• Wayne Eckerson • [email protected] • @weckerson
Wayne Eckerson
4
• BI thought leader • President, BI Leader Consul/ng • Director, BI Leadership Forum • Director, BI Leadership • Former director of research at TDWI • Author
Analy;cal Leaders
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Dan Ingle, Kelley Blue Book 1. Incremental development 2. Teamwork 3. One size doesn’t fit all
Amy O’Connor, Nokia 1. Data is a product 2. Create an ecosystem 3. Change management
Darren Taylor, Blue KC 1. Create the right team 2. Get execu/ve support 3. Deliver a quick win
Eric Colson, NeIlix 1. Eliminate coordina/on costs 2. Work fast, cohere later 3. Build with context
Tim Leonard, USXpress 1. Talk language of business 2. Let business present 3. Deliver quick wins
Kurt Thearling, CapitalOne 1. Curate the data 2. Sta/s/cians are craUsmen 3. Manage model produc/on
Ken Rudin, Zynga 1. Ques/ons, not answers 2. Impacts, not insights 3. Evangelists, not oracles
Purple People • Straddle business and technology • Talk the language of business • Run the analy/cal group like a business • Recruit business people to their team • Manage “front” and “back” offices
CULTURE
Data Treated as a Corporate Asset
Performance M
easurement
Fact-‐based
Decision
s
PEOPLE Analysts
Casual and Power Users
Data Develop
ers
ORGANIZATION
Business-‐oriented BI Embe
dded
Analysts
Analy/cal Center of Excellence
ARCHITECTURE
Bo^om
-‐up Top-‐do
wn
Sandboxes
PROCESS
Cross-‐func/onal Collabora/on
Developm
ent M
etho
ds Project M
anagement
DATA
Unstructured
Structured
Internal External
Success framework
Create an analy;cal culture
Ken Rudin
Keystone habit: “Be evangelists, not oracles”
Idea
Test hypothesis
LiU and sa/sfac/on!
Cue
Rou;ne
Reward
Culture
Team members
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Repor;ng & Monitoring (Casual Users)
Predefined Metrics
Corporate Objec;ves and Strategy “Business Intelligence”
Data Warehousing Architecture
Casual Users
Processes and Projects
Analysis and Predic;on (Power Users)
Ad hoc queries
Analy;cs Architecture
Power Users
BI/DW Developers (Centralized)
Analysts (embedded)
Data architects, ETL developers, report developers, data administrators, DW administrators, technical architects, requirements specialists, trainers, etc.
Super users, business analysts, sta/s/cians, data scien/sts, data
analysts
TOP DOWN
BOTTOM UP
People
• Hire people with business knowledge and emo/onal IQ
• Align people with their natural strengths • Prac;ce the principle of proximity • Empower people to build complete solu/ons • Foster teamwork and trust • Allow failure
Team principles
Autonomy, mastery, purpose
Organiza/on
• Answer a meaningful ques/on • Deliver value along the way • Get a quick win • Implement scrum • Empower spanners
Deliver value fast!
... to gain credibility and momentum
Process
Business Intelligence
Analy;cs Intelligence
Con;nuous Intelligence Co
nten
t Intelligen
ce
Data Warehousing
Ad hoc query, Spreadsheets, OLAP, Visual Analysis, Analy/c
Workbenches, Hadoop
Analy/c Sandboxes
Event-‐driven
Reports and Dashboards
MAD Dashboards
Data Ware-‐ housing
End-‐User Tools
Event-‐Driven Alerts and Dashboards
Ad hoc SQL
Dashboard Alerts
Event detec/on and correla/on
CEP, Streams
Analy/c Sandboxes
Design Framework
Architecture
Repor;ng
& Analysis
Excel, Access, OLAP, Data mining, visual explora/on
Keyw
ord search, B
I too
ls,
Xque
ry, H
ive, Ja
va, etc.
MapRe
duce, XML sche
ma,
Key-‐value pairs, graph
no
ta/o
n, etc.
HDFS, N
oSQL
databses
Monitoring Casual Users
Explora/on Power Users
Architecture
Analy;cal Ecosystem
Machine Data
Web Data Hadoop Cluster
Power User
BI Server
Casual User
Operational System
Operational System
Upload & query
Query Free-‐standing Analy;cal sandbox
Logical or
Physical Data Mart
Data Warehouse
Virtual Sandboxes Top-‐down BI Bo+om-‐up BI
External Data
Alerts
Audio/video Data
Streaming/ CEP Engine
ETL
Visual discovery
tools
Event-‐driven messaging
Classic BI KEY: New Stuff
ODS
ETL
Interac/ve dashboards
BI tools market
Visual Discovery
BI FUNCT
IONAL
ITY
Enterprise Department SCOPE OF DEPLOYMENT
Top-‐down Bo^om-‐up
Repo
r/ng
Dashbo
ards
Analysis
Mining
Pixel Perfect Repor/ng Ad hoc
Reports/ Dashboards
Analyst
Data Mining Workbench
Opera/onal Reports/
Dashboards
Big Data Analy/cs Planorms
Rela/onal OLAP Mul/-‐
dimensional OLAP
Desktop Analysis (e.g. Excel) Pow
er Users
Casual Users
Tools
What is “big data”?
www.bileader.com
Yes!
a) Lots of data b) Different types of data c) High velocity data d) Purpose-‐built analy/cal database e) Distributed file system f) In-‐memory database g) A Java developer’s full employment act h) A replacement for the RDBMS i) A club for hip data people
Data “Three V’s”
Systems
Movement
Data
CULTURE
Data Treated as a Corporate Asset Perform
ance Measurem
ent
Fact-‐based
Decision
s
PEOPLE
Analysts
Casual and Power Users
Data Develop
ers
ORGANIZATION
Business-‐oriented BI Embe
dded
Analysts
Analy/cal Center of Excellence
ARCHITECTURE Bo^om
-‐up Top-‐do
wn
Sandboxes
PROCESS
Cross-‐func/onal Collabora/on
Developm
ent M
etho
ds Project M
anagement
DATA
Unstructured
Structured
Internal External
Summary
Keys: -‐ Deliver value fast -‐ Manage change -‐ Hire the right people… -‐ And point them in the right direc/on -‐ Create agile data warehouses -‐ Curate the data
Available at Amazon.com
I nominate @twi^erhandle for the #bigdata100 most influen/al #bigdata Twi^er accounts h^p://bit.ly/10QUXoo
To Vote Tweet the following with your Favs “tweet handle”
1. Wayne Eckerson @weckerson 2. J. David Morris @jdavidmorris 3. Cetas @cetasanaly/cs 4. Karthik Kannan @KarthikBigData 5. Rakish Nair @mynameisnair
www.bileadership.com 18
Ques;ons??
I’m listening! • Wayne Eckerson • [email protected] • @weckerson
Available at Amazon.com
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© 2009 VMware Inc. All rights reserved
Big Data Thought Leadership Webinar Series
Web: www.cetas.net Twi)er: @CetasAnaly/cs Blog: www.cetas.net/blog YouTube: www.youtube.com/CetasAnaly/cs
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