Succeeding with Analytics: Mastering People, Process, and Technology
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Transcript of Succeeding with Analytics: Mastering People, Process, and Technology
Succeeding with AnalyticsMastering People, Process, and Technology
Wayne W. EckersonPrincipal Consultant, Eckerson Group Dr. Rado KotorovChief Innovation Officer, Information Builders
© Eckerson Group LLC 2
What’s in a Name?Data
Warehousing(Early 1990s)
Business Intelligence(Early 2000s)
Performance Management(Mid 2000s)
Big Data/ Analytics(2010s)
© Eckerson Group LLC 3
What’s in a Name?
DATA INSIGHTS ACTION
Data Warehousing(Early 1990s)
Business Intelligence(Early 2000s)
Performance Management(Mid 2000s)
Big Data/ Analytics(2010s)
© Eckerson Group LLC 4
What’s in a Name?
DATA INSIGHTS ACTION
DATA ACQUISITIONETL, data modeling, data quality, data warehousing
IT ENVIRONMENT
Reports, analysis, dashboards, predictive analytics
DATA DELIVERY
BUSINESS ENVIRONMENT
Data Warehousing(Early 1990s)
Business Intelligence(Early 2000s)
Performance Management(Mid 2000s)
Big Data/ Analytics(2010s)
© Eckerson Group LLC
• Understand the past– “Which campaigns provided
the best return?”• Optimize the present
– “Which packaging provides the best lift in sales?”
• Predict the future – “Which customers are likely to
respond to this offer?”
Why Analytics?
© Eckerson Group LLC
• Right people• Right tools• Right architecture• Right organization
Analytics Success Factors
© Eckerson Group LLC
Right People
CONSUMERS
• Data Consumer• Data Explorer• Data Analyst• Data Scientist• Statistician
PRODUCERS
• Report Analyst • Data Engineer• Business Developer• App Developer
© Eckerson Group LLC
TOOLSData
ConsumerData
ExplorerReport Analyst
Data Analyst
Data Scientist
Data Enginee
r
KPI dashboards
Ad hoc reports
Report authoring
Ad hoc discovery
Predictive modeling
Data development
Right Tools
• KPI dashboards = Interactive KPI reporting; locked down data• Ad hoc reports = Modifiable reports that expose data model to data explorers or search BI• Report authoring = Create reports from scratch from semantic layer • Visual discovery = Connect to data sources, mash the data, and visualize results• Predictive modeling = Data science tools• Data development = SQL, ETL and other tools
Lines of Support
Top Down
Bottom up
Casual Users Power Users
Expo
se o
n De
man
d
© Eckerson Group LLC
Source Data
(Relational and NoSQL, internal,
external, devices)
On Premise, Cloud, or Hybrid
Data Hub
(Integrated Tables)
MoveStream
FlattenLink
Business Views
(Subject-specific, physical or
virtual models)
Landing Areas
(Raw Tables)
Analytic Applications
(Reports, dashboard, embedded analytics, custom applications)
Data Consumer (50%)
Poin
t and
clic
kSe
arch
Data Explorer (40%)Dr
ag/D
rop/
Edit
Ad h
oc re
port
s
DesignConform
CreateRefine
Data Analyst (8%)
Conn
ect,
disc
over
,m
ash,
visu
alize
Data Scientist (2%)
Conn
ect,
prep
are,
mod
el, s
core
RDBMS, Hadoop, Spark, Cloud PaaS
Systems Analysts
100/0
Data Engineers
80/20
Business Developers
30/70
Data Pipelining, DW Automation, Streaming
DB Views, DV tools APIs, SDKs, IDEs
With permission
With permissi
on
KEY:
Da
ta/B
usin
ess s
kills
ARCH
ITEC
TURE
DEVE
LOPE
RSBU
SIN
ESS
USE
RSTO
OLS Analytic Platforms, App Development
App Developers
20/80
Operationalized models
Data Mining Toolkit
Statistician
Top-Down: Silver ServiceBottom-up: Self ServiceKE
Y: %
=%
of B
usin
ess U
sers
Enterprise Governance Grassroots Governance
Operations
Data Catalog
Data Prep Data
Prep
© Eckerson Group LLC
Right Organization
Director/VPBI tools specialists
Data architectsETL developers
BA Team
Business Analytics Council
Executive Committee – Business unit sponsorsFacilitated by BA Head
Working Committee – Business Unit Analyst ManagersFacilitated by BA Head and Relationship Managers
Analytics Forum – Business unit analysts and data scientistsFacilitated by BI Relationship Managers
Analytics Dir/VPStatisticians/Data Scientists
Business UnitsAnalyst ManagersBusiness analystsReport analysts
Source System – Owners
- DBAs
BA Relationship Managers BA Liaisons
1 per unit 1 per system
40+ Years of Sustained InnovationMaking Money with Analytics
Dr. Rado KotorovChief Innovation Officer
Not Your Physical Assets; Data Is the Most Strategic AssetInfonomics is the new management science about how to manage data assets
Bitcoin is data!
From Data Management to Data Monetization
You maximize the business value of your information investments through complete information management and pervasive business intelligence and analytics.
IB Platform is Built for Data MonetizationThe methodology for data monetization is aligned with our technology
Decision ManagementApplications
Valu
eHigh
Low
Raw Data Integrated andEnriched Data
AnalyzedInformation
Repurpose Information forOther Revenue Generation Use Cases
Land ofOpportunities
Business Use of Information
IT Value-Added
Operational
Value-Added
Business
Value-Added
Customer
Value-Added
AnalyticalTools
IT Tools InfoApps™(Analytic Applications)
CustomerFacingInfoApps™
Data Assets Data Monetization
Managing The Data Value Chain
Where Do We See The Opportunities?
Opportunity 1: Operationalize AnalyticsWhen analytics is implemented, operationalization is never being considered
Only 22% of employees get BI 90% of BI projects fail to
produce ROI
The secret to success is in empowering the 78%
19
Why are the 78% so important?
"In the study of organizations, the employee must be the focus of attention, for the success of the structure will be judged by his performance within it".
Herbert Simon, Nobel Prize winner for studies in decision-making in 1978
Money Are Made in Operations
20
Insights create opportunities, but only operationalization turns insights into value
21
Empower the Mechanics to Save Money
An InfoApp from Information Builders available in 14 different languages for 60,000+ users in 14,000 dealerships. Helps employees make on the job repair-or-replace decisions and save Ford $60 million per year.
22
Opportunity 2: Big Data Leads to More CustomersPeople discuss only big data analytics, but what about getting more customers?
23
Empowering 260,000 Small Advertisers
Yellow Pages provides advertisers information to measure the return on their advertising dollars and track the success of their campaigns:
Approximately 52 billon rows (nine TB) of raw data per day
Response rate 2 to 10 seconds
24
Empowering 350,000 Merchants with Spend Analytics
25
Opportunity 3: Empower the Consumer With AnalyticsWhy not consumerise and commoditize BI and analytics ?
26
Billions of Documents Are Distributed to ConsumersEvery document is an opportunity to consumerise BI and analytics
20Billion
10Per
month
137Pages
71%No
HTML
10%Provide Linking
14%Navigatbe
27
Static PDF Leaves the Consumer PowerlessAll static PDFs are a missed opportunity to consumerise BI and analytics
98%static
28
PDF (No analytics) vs ADF (For In-document analytics)IB Analytical Document Format allows to put the analytics in every document
Each PDF file encapsulates:(1) a complete fixed-layout, (2) fonts & images(3) text, data, and charts(4) Requires a reader to render file
Each ADF file Encapsulates:(1) a complete fixed-layout, (2) fonts & images(3) text, data, and charts(4) Requires a reader to render file(4) Interactive Analytic Engine(5) Responsive design to fit any device
PDF (Portable Document Format) ADF (Analytical Document Format)
29
Distributing 2 Million 401K Statements MonthlyHuge savings, high adoption, increased customer satisfaction
Principal Financial Group:A $2.80 to print, stuff, mail,
support17% switched to eStatements
within three months
30
Thank you