Slides for JackBe

Wayne EckersonPrincipal Consultant, BI Leader Consulting

2

Slide courtesy of NetApp

NetApp – Enterprise BI Framework

EnterpriseAnalytics

Functional AnalyticsSales, Marketing, Product Ops,

Finance, Global Services …

Role-Based AnalyticsSales Rep, Account Manager, DM, RM, SE, Marketing

analytics, Financial analytics, Security Admin, IT Admin, Audit, Usage Tracking…

Subject Area AnalyticsCross-sell, Up Sell, Account Performance, end customer, Period Close

performance, Hourly Projected Booking Analytics…

360 Degree ViewsCustomer, Partner, Product, Service, Sales Rep, employee, user…

Improve AccountabilityMeasu

re P

erfo

rman

ce

Increase Productivity

Detailed Data

Dimensional Data

Graphical Data

Transactional Data

Unified BI platform: Build once, deploy multiple instances

3

MAD Framework

Detailed Data

Summarized Dimensional Data

Graphical Metrics Data

Detailed Transactional Data

Monitor

Analyze

Drill thru

Functionality

Executives/ Managers

Analysts

Workers

Users

4www.bileader.com

5www.bileader.com

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Market Evolution

Enterprise BI vendors

Oracle, SAP, IBM, SAS

“BI as foundation technology”

Low cost BI vendors

Microsoft, QlikTech, O

pen

Source, Cloud BI (SaaS)

“BI for the mid-market”Client/Server

Web

SOA/Web Services

Data Warehousing

Business Intelligence

Performance Management

1990s 2000s 2010

CEO,CFO, CMO, etc.

“Get the data”

“Use the data”

“Improve the business”

Analytics“Drive the business”

2007 Mega M&A:OracleHyperionSAPBusiness ObjectsIBM Cognos

Mobile

Cloud

8

Waves of BI

Bus

ines

s Va

lue

High

2010s (mainstream)

Reporting

1980s

Analysis

Prediction

Monitoring

Query, Excel, OLAP, Visual discovery

Dashboards, Scorecards

Statistics, data mining, optimization

Static & Interactive Reports

“What happened?”

“Why did it happen?”

“What’s happening?”

“What will happen?”

Low

= Reporting

= Analytics

1990s 2000s

Reporting & Monitoring (Casual Users)

Predefined metrics

Corporate Objectives and StrategyTOP DOWN- “Business Intelligence”

Processes and Projects

Analysis and Prediction (Power Users)

Ad hoc queries And data

BOTTOM UP – “Analytics Intelligence”

Analysis Begets Reports

Reports Beget

Analysis

Pros: -Alignment-Consistency

Cons: -Hard to build-Politically charged-Hard to change- Expensive-“Schema Heavy”

Pros: -Quick to build- Politically uncharged- Easy to change- Low cost

Cons: -Alignment-Consistency--“Schema Light”

DW Architecture

Non-volatile data

Analytics Architecture

Volatile data

Reporting & Monitoring (Casual Users)

Predefined metrics

Corporate Objectives and StrategyTOP DOWN- “Business Intelligence”

Processes and Projects

Analysis and Prediction (Power Users)

Ad hoc queries And data

BOTTOM UP – “Analytics Intelligence”

Pros: -Alignment-Consistency

Cons: -Hard to build-Politically charged-Hard to change- Expensive-“Schema Heavy”

Pros: -Quick to build- Politically uncharged- Easy to change- Low cost

Cons: -Alignment-Consistency--“Schema Light”

Self-Service BISuper Users

DW Architecture

Non-volatile data

Analytics Architecture

Volatile data

Reporting & Monitoring (Casual Users)

Predefined metrics

Corporate Objectives and StrategyTOP DOWN- “Business Intelligence”

Processes and Projects

Analysis and Prediction (Power Users)

Ad hoc queries And data

BOTTOM UP – “Analytics Intelligence”

Pros: -Alignment-Consistency

Cons: -Hard to build-Politically charged-Hard to change- Expensive-“Schema Heavy”

Pros: -Quick to build- Politically uncharged- Easy to change- Low cost

Cons: -Alignment-Consistency--“Schema Light”

Semantic Layer/Mashboards

Visual Analysis/Direct Connect Dashboards

DW Architecture

Non-volatile data

Analytics Architecture

Volatile data

Three TypesOperational Tactical Strategic

Purpose Control operations Optimize processes Manage strategy

Scope Operational Departmental Enterprise

Users Staff+ Managers+ Executives+

Primary activity Act Analyze Review

Focus Current Past Future

Data Refresh Intraday/Daily Daily/Weekly Monthly/Quarterly

Primary Source Core systems Data warehouse Data mart/Excel

KPIs Drivers Outcomes/Drivers Outcomes

Existing? 100% 75% 50%

Looks Like? Dashboard Portal Scorecard

Mapping Users to Dashboards

Strategic Dashboard

Tactical Dashboard

Operational Dashboard

Executives

Managers/Analysts

Operations Staff

59%

80%

64%

29%38%

20%12%

Operational Tactical Strategic All equally

In use

Most widely used

Dashboard Usage by Type

Based on 685 respondents, 2009

(Deployed)

37% 33%

8%

33%29%

24%

0%

10%

20%

30%

40%

50%

60%

70%

80%

Operational Tactical Strategic

High

Very high

To what degree has the dashboard had a positive impact on the business?

Based on 685 respondents, 2009

Metrics and Users

Operational Tactical Strategic# of top-level metrics 11 12 14

Total # of metrics 141 110 183

Total # of users 230 236 180