How to Collaboratively Manage Excel-Based Process Data in SQL Server Your organization probably uses Excel for a variety of business processes including budgeting, sales revenue forecasting, product demand planning, and project management. You'll learn how to set up and manage multi-user collaborative processes using Excel as the data form and SQL Server as the data store and process engine. You'll learn: * How to enable cell-level collaboration between multiple users using Excel and SQL Server. * How to effectively integrate desktop Excel-based process data with enterprise applications. * How to mitigate the limitations normally associated with Excel-to-database connections including record locking (check-in/out), conflict management, and change management and versioning.

1. How To Collaboratively Manage Excel‐
How To Collaboratively M
H T C ll b ti l Manage Excel‐ E l
Based Process Data in SQL Server
Speaker: JB Kuppe
Boardwalktech
Silicon Valley SQL Server User Group
June 2011
Mark Ginnebaugh, User Group Leader,
mark@designmind.com

2. JB Kuppe
Jb.kuppe@boardwalktech.com
Collaboratively Manage Excel‐Based
ll b i l l d
Process Data in SQL Server
Enabling companies to build and maintain competitive advantage through
business process innovation in the collaborative planning space

3.  Founded in 2004 ‐ HQ in Palo Alto, CA
 Origins in MCAD PDM
 Patented Positional Database Technology
Patented “Positional” Database Technology
 Product: The Boardwalk Collaboration Platform (BCP)
 Application Focus: Collaborative Planning Processes

4. The Elephant in the Room
p
Enterprise Reality
IT Perception
IT Perception
Desktop Applications
Business GAP
Intelligence
Data Warehouse
OLAP Reporting
Specialty /Edge Business Intelligence
Applications
Financials
CRM SCM
Edge Apps
Core ERP
Core ERP
“80% of the work”

5. X Denormalized Tables Business Intelligence
Business Focus
Information Reporting Cubes $$$
collection
Can’t contribute to Iteration A: Cleansing and
the Denormalized View schema design
Mapping and Transformation
EAI , BI $$$ Iteration B: Cleansing and
schema changes
Technology Focus
$$ Expensive Iterations
Normalized
Normalized Normalized
Normalized
Table Table

6. select cust.companyname, cust.contactname, orddet.quantity, ord.orderdate,
prod.productname from customers cust inner join orders ord on cust.customerid =
ord.customerid inner join [order details] orddet on ord.orderid = orddet.orderid inner
j p
join products prod on orddet.productid = prod.productid where prod.productname =
p p p p p p
Backward looking
versus forward
looking..

7. Export to
Excel
Email to
Change everyone
history
Maintain data
connection ‐ data
location changes
location changes
Merge in Create multiple views Create dependent
other data for different users data calculation

8. Create
 Define schema (create from Excel)
 Create a database schema, define entity relationship
Create a database schema, define entity relationship
Manage
 Create UI in Excel to match database schema
 Create a J2EE or .Net data update layer
 Program ability to create new record from Excel
 Program access control and consolidation rules into every sheet
connected to RDBMS
 Versioning for all schemas has to be programmed
Versioning for all schemas has to be programmed
 Change management has to be programmed
 Formula support needs to be programmed
 Check‐out/in mechanism used to work on data
 Only “latest” change wins
Report
 For every report, run a SQL query to filter the data, paste it in Excel,
t i t il t
create pivots, email reports
 Do process again if data changes/version “old” reports

9. OLAP

10. Rows of Data
• Product
Columns of Data
• Customer
• Time
• User
• Business variable
How to Collaborate?
How to Collaborate?
Excel is a business process platform
Emailing does not work
• Position of data drives business logic Excel “Connectors” do not work
• Complex relationships (formulas)
• No change management • Rigid model pushed to spreadsheet
• Flexibility
• Versioning nightmaremanagement UI (colors
Versioning nightmare
• Powerful data management UI (colors,
Powerful data • No persistence
No persistence
• conditional format, picklists)
No central version • No change/audit
• Offline environment/mature data RDBMS
• No access control • No access control
• “Save‐as” local versioning=scenarios
• Data consistency • No positional integrity

11. Change values and formulas
V2 (R/C,U,T,Net Change)
V1 (R/C,U,T)

12. • Patent awarded 2008
“Positional” Data Structure
‒ Positional cell data management
Versions (R/C Position, Structure, Net Change, User, Time) ‒ Range vs record transaction control
Columns ‒ Single flexible schema
• Excel range creates/drives shareable
database model
database model
User Access 1
Data
Row User Access 2 Data
Range2
• Scalable multi‐user collaboration
User Access 3 Range1
‒ Work “off‐line,” no check‐in/out
‒ Dynamic access control
y
‒ “Submit/Refresh” sharing
Business Column
Logic ‒ Centrally manage collaborative data
‒ Net‐change versions vs. overwrite
‒ Cell‐level change tracking
Other App/DB
• Integration with any App/DB
• Application flexibility
‒ One platform, many solutions
l f l

13.  Addressability to Business Objects (Table, Row, Column)
 Data Ordering (Row, Column)
 Referential Integrity limits growth
Referential Integrity limits growth
 No Locking – High Concurrency
 No Data Overwrite ‐ Versioning
 Persistent Transactions
Persistent Transactions
 WYSWYG Data Update

14. Sharing data &
formulas
Manager Rep
Refresh Submit
Firewall
Other ERP…

15. Form Interface Model Tabular User Interface Model and Business Logic
Communication Technology Communication Technology Communication Technology Communication Technology
Centralized Business Model and Logic Positional Data Management
Relational Relational Relational Relational
Rigid Data Models Abstract Tabular Data Model
Persistence w/o history Persistence w/o history Persistence with history Persistence with history
1. Business person defines requirements 1. Business person expresses requirements in a
2. Each technology layer looses information Tabular model
3. Each layer introduces rigidity 2. The Model is translated WYSIWYG to the tabular
4. y
Each layer adds cost database so no loss of information
5. Each layer adds latency to change 3. Changes in the Model at UI layer directly drive the
flexible tabular database
6. Every one confirms to centralized model and logic
4. Cost of change is zero
7. Business Person at the top has no control over the
Data Models 5. There is no latency to change
6. Business Logic is embedded in the UI and doesn’t
require conformance by all parties
7. Business person is in full control over the data
model and is fully empowered

16. The Cuboid Powered Enterprise
p
Enterprise
Collaboration

17. • General forecasting • Tax platform
o Periodic shift
Periodic shift o Multi entity tax environment (corporate, partnership)
Multi‐entity tax environment (corporate, partnership)
o Aggregation/disaggregation o SME template authoring, management, and
o Re‐alignment propagation
o Exceptions o Tax formula library
o Notifications
N tifi ti o Tax business rules library
Tax business rules library
o Scenario planning o Dynamic taxonomy management
• New product introductions o Rollover services
o Tax item allocation and consolidation
o Product attribute
o Project tax data consolidation
o Phase in/out
o Document management integration
o Plan‐o‐gram driven forecasting
o External data query/integration
o Product master management
• EDI collaboration
EDI collaboration
o Outsourced retail supply planning
o Supplier collaboration
Page 17

18. BCP Powered Enterprise Solutions
p
Demand Planning/Supply Planning
Sales manager adjustments can be done
at the customer/SKU level or at the
aggregate region/territory l
t i /t it level
l
Spreadsheet-based measures &
calculations
Measures & applicable SKUs from
planning SOR
Cell-level, two-way
collaboration
Access control

20. To learn more or inquire about speaking opportunities, please contact:
Mark Ginnebaugh, User Group Leader
Mark Ginnebaugh User Group Leader
mark@designmind.com