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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.
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H T C ll b ti lH T C ll b ti l M E lM E lHow To Collaboratively How To Collaboratively Manage ExcelManage Excel‐‐Based Process Data in SQL ServerBased Process Data in SQL Server
Speaker: JB KuppeBoardwalktech
Silicon Valley SQL Server User GroupJune 2011
Mark Ginnebaugh, User Group Leader, [email protected]
ll b i l l dCollaboratively Manage Excel‐Based Process Data in SQL Server
Enabling companies to build and maintain competitive advantage through business process innovation in the collaborative planning space
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
The Elephant in the Roomp
IT Perception
Enterprise Reality
Desktop ApplicationsDesktop Applications
GAPBusiness Intelligence
IT Perception
Business Intelligence
Intelligence
Specialty /Edge Applications
OLAP ReportingData Warehouse
Edge Apps
CRM SCMFinancials
Core ERP
Core ERP
“80% of the work”
Denormalized TablesX Business Intelligence
Information collection
Reporting Cubes $$$Business Focus
Mapping and Transformation
Iteration A: Cleansing and schema design
collection
Can’t contribute to the Denormalized View
EAI , BI $$$ Iteration B: Cleansing and schema changes
Technology Focus
Normalized Normalized
$$ Expensive Iterations
Normalized Table
Normalized Table
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 join products prod on orddet.productid = prod.productid where prod.productname =j p p p p p p p
Backward looking versus forward looking..
Export to Excel
Change history
Email to everyone
Maintain data connection ‐ data location changes
Create dependent data calculation
Create multiple views for different users
location changes
Merge in other data
Create
Define schema (create from Excel)
Create a database schema, define entity relationshipCreate 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 tcreate pivots, email reports
Do process again if data changes/version “old” reports
OLAP
Columns of Data• Time
Rows of Data• Product• Customer• User
• Business variableUser
How to Collaborate?How to Collaborate?
Excel “Connectors” do not work• Rigid model pushed to spreadsheet
• No persistence
Excel is a business process platform• Position of data drives business logic• Complex relationships (formulas)• Flexibility• Powerful data management UI (colors
Emailing does not work• No change management
• Versioning nightmare No persistence
• No change/audit
• No access control
• No positional integrity
RDBMS
• Powerful data management UI (colors, conditional format, picklists)
• Offline environment/mature data• “Save‐as” local versioning=scenarios
Versioning nightmare
• No central version
• No access control
• Data consistency
Change values and formulas
V2 (R/C,U,T,Net Change)
V1 (R/C,U,T)
• Patent awarded 2008
‒ Positional cell data management“Positional” Data Structure
‒ Range vs record transaction control
‒ Single flexible schema
• Excel range creates/drives shareable database model
Columns
Versions (R/C Position, Structure, Net Change, User, Time)
database model
• Scalable multi‐user collaboration
‒ Work “off‐line,” no check‐in/out
‒ Dynamic access control
DataRange2
User Access 1
User Access 3
DataRange1
User Access 2Row
y
‒ “Submit/Refresh” sharing
‒ Centrally manage collaborative data
‒ Net‐change versions vs. overwrite
ColumnBusiness Logic
‒ Cell‐level change tracking
• Integration with any App/DB
• Application flexibility
l f l
Other App/DB
‒ One platform, many solutions
Addressability to Business Objects (Table, Row, Column)
Data Ordering (Row, Column)
Referential Integrity limits growthReferential Integrity limits growth
No Locking – High Concurrency
No Data Overwrite ‐ Versioning
Persistent Transactions Persistent Transactions
WYSWYG Data Update
Manager Rep
Sharing data & formulas
Refresh Submit
Firewall
Other ERP…
Form Interface Model
Communication Technology Communication Technology
Tabular User Interface Model and Business Logic
Communication Technology Communication Technology
Centralized Business Model and Logic
Relational Relational
Positional Data Management
Relational Relational
Rigid Data Models
Persistence w/o history Persistence w/o history
Abstract Tabular Data Model
Persistence with history Persistence with history
1. Business person defines requirements
2. Each technology layer looses information
3. Each layer introduces rigidity
4. Each layer adds cost
1. Business person expresses requirements in a Tabular model
2. The Model is translated WYSIWYG to the tabular database so no loss of informationy
5. Each layer adds latency to change
6. Every one confirms to centralized model and logic
7. Business Person at the top has no control over the Data Models
3. Changes in the Model at UI layer directly drive the flexible tabular database
4. Cost of change is zero
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
The Cuboid Powered Enterprise p
EnterpriseCollaboration
• Tax platformo Multi‐entity tax environment (corporate, partnership)
• General forecastingo Periodic shift o Multi entity tax environment (corporate, partnership)
o SME template authoring, management, and propagation
o Tax formula library
o Tax business rules library
o Periodic shift
o Aggregation/disaggregation
o Re‐alignment
o Exceptions
N tifi ti o Tax business rules library
o Dynamic taxonomy management
o Rollover services
o Tax item allocation and consolidation
o Notifications
o Scenario planning
• New product introductionso Product attribute
o Project tax data consolidation
o Document management integration
o External data query/integration
o Phase in/out
o Plan‐o‐gram driven forecasting
o Product master management
• EDI collaboration• EDI collaborationo Outsourced retail supply planning
o Supplier collaboration
Page 17
BCP Powered Enterprise SolutionspDemand Planning/Supply Planning
Sales manager adjustments can be done at the customer/SKU level or at the
t i /t it l laggregate region/territory level
Spreadsheet-based measures & calculations
Cell-level, two-way collaboration
Measures & applicable SKUs from planning SOR
Access control
collaboration
To learn more or inquire about speaking opportunities, please contact:
Mark Ginnebaugh User Group LeaderMark Ginnebaugh, User Group [email protected]