Microsoft SQL Server - How to Collaboratively Manage Excel Data
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The document discusses the challenges and solutions for collaboratively managing Excel-based data processes in SQL Server, emphasizing the need for innovative business process management. It highlights the Boardwalk Collaboration Platform (BCP) as a tool for effective data management and collaboration, addressing issues like data versioning, access control, and flexible modeling. The presentation urges organizations to focus on enhancing collaborative planning and integration with existing applications for improved efficiency and competitiveness.
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Microsoft SQL Server - How to Collaboratively Manage Excel Data
- 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, [email protected]
- 2. JB Kuppe [email protected] 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 [email protected]