JDE Data Warehousing and BI/Reporting with Microsoft PowerPivot at Clif Bar & Company Session ID#:

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1 JDE Data Warehousing and BI/Reporting with Microsoft PowerPivot at Clif Bar & Company Session ID#: Our journey to replace our Data Warehouse and Business Intelligence platform Prepared by: Dave Hartwell Director, Business Applications Clif Bar & Company & Adam Crigger President Preferred Strategies REMINDER Check in on the COLLABORATE mobile app

2 Presentation Route About Clif Bar & Company About Preferred Strategies Our Business Intelligence History & Context Our Challenges and High Level Objectives Key Decisions Project Planning Why Microsoft? Why Preferred Strategies? Data Warehouse Solution Overview Keys to Success Demonstration Questions?

3 About Clif Bar & Company Who We Are and What We Do Clif Bar & Company is the leading brand in all-natural and organic energy and nutrition foods and drinks

4 About Clif Bar & Company The Clif Bar Journey Founded in 1992 Family and Employee Owned Prefer the White Road to the Red Road Red Roads Larger, straighter, more typical White Roads Smaller, Exploratory, Interesting

5 About Clif Bar & Company 5 Aspirations Business Model Business Brands People Community Planet

6 About Preferred Strategies Introduction & Context Who is Preferred Strategies? Oracle Partner Provide 3 rd Party BI and Data Warehouse Applications for Oracle s JDE World & EnterpriseOne What is BI Quick Launch? Jumpstart BI Reporting and Analytics Platforms Offered for JDE BI Options Oracle BI and BI Publisher Business Objects BI and Crystal Reports Microsoft BI and PowerPivot Direct Connect Enterprise Data Warehouse

7 Clif Bar & Company ERP and BI History and Context ERP Implemented World A7.3 in 1998 Migrated to EnterpriseOne 9.0 in 2011 Data Warehouse and Business Intelligence Implemented Corporate Radar and SQL Server DW in 2002

8 Clif Bar & Company 2012 Clif Bar BI Scenario Business Intelligence Tools Corporate Radar BI Reporting IT supported Numerous business data silos mostly independent from IT Data Warehouse Non-Traditional data repository Primary Subject Areas Offered GL Budget to Actual Sales Analysis Trade Spending

9 BI and Data Warehouse Challenges

10 Challenges & High Level Objectives Challenges Software introduced in 2002, sunset after acquisitions With rapid growth, business cobbling solutions Numerous data silos in business areas Different reports producing different information Some dimensions and measures missing in existing subject areaas Additional subject areas missing altogether Objectives Solution for the long term Better, Faster Decision Making Self Service BI Single Source of Truth Common Data Definitions, Standard Master Data, Conformed Dimensions Increased Availability of Historical Data

11 Key Decision Build or Buy Develop everything from the ground Up Buy an established template for E1 data connection Decision: We preferred to go with a pre-built starter DW & BI solution with an established Oracle partner with JDE E1 experience

12 Key Decision Direct Connect to JDE E1 or Traditional Enterprise Data Warehouse Different tools and approaches for data sources across the company Common Framework with Foundation & Options for Future Expansion Decision: Given overall needs, we preferred an Enterprise Data Warehouse E1 primary, but not only data source Long Term vision for BI and DW

13 Project Planning High Level Data Warehouse & BI Approach 13

14 Project Planning Key Considerations Limited budget for full evaluation/selection/strategy development Think Big, Start Small: Build the foundation first with long term vision in mind Capability to deliver and support IT is and will likely be a lean team BI doesn t start with the reporting tool, but building the Data Warehouse To do this properly, it will take time, effort, and money

15 BI & Data Warehouse Iceberg Analogy

16 The Road to overhaul our BI and DW End of 2012, initial budget and proposed plan for 2013 Formal BI & DW Strategic Analysis and Plan Solution Evaluation technologies and JDE partners Software Acquisition Plan Implementation and Initiate build out What actually happened in 2013! Proposed budget cut in half Reduced Evaluation to Microsoft Validation Reviewed and found DW/BI Partner Planned and implemented initial subject areas Came in under revised, reduced budget!

17 Data Warehouse & BI Timeline Past Accomplishments Q Q Q Q Q & Beyond BI / DW Project Approval and Kick Off Core Technology Platform Standardization DW Vendor Evaluations JDE Solutions DW Vendor Evaluation Preferred Strategies Build or Buy Decision for E1 BI solution Short / Mid Term Plan DW Implementation Planning Master Data Cleansing and Planning Phase 1 : E1 GL Phase 2 : E1 Inventory, Sales, Procurement Phase 3 :E1 Other Subject Areas Phase 4: Other Data Sources Past / Future Outcomes BI/DW Project Approved Microsoft Chosen Platform No Go on other JDE Solutions PS Chosen DW Vendor MD Cleansed, DW Planned DW Implemented with GL DW Implemented with Phase 2 SAs DW Phase 3 E1 SAs DW Phase 4 Other Data Sources

18 Why Microsoft Technologies? Tools Microsoft Excel is the most widely adopted analytic and reporting tool in the world There is no escaping it, so EMBRACE it! Microsoft has invested significantly in DW and BI as strategic focus and will continue to do so In 2013, Gartner placed Microsoft BI in the desired quadrant Capability to provide personal, department, and enterprise solutions Capability to model/test Enterprise solutions in PowerPivot

19 Why Microsoft Technologies? Tools Source Systems DB: MS SQL Server Data Warehouse DB: MS SQL Server 2012 Change Data Capture E1 Source: MS SQL Server 2008 R2 (CDC) Extract, Transform, Load: MS SQL Server ETL (SSIS) Reporting Solutions: Highly structured reports: MS Reporting Services (SSRS) Multi-Dimensional/Analytics: MS PowerPivot (Excel) Portal, Delivery: MS SharePoint Visualization (Charts, Graphs, KPI Dashboards): MS PowerView MS PerformancePoint And various other Power and P s Cubes (SSAS)

20 Why Microsoft Technologies? Clif Bar Considerations Same tools to run directly against E1 if desired, using DB Views, Excel, etc. Clif Bar people already know and use Excel and SharePoint extensively minimized learning curve Clif Bar IT already know SQL Server, Excel, SharePoint Clif IT already standardized on Microsoft stack Server and End User operating systems, Office, Outlook, SQL Server Database, SharePoint, Office, etc. Cost of Entry and ongoing licensing and support significantly lower than other DW and BI solutions

21 Why Preferred Strategies? Proven depth of experience JDE World and E1 Data Warehouse Business Intelligence requirements Microsoft technologies from DB to ETL to PowerPivot The right team and approach for Clif Bar Agile Collaborative Pragmatic Partners Guiding Awesome people! Aligned with Clif Bar s 5 Aspirations

22 Data Warehouse Solution Overview Facts Dimensions Result: Near Real Time data in Data Warehouse for Analytics & Operational Data Store (ODS) 22

23 Keys to Success Implementation A Great Ride Results from Good Preparation Embracing the effort Unexpected highlights Few mechanical breakdowns Efficient maintenance

24 Keys to Success Project Management & Partnership Define Clear requirements Understand YOUR needs and realistic challenges Conduct detailed Proof of Concept Define clear internal roles from Business & IT Develop Customer/Supplier relationship PARTNERSHIP Supplier knowledge of ERP (JDE), Data Warehouse, and BI Supplier Project Management On Time On Budget Scope & Change Management

25 Clif Bar & Company BI Analytics Demo

26 More About Preferred Strategies

27 Goals of the Business Intelligence SIG

28 Data Warehouse ETL & PowerPivot Models for JD Edwards General Accounting Accounts Receivable Accounts Payable Data Warehouse ETL PowerPivot Models Data Warehouse ETL PowerPivot Models Data Warehouse ETL PowerPivot Models Sales Order Inventory Procurement Data Warehouse ETL PowerPivot Models Data Warehouse ETL PowerPivot Models Data Warehouse ETL PowerPivot Models Enterprise Asset Mgmt Job Cost Contract Billing Data Warehouse ETL PowerPivot Models Data Warehouse ETL PowerPivot Models Data Warehouse ETL PowerPivot Models In Dev Human Resources / Payroll Manufacturing Property Management Data Warehouse ETL PowerPivot Models In Dev Data Warehouse ETL PowerPivot Models In Dev Data Warehouse ETL PowerPivot Models In Dev

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