OBIEE Training Part III Bringing it all Together
OBIEE Training Part III Bringing it all Together Ronda Stemach EDM Group February 5, 2013
Where we’ve Come • Data Warehouse and Hyperion started in 2008 • Data Warehouse and OBIEE completed in 2010 for Finance and HR
Where we’re Going • Introduction of Student Data in Data Warehouse
What do we get with EPM 9. 1? 1 • Fact: Number of units a Student has taken ETL - The process that Extracts data from our Dimensions: People. Soft tables, Transforms data, and Loads Who? Person (and related bio-demo data) data into the Facts and Dimensions of our Data When? Academic Term, Year Warehouse. Where? Class, Department, College hierarchy 2 • Name Translations: Repository – the method used to look at the Fact • and Dimension Tables, apply business logic to Stu_Car_Term table = Term Enrollment them, and organize them for Presentation to the Application of Business Rules & Logic user. Data Organization & Presentation to OBIEE Author 3 • Catalog – the collection of Delivered Reports, Reports and Dashboards delivered with EPM filters, prompts and dashboards created using Reports and Dashboards created by the Authors OBIEE. 4
Subject Groupings and Areas Data Mart Subject Area Admissions and Recruiting Admission Application Status Admission Funnel Application Evaluation External Academic Summary Student Financial Services Award Disbursement Award Snapshot Bill Summary Credit History Payment and Charges Cross Reference Payment Summary Student Financials Accounting Line Student Financials Payment Details Student Financials Transactions Details
Subject Groupings and Areas Data Mart Subject Area Student Records Academic Plan Summary Academic Program Detail Class Enrollment Class Instructor Class / Class Meeting Pattern Enrollment Requests Institution Summary Student Degrees Term Enrollment Institutional Research (Snapshots) Enrollment Admissions Completions (Graduation) End of Term
Census Data
Why OBIEE? Business intelligence (BI) is defined as the ability for an Knowledge organization to take its and convert it into Data • OBI is a Reporting Tool • OBI is the “Front End” view of the Data Warehouse • OBI is about making the mind of your institution’s business talk to you LIVE • Kimball Star Schema Design • Analyze wide range of Information
Think about how you Consume Data When you want a weather report, do you go here:
Think about how you Consume Data … OR Here: • Summary to Detail • Multiple layers of info • Layout of Information
HSU Best Practices in OBI Design Dashboards and Prompts • Prompt Section should appear at the top of the Dashboard • For multi-page dashboards, be aware of the scope of your prompt • The number of pages per dashboard should not exceed the horizontal width of your screen – avoid having to scroll to pages • Don’t overuse the constrain option in prompts – it can really slow down performance • Check “Print Rows” setting of Dashboard, in PDF & Print Properties – All versus Visible • Consider web page eye movement and the level of priority of the elements of your dashboard.
HSU Best Practices in OBI Design Analyses • • • Always display your filters at the bottom Limit your columns, if possible, to avoid horizontal scrolling Use consistent color coding when possible Use consistent export links Provide insight, not just Excel – create interactive ways to view the data. Create links, drill to-s, different views, pivots… • Provide context – comparison to previous year, comparison to budget, highs and lows, comparison to others. • Make use of the Run Date/Time feature in your Title • Add a Subtitle to further explain the report
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