Finance Data Mart Data Training January, 2003

Contents Introduction and Training Objectives Brio Products Overview Brio Portal and Brio Insight Overview Brio Portal Username and Password Database Username and Password Information Sharing Data Access Security Summary Security Details Executive Dashboard Overview Published BQYs Data Star Schemas Meta Topics – Simplified Data Access OLM Fact Definitions and Usage Brio Essentials Data Warehouse Team Contacts

Training Objectives The goal of the session is to provide attendees with a basic understanding of data within the Finance Data Mart. Upon completion of the training, attendees should be able to perform the following tasks: Download the Brio Insight plug-in Retrieve and analyze data from published BQYs Create their own queries from Brio meta topics and star schemas

Brio Products Overview Brio Desktop User (i.e., Brio Explorer, or Designer) Data Warehouse Connects to the DW without Portal Brio Portal Finance Data Mart Position Control Data Mart Portal and Insight are also available to Desktop users via the Web Brio Insight User Other Data Marts Brio Insight Web Folders, Published Documents, Personalized Content, Dashboards Connects to the DW with Insight and Portal via the Web Each user will have separate Portal and database usernames and passwords. The Portal login provides the user with access to published content based on a security profile. The database login is necessary to extract data from the Data Warehouse.

Brio Portal and Brio Insight Overview Allows users to access published documents (e.g., BQYs, Brio manuals, training documents) and personalize their content Brio Insight: Web-based query, analysis, and reporting tool available via Brio Portal Brio Insight is a browser plug-in that allows users to extract, analyze, and report on data from the Data Warehouse

Brio Portal and Brio Insight Overview Getting started with Portal and Insight: The link below brings you to a document that provides detailed instructions for accessing Brio Portal and downloading Brio Insight http://www.rpi.edu/datawarehouse/docs/Brio-Portal-and-Insight-Getting-Started.doc

Brio Portal Username and Password The Data Warehouse team will provide you with a Portal username and password Change your Portal password after your initial login: The link below brings you to a document that provides detailed instructions for changing your Portal password: http://www.rpi.edu/datawarehouse/docs/Changing-Portal-Password.doc

Database Username and Password The Data Warehouse team will provide you with a database username and password Change your database password after your initial login: The link below brings you to a document that provides detailed instructions for changing your database password: http://www.rpi.edu/datawarehouse/docs/Changing-Database-Password.doc

Information Sharing Insight User Insight User Explorer, Designer User A BQY document created and saved with Insight is compatible with Explorer and Designer Explorer, Designer User Explorer, Designer User A BQY document created and saved with Explorer or Designer is not compatible with Insight. To share with Insight users, desktop users should export results to Excel or use Insight to create a BQY document that can be shared. BQY documents can be emailed or placed in a shared directory. A BQY document that is frequently used by multiple users may also be published to the Portal. Contact the DW team for publishing guidelines.

Data Access - Overview High Cabinet, Deans, Department Chairs, Center Directors Department Financial Managers Finance Administration, Portfolio Financial Managers High

Data Access - Security Summary Portal security via user id and password Brio documents secured based on user role and profile Data secured based on user role and profile

Data Access – Security Details Data Base security applies to all individuals given either direct access to the warehoused data or given permissions to process Brio dynamic reports Financial Managers and the Management of Organizations will have access to the warehoused Financial data based on the following criteria: All financials posted against that Organization All funds listing that Organization as a home Organization All funds listing the PI (or the Financial Manager) associated with that Org as Fund Financial Manager. (This resolves the Multi-disciplinary issue) All funds and orgs listing that Org as a predecessor in either one of the above three cases. Administrative role: Individuals may be granted access to additional funds and orgs based on their needs and their role within Rensselaer.

Executive Dashboard Overview Accessed via the Portal High-level, graphical views of Portfolio-specific data Designed primarily for executive use, though available to other users as well Currently, there are two dashboards: Financial Analysis Research and Grants Comprised of monthly summary data, refreshed periodically

Executive Dashboard Overview At the portfolio level, we pre-populate the dashboards with data At the Department level, users must process to see data: To process each dashboard, it is currently necessary to login (with a database password) more than once. This is because there is more than one query in each dashboard.

Published BQYs There are several pre-built Brio Insight documents (i.e., BQYs) available on the Portal for Finance Data Mart users. To find them, click on the Browse tab in the Portal and navigate to the Finance Data Mart folder within the Data Warehouse folder. Click on a document to open it and Insight starts automatically.

Published BQYs Published Insight BQYs were developed by members of Finance and the DW team. They reflect our estimation of what users want to see. Publishing BQYs is an ongoing process. As the rollout progresses, publishing will be more user-driven.

Published BQYs Subscribe Document Title Description SmartCut Date Published Brio Document Access Privilege

Published BQYs Brio Document Privileges Data Model and Query The highest privilege level with abilities to see the table catalog, build queries, process, and analyze (i.e., drill) Query and Analyze Able to query (i.e., add new fields), process, and drill Analyze and Process Has the ability to process and drill Analyze Able to drill into existing data, but not process View and Process Has the ability to process (i.e., refresh) static data View The basic privilege level with static views only

Published BQYs Brio Document Section Naming Standards: EIS: Executive Information System Q: Query R: Results P: Pivot Table C: Chart RPT: Report

Data: Star Schemas In the Data Warehouse, data is organized in Star Schemas Star Schemas are: Intuitive for developers and end-users Designed for analysis and efficient performance

Data: Star Schemas Definition: A Star Schema is comprised of one Fact table joined to one or more Dimension tables through Key fields

Data: Star Schemas A Star Schema is comprised of one Fact table joined to one or more Dimension tables through Key fields Join: A link between a fact table and a dimension table. Key: A numeric field that identifies rows in fact and dimension tables. Dimension Table: A table that describes the facts (e.g., expenditures by fund, account, etc.). Fact Table: The central table in a Star Schema. It contains numeric performance measurements, i.e., facts. For example, revenue, expenditure, and encumbrance amounts are facts.

Data: Star Schemas The Finance Data Mart contains 5 Star Schemas GLM: General Ledger Monthly summary OLM: Operational Ledger Monthly summary OLT: Operating Ledger Transactions detail – Actuals Operating Ledger Transactions detail – Budgets Operating Ledger Transactions detail – Commitments Extensive information about the Data Warehouse and Star Schemas is available at: http://www.rpi.edu/datawarehouse/

Finance Data Mart Tables Data: Star Schemas Finance Data Mart Tables Each table name includes a three-character acronym (GLM, OLM, OLT) that describes which Star Schema it belongs to. In addition, table names include the words FACT or DIM (dimension) to indicate what kind of table it is. GLM: General Ledger Monthly summary OLM: Operational Ledger Monthly summary OLT: Operational Ledger Transaction details

Data: Star Schemas - Big Picture Finance Data Mart Tables Data mart tables are the building blocks of Star Schemas. A Data Mart contains data tables from a single business process, e.g., Finance. A Data Warehouse is a centralized repository where operational data is arranged for query, analysis, and ease-of-use. A Data Warehouse is comprised of one or more Data Marts

Data: Meta Topics Meta Topic A Meta Topic is a simplified display of a Star Schema. Star Schema Fact and Dimension tables are rolled into one table where the fields are separated by category headings. Generally, a Meta Topic will contain a subset of the important items for analysis.

Data: OLM Fact Definitions and Usage Schema / Meta Topic Fact Definition Usage OLM Annual Budget Amount Annual budget amounts submitted to the Budget office as the full funds budget for the fiscal year. In the case of all research, endowment income, gift and designated funds, the amount expected to be spent within the fiscal year. Comparison by fiscal years; comparison against expenditures and commitments Project YTD Revenue Budget Amount Primarily used by finance administration to hold the anticipated revenue budget for the fund. Not used by campus, only finance administration. Project YTD Budget Amount Represents the prior year ending balance plus any current YTD budget changes. Budget vs. Expenditures by fund for a fiscal year. Project ITD Revenue Budget Amount Primarily used by finance administration to hold the cumulative revenue budget for the fund.

Data: OLM Fact Definitions and Usage Schema / Meta Topic Fact Definition Usage OLM Project ITD Budget Amount Represents cumulative expense budget over the life of a project. Budget vs. Expenditures by fund over the life of the fund. Do NOT use for unrestricted funds Revenue Recognized income prior to deductions. Comparative analysis Expenditure Amount A payment, or the promise of a future payment Transfer Amount Amount moved between funds Transfers function similar to expenditures Encumbrance Amount Represents requisition amounts that have been turned into purchase orders, and any other actual and/or anticipated commitments of funds (e.g., tuition encumbrance against research funds) Commitment Amount Represents the sum of Reservation & Encumbrance Amounts.

Data: OLM Fact Definitions and Usage Schema / Meta Topic Fact Definition Usage OLM ITD Reservation Amount Represents amounts reserved to be spent (i.e. purchase requisitions) over the life of the fund Comparative analysis ITD Encumbrance Amount Represents requisition amounts that have been turned into purchase orders and any other actual and anticipated commitments of funds (e.g. tuition encumbrance against research funds) over the life of the fund. ITD Commitment Amount Represents the sum of Reservation & Encumbrance Amounts over the life of the fund.

Data: Brio Essentials Data Functions on Numeric Facts: You must either use a data function like Sum, OR change the data type to Real. The default data type is Automatic, however, there is a Brio bug that causes nulls to be returned instead of valid data. Right-click on a request line item to add a data function Use the Item Properties to change the data type

DW Team: Contact Information Data Warehouse team contacts: Keith Cushing (Brio training, data analysis) Phone: 518-276-4038 Email: cushik@rpi.edu Christa Wilary (Brio installations, user setup) Phone: 518-276-2117 Email: wilarc@rpi.edu http://www.rpi.edu/datawarehouse/dw-team.html User Community Brio-users-l@lists.rpi.edu Help, Issues, Changes, etc… Iacs-dw-sup-l@lists.rpi.edu