Data Warehouse Scope Recommendations

Transcription

1 Rensselaer Data Warehuse Prject Financial Analysis Scpe and Data Audits This dcument describes the scpe f the Financial Analysis data mart scheduled fr delivery in July 2002 and the data auditing issues affecting this scpe. Data Warehuse Scpe Recmmendatins On Octber 18, 2001 the Data Warehuse Spnsrship Cmmittee adpted a phased implementatin apprach that builds upn and integrates with previus phases in implementing the Rensselaer Data Warehuse architecture. Using this apprach, the data warehuse will be develped in an evlutinary, ne-step-at-a-time fashin, starting with a well-defined and cmmnly agreed t set f requirements, and expanded it ver time. Identifying scpe is critical t defining the subject areas that will be addressed within each phase. During the detailed requirements gathering prcess fr the financial analysis subject area, additinal key requirements were identified that althugh are utside the parameters f the July 2002 deliverables have t be nted and addressed: the need fr psitin cntrl and labr data and research-related activity data. Althugh Research was identified as a separate subject area scheduled fr develpment later n, the academic schls fcus a great deal f their financial analysis n research related activity. Enabling the academic schls t clearly identify research related budgets and expenditures in the first phase wuld greatly enhance the value f financial infrmatin delivered in July Business representatives cmmnly discussed reprting and analyzing labr budget and actual data as a pririty. In additin t reprting by fund, rganizatin, accunt, prgram, activity and lcatin (FOAPAL), labr budget and actual data is analyzed by psitin, jb and persn. Prviding a ttal picture fr planning will require linking t Human Resurces data t acquire psitin cntrl data t help prtfli mangers understand the budget impact f cmmitted new hires. Delivered in July 2002, Financial Analysis data mart implementatin will fcus n analysis f budget and expenditure activity assciated with the fund, rganizatin, accunt, prgram, activity and lcatin (FOAPAL) structures. In the fllwing phases, the data warehuse shuld address the need t integrate psitin cntrl data alng with research infrmatin characterized by cntracts and Grants and Spnsr Agencies. The fllwing describes the primary characteristics f phases I III f the data warehuse: Phase I Financial Analysis (January 2002 June 2002) The financial data frm the peratinal ledger will include budget, expenditure, encumbrance and reservatin, while the general ledger data will include debits and credits. Key reprting attributes will include Fund, Organizatin, Accunt, Prgram and Activity. The structured hierarchies within Banner will be incrprated int each data warehuse dimensin. Since transactin data is required, attributes such as dcument type will be included t help end users categrize transactin activity. The data warehuse will cntain three years f histrical data crrespnding t the FOAPAL structures summarized by mnth, fiscal quarter and fiscal

2 Rensselaer Data Warehuse Prject perid. The summarized data will be supprted with the current tw fiscal years f transactin detail. The data warehuse will begin t address fundamental reprting aspects f research related activity by incrprating key Grant attributes such as grant cde, descriptin, ttal amunt awarded, grant perids, grant status and spnsr agency. The data warehuse will incrprate key transactin related infrmatin such as transactin amunt, dcument cde, dcument type, transactin descriptin. Additinal items assciated with transactins will be identified and incrprated during the design phase. Unless directed therwise by the guidelines develped by the Data Plicy cmmittee, the infrmatin in the data warehuse will be secured by fund and rganizatin, enabling a fund wner t access all activity assciated with the fund regardless f the rganizatin. Similar t Banner security, this apprach will restrict peple t view nly their financial data. Data will be refreshed n a daily basis. The data warehuse will preserve histrical reprting by ensuring data assciated with a fund r rganizatin is nt changed as these structures change frm fiscal year t fiscal year. Additinally, the flexibility t reprt n past histrical data using current and fiscal year end structures will be incrprated. Phase II Labr Budget and Actual (July 2002 September 2002) The data warehuse will be expanded t incrprate psitin, jb, persn and distributin data. The data warehuse grup will wrk clsely with the budget ffice t integrate infrmatin with the quarterly frecasting and annual budgeting prcess. Phase III Research Analysis (Octber 2002 December2002) The data warehuse will be expanded t incrprate spnsred research infrmatin. Key areas addressed during this phase will further enhance the analysis f research data by spnsr, time, FOAPAL and Grant PIs. Results f the Financial Data Audit Analysis Data Audit effrt cnsisted f identifying data surces, and determining the cnsistency and integrity f the data. Thrughut this prcess, the data Warehuse grup has identified several issues. These issues are lgged and will be wrked ut by the Financial Analysis Implementatin team and the Data Warehuse grup. Several issues listed belw have a direct impact n the scpe fr the July 2002 deliverables and therefre have t be addressed and agreed upn:

3 Rensselaer Data Warehuse Prject Financial Statements The finance department needs t simplify and reduce the time it takes t prduce and distribute quarterly management reprts and annual financial statements. Currently, a large number f queries are executed t extract data frm the Banner business systems t integrate int lcal spreadsheets and Micrsft Access database tables. This time cnsuming prcess requires many steps t manually integrate and regrup data frm varius surces int meaningful financial infrmatin. Thse respnsible fr the preparatin f this infrmatin are requesting a single surce f integrated, reliable and timely financial infrmatin that is interfaced with an easy t use and flexible reprting tl. Issue: Currently the data as it is cllected in Banner des nt crrespnd t the frmal presentatin categries utilized in the annual financial statements. The finance ffice must first take the necessary steps t analyze and identify hw the financial statements prepared befre the data warehuse can incrprate the frmal prductin f financial statements. Furthermre, the data warehuse must incrprate a mechanism t integrate Rensselaer Technlgy Park year-end summarized financial data fr the prductin f annual financial statements. Reslutin: Finance has t analyze and determine the new reprting structure f the financial statements. Once the structure is determined, the implementatin apprach needs t be develped, thrugh Banner r the Data Warehuse. In additin, the DW grup will need access t the Technlgy Park financial data. Timing: T be included in the July 2002 deliverables, the financial statements reprting structure has t be designed by the end f February 2002 at the latest. Otherwise, it will be scheduled fr a later delivery date. Fllw-up ntes: On February 26, 2002 the Data Warehuse Steering Cmmittee has apprved the exclusin f the financial statements frm July 2002 deliverables. Once the Financial Statements reprting structure is implemented in Banner, the cmmittee will re-visit this issue. Principal Investigatr s and Multidisciplinary research data. There is a requirement t be able t reprt and analyze Research expenditures and budgets data based n the attributes f all Principal Investigatrs assciated with the Grant and have better infrmatin available n the Multidisciplinary research. Issue: Currently within the Banner Research mdule we are capturing nly infrmatin abut ne Principal Investigatr. Reslutin: Multiple PI s data has t be captured in Banner t prvide a single and reliable surce f infrmatin. Timing: Has t be implemented by Octber 2002 befre the implementatin f the Research Data Mart. Fllw-up ntes: Since the multiple PI s data is currently nt available, the Data Warehuse Steering Cmmittee has decided n February 26, 2002 t exclude it frm July 2002 deliverables. Multiple PI s data will becme available thrugh the implementatin f the Research data mart.

4 Capital Prjects Rensselaer Data Warehuse Prject Currently there is a requirement fr analyzing, tracking, and reprting Capital Prjects infrmatin by the assciated Prject Managers. Issue: Unfrtunately the infrmatin regarding Prject Managers is nt stred anywhere. Reslutin: We either identify hw t stre it in Banner r decide that we will nt meet this requirement. Timing: N/A Fllw-up ntes: Since the infrmatin is nt available, the Data Warehuse Steering Cmmittee has decided n February 26, 2002 t exclude it frm July 2002 deliverables. Technlgy Park financials Currently, the Rensselaer Technlgy Park data resides in a lcal business system and is manually integrated int the annual financial statements. Reslutin: The Rensselaer Technlgy Park financial data will need t be laded in summary either int Banner r int the data warehuse. Timing: If the Financial statements nt included in July 2002 deliverables, there is n cmpelling reasn t lad the Technlgy Parks financials int the Data Warehuse. Otherwise the DW grup needs access t the data by mid February. Fllw-up ntes: On February 26, 2002 the Data Warehuse Steering Cmmittee has apprved that the Technlgy Park financials will be re-entered int Banner by the Finance ffice using the apprpriate FOAPA structure that will allw clear separatin f the Technlgy Park financial data. Summarized Technlgy Park financials will be laded int the Data Warehuse in the same fashin as Try and Hartfrd data.

5 Rensselaer Data Warehuse Prject Salaries encumbrances As identified by DecisinWrks Cnsulting in the Data Warehuse Requirements Analysis and Priritizatin Findings and Recmmendatins dcument: Implementatin f data t supprt financial analysis in the data warehuse will prvide the prtfli managers with mre rbust tls t supprt the new budget and planning prcesses and prvide better cntrl ver their current spend rate. They will be better equipped t justify their expenditures, identify available budget mnies, and react mre quickly t negative variances The feasibility f implementing this pprtunity is mderate...hwever, implementing salary encumbrances in Banner is a key prerequisite t supprting this requirement in the mst meaningful manner. This prerequisite pushes the feasibility f this pprtunity t the mderate range. Financial analysis was determined t be ne f the highest pririty requirements, in spite f the feasibility challenges described abve. On Octber 18, financial analysis was selected as the initial phase fr the data warehuse prject. Issue: There is n system in place that captures salaries encumbrances. T include any utside Banner slutins, we will need access t the design f the surces by the end f February Reslutin Once a Salaries encumbrances slutin is identified and implemented, the DW grup will make plans t lad this data int the Data Warehuse. Fllw-up ntes: Due t the lacking data, n February 26, 2002 the Data Warehuse Steering Cmmittee has apprved the exclusin f the Salary Encumbrances data frm the July 2002 deliverables.