Looking Back and Surging Ahead

Transcription

1 Business Intelligence atunisa Looking Back and Surging Ahead IBM Business Analytics User Group September 2011 Stuart Ainsworth Stuart Ainsworth Planning and Institutional Performance

2 Expansion of Data Warehouse Strategic Focus for EDW development Real Time reporting Next generation BI toolsets BI UniSA IBM Cognos 8 Upgrade technology upgrade rationalised reports centralised report management from desktops (whilst still maintaining devolved development) Prototype Data Warehouse Move beyond source data to dimensionally modelled data warehouse Implemented first schemas for Research Performance Devolved Report Development Impromptu and Powerplay on desktops Implementation of Cognos 7 Impromptu and Powerplay for developers Cognos Upfront for UniSA wide report execution Creation of Operational Data Store p Primarily for Staff and Student Portals Opened up data for custom reporting Consisted of source data and summary views

3 BI at UniSA now Reporting capability Large number of operational reports (single data source) Few integrated suite of reports (eg. workforce performance) Cognos reporting tool used across UniSA Central data warehouse diverse subject areas and external data sources Education Regular BI training at different levels Co ordinated induction and support for C8 report developers BIHub one stop shop

4 UniSA BI Technical Architecture Requirements Data Quality HR Research Student t Staff Student Views Views Securit ty Operational Data Store Se ecurity Presentation Design Data Presenta ation BI Hub Logical BI outputs t Designs Reports, Cubes etc Finance Data Extraction Data Profiling Source Systems ETL Development ETL Process Changed Data Transform Data Apply Business Rules Enterprise Data Warehouse Data Integrity Layer BI BI Developers Consumers

5 However Are we agile enough to know what external threats /opportunities to respond to, when and why? Do we know which factors to put limited resources into and which to ignore (eg. retention)? Once the path is clear how do we deliver the insight and context to staff on the ground in their day to day work? (including follow up insights?) What s needed a BI Strategy, not Enterprise Information Management or Data Warehousing Strategy BI requirements explicitly driven by Corporate Plans BI has to be planned, prioritised and monitored based on its impact on decision making (so track this) BI has to shorten the cycle of request data analyse data request data Strengthened governances senior management drives investment (it s not about the data or technology) Bl Balance between bt operational reports, more integrated, t cross institutional reports data about processes rather than transactions/interactions ODS vs EDW vs source system reporting. Lots of data, but answers can be elusive!

6 BI Health Check Source: Gartner 2010

7 BI Building Blocks Bothtechnical technical and non technical can t have one without the rest linked to business deliverable (checklist) BI Asset Management Governance and Standards Data Quality Customised Information Delivery Training i and System User Support Environment Communication and Culture

8 BI Building Blocks Customised Information Delivery BI Asset Management Greater use of existing tools for BI Asset Inventory a customised experience BI Assets, data definitions, master drill through (across) reference lists, standards, etc dashboards Central view of current data and data into EDW analysis assets ( duplication) Data Quality student lifecycle DQ activities (profiling, matching) workforce performance historical and trend Dt Data standards d in new system design 3rd party/external Performance indicators for DQ Socialmedia? System environment Increased performance, security, robustness Near real time reporting Support for visualisation tools

9 Governance Senior Management Group Info Management Group BI Steering Group Corporate Information Systems Steering Group

10 BI development process Requirements Development Implementation Mainstream Development requirements are known regular reporting cycles Mainstream or throw away Inquisitive Requirement Prototype ETL & Reports Fuzzy Relationship matching Exploratory Development requirements are NOT well known inquisitive in nature may be one off or become mainstreamed Note: data + other deliverables

11 EDW Architecture New (project) requirements UniSA data sources External data sources Requirements Minor changes mature, repeatable to existing Dependability

12 Lessons Strategy Invest Obtain Buy-in Ensure BI goals are strategic Don t let operational data needs drive the overall strategy Good technology and skills can reduce build time and improve quality Data custodians know their data best and can assess (and fix) DQ issues Requirements Make sure population of data warehouse is explicitly driven by a business requirement Don t try and replace source system reporting that already exists The business must trust the warehouse, therefore must see Governance that it is treated as a corporate system Timeliness of Data Methodology There will be a continual request for real-time data Seek technology and design improvements that can provide this Support both Exploratory (Agile) and Mainstreamed BI Development

13 Next steps UniSA BI Framework ongoing capacity Annual plans to stay responsive Injectionintothe into the decision makingprocess Promotion and integration into other key processes Induction Performance management Manager training Planning and review processes More visual tools Increased data and report competency

14 Questions?