Business and IS Performance (IS 6010) MBS BIS 2010 / th November 2010 Fergal Carton Accounting Finance and Information Systems

Last week Decoupling point Control objectives undermined Performance visibility is a design question Builder quotation exercise Apple case study

This week Decision support DW architecture and ETL Data quality Real time information Response times and refresh rates

Decisions compare plan to actual Compare –Plan to –Actual figure Decide on course of action

What is a Decision?

Extraction Cleaning Transformation Loading Relational Database on a dedicated Server De normalised, data Static Reporting Scrutinising Multidimensional Data Cubes OLAP tools Data Warehouse Source Systems Discovering Data Mining ……. Data Staging Area Exploiting the DW data

ETL Tools Extraction, Transformation, and Loading Specification based Eliminate custom coding Third party and DBMS based tools

Data extraction and transformation Getting data out of legacy applications Cleaning up the data Enriching it with new data Converting it to a form suitable for upload Staging areas

Data Quality Problems Multiple identifiers: –some data sources may use different primary keys for the same entity such as different customer numbers. Multiple names: –the same field may be represented using different field names. Different units: –measures and dimensions may have different units and granularities. Missing values: –data may not exist in some databases. To compensate for missing values, different default values may be used across data sources.

Data Quality Problems Orphaned transactions: –some transactions may be missing important parts such as an order without a customer. Multipurpose fields: –some databases may combine data into one field such as different components of an address. Conflicting data: –some data sources may have conflicting data such as different customer addresses. Different update times: –some data sources may perform updates at different intervals.

Example 1 – the supplier file Sup codeSup nameSup addressCityPhone 4 digits Sup codeSup nameSup address…PhoneCat 3 letters +1,2,3 depending 4 digitson total purchases last year OLD NEW New supplier code to include city where firm is based Assignation of category based on amounts purchased

Example 2: merging files Complete customer file based on Accounts and Sales and Shipping OLD (finance) CustIDnameaddresscityaccount numbercredit limitbalance OLD (sales) OLD (Shipping) CustID*nameaddresscitydiscount ratessales_to_daterep_name CustID**nameaddresscityPreferred haulier

Life cycle of the DW Operational Databases Warehouse Database First time load Refresh Refresh Refresh Purge or Archive

Real time information Up to date On-line Actual data Live feed Decisions made on what basis?

Real time requirement? Historical sales or accounting data, not real-time Sales as quarter end approaches Inventory levels for MRP Exchange rates, when is Visa rate calculated? Real-time processing: card transactions down

Real time requirement for Apple?

Response times Response times are a function of : – response time, –Infrastructure elements, –Database sizing –Transaction processing –Interfaces –Reporting –Other processing demands –Peak times –…

Refreshing databases Timing Criticality of information Volume of data Response time Real-time requirement Level of aggregation / granularity

Refresh Optimization

Determining the Refresh Frequency Maximize net refresh benefit Value of data timeliness Cost of refresh Satisfy data warehouse and source system constraints