Business Issues in Business Intelligence - Essay Example

ID # ETL Issues in Business Intelligence Systems Business intelligence (BI) is composed of a variety of tools and applications to gather, store, analyze, and provide access to data to help organizational users (i.e. managers and CEOs) make better business decisions. Normally, the BI tools and technologies comprise the operations of query and reporting, decision support systems, online analytical processing (OLAP), statistical analysis, forecasting, and data mining. In simple words, business intelligence makes the processes of information discovery and analysis much simpler for decision makers at all levels of a corporation to more simply access, identify, evaluate, collaborate, and perform operations on information, anywhere and anytime (TechTarget; Microsoft).

Problem/Issue:Though, many business intelligence tools work fine and help organizations take better decisions. They provide exact targets, graphs, drill-through and drill-downs. However, a great deal of work in an operational data warehouse system entails processing of data collected from different operational systems into the data warehouse. In this process of decision making and making intelligible decisions, there exist many problems regarding ETL (extraction, transformation and loading). In other words, while collecting huge amount of data from different sources we can face many issues regarding ETL.

These issues can also influence the overall quality of decisions and business operations. In addition, ETL can entail substantial complexity and significant operational problems those can take place due to improperly designed ETL systems that can eventually influence the performance of BI system’s working and operations (Scott). Documentation and Analysis:The successful implementation of BI requires plenty of data analysis and evaluation. In this scenario we need to assess the quality of data in predicting the results.

On the other hand, data warehouses are normally assembled from a mixture of data sources with different formats as well as purposes. In this scenario, ETL is a key process to bring the entire data together in a standard and uniform structure. In case a problem happens to ETL process overall working and operations of the corporate decision support can be exaggerated. In addition, it will lead to ineffective and lower quality results. Moreover, major issues in ETL can include: (Kimball and Caserta; Kimball and Ross, The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling, 2nd Edition) Low quality of dataDifferent sources of data and target data structuresDependencies exist in the dataComplexities in meta data usedComplex data relationshipsThe presence of any of the above listed issues can affect the implementation of business intelligence.

These issues can also lead toward low quality business decisions. The variety of data values or data quality in BI operational system can increase the hopes of designers at the time validation and transformation policy is specified. In addition, business data profiling of a source all through data analysis can help identify the data environment that will require to be administered through varying rules and conditions. Moreover, this will direct to variation of validation rules openly as well as implicitly applied in the ETL process (Kimball and Caserta; Kimball and Ross, The Data Warehouse Toolkit: The Complete Guide to Dimensional Modeling, 2nd Edition).

Recommendation: From the above discussion, it is clear that the overall process of ETL should be improved. As a result, the quality and performance of business intelligence will be improved. In addition, effective BI system will allow for effective decision support and superior performance. In this scenario, Van Scott suggests a solution that involves four common approaches to transforming and loading data issues for the business intelligence system working and corporate decision support. These solutions are outlines below: (Scott) Build a custom solutionBuy a code generatorBuy a data transformation engineUse a mixture of the above Works CitedBrackett, Michael H.

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11 March 2008. 23 January 2012 .Scott, Van. Extraction, Transformation, and Load Issues and Approaches. 01 January 2000. 20 January 2012 .Stewart, Syd. Business Intelligence Issues. 2008. 24 January 2012 .TechTarget. business intelligence (BI). 2012. 24 January 2012 .