Artículos IT, información y publicaciones sobre Integracion de datos

Addressing a business intelligence project is important to proper assessment of the ETL tool that we will use. The tool based on which we will implement our procurement processes of the Datamart, Datawarehouse or storage structure based on which further exploit the data. It is a cornerstone for the design, construction and subsequent evolution of our BI system. We will analyze technical issues only, without entering into the economic aspects or otherwise (licenses, agreements, technical support, tool changes, etc. ..) . Note that the ETL processes, are closely linked to the processes of data profiling and data quality, here we will not consider.

There is an ever greater need in the Business Intelligence environment to have the information in the shortest time possible, data generation cycles getting shorter and updating of data in near real time. There is talk of 'Operational Business Intelligence (OBI)' and 'Real Time Decision Support'.

It is critical to reaching operational data analytic environments in shortest possible time. There is a need for a 'Real Time Data Integration'.

In the optimization of these data integration processes, we must consider both the usual source data (ERP's, CRM's, operating systems, databases, flat files, Excel, XML, etc. ..) and other from more immediate nature such as messaging queues and on-line information accessed via Web services or RSS.

Open Data is a movement that is meant to make easily accessible to citizens and businesses that collect public government data.

Open Data is supported by the W3C and other international bodies, and gradually adds up initiatives in different countries. The first step is the initiative of a public body, was made publicly available certain information in one or more standard formats easily 'treatable'. Since there may be other agencies or businesses that add value to that data across or enriching them with other data sources, or developing applications that allow user to see that data in a friendly environment.

The task Data Profile of SQL Server Information Services stores the results of profiling in an XML document that can be examined with the Data Profile Viewer. Article Dataprofiling with SQL Server 2008 explains how to use this new Task in SSIS.

Although this method is very simple, sometimes may not be sufficient. Addressing a data quality project may involve, for example, storing a history of profiles to assess how data quality of processed data has been improving.

The best way to work with historical data is using a database and storing the data in tables, where you can make queries, reports and comparisons. To achieve that all you would need to do is moving the metadata that the profiling task has been storing in the XML file to database tables.

Well, someone has already prepared an easy way to do it. Thomas Frisendal from the website Information Quality Solutions explains how to create an XSLT file for each type of profiling that is used to extract the XML generated by the Data Profile Task SSIS into one or more XML files with a format that can be directly imported to tables .