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Encoding Quick Response Code in Java OLAP Databases

OLAP Databases
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In presenting this topic at user groups and conferences, the percentage of companies that integrate OLAP databases with the BusinessObjects Enterprise deployment remains small There are a number of reasons for this
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Companies often treat OLAP databases as separate applications for several reasons First, each OLAP vendor provides their own access tools: Hyperion provides Web Analysis (formerly named Analyzer) and a spreadsheet add-in to access Essbase OLAP databases As Hyperion has now entered the query and reporting space, Hyperion and Business Objects increasingly compete with one another Microsoft uses Excel to access MS Analysis Services cubes and in Q2 2006 announced intentions to acquire ProClarity to provide visualization and dashboard capabilities to Analysis Services Business Information Warehouse (BW) provides Business Explorer as a front end to BW (Net Weaver) Info Cubes Just as data marts and BI implementations can be implemented departmentally, so can OLAP databases Unless a business sponsor and program management are in place to integrate the two, it seems rarely to happen As these leading OLAP vendors offer their own front ends to their databases, customers often incorrectly assume that they must use the corresponding front end Furthermore, Business Objects approach to OLAP access has gone through many transitions, so confusion and lack of awareness abounds With BusinessObjects XI, the vendor now offers OLAP Intelligence, previously called Crystal Analysis, as a way of accessing third-party OLAP databases Also, new in XI Release 2 is the ability to access OLAP databases through a universe Finally, BusinessObjects XI itself, with its microcube engine, is also considered an OLAP tool Thus, many companies assume that they need only BusinessObjects XI and do not need another OLAP database This assumption is reasonable However, because of some of the inherent limitations with the dynamic microcubes, there are instances in which an OLAP database can provide some significant benefits as long as the competing vendors do not encroach on each other s space within a customer organization One of the biggest differences between the OLAP capabilities via the BusinessObjects XI microcube and an OLAP database is the data volume There is no hard rule as to the size of a BusinessObjects XI microcube; it could be 300,000 rows of data It would not be 3 million, as is the case of an OLAP database In this respect, it is much more appropriate to think of applications such as MS Analysis Services and Essbase as databases or data sources than as competing tools There also is a significant difference between drilling within a microcube and drilling against an OLAP data source The goal with any OLAP deployment is to ensure that when users drill, it is at the speed of thought Because an OLAP database is pre-aggregated, the response times are more predictable than relational query times To ensure fast drilling times against a Desktop Intelligence or Web Intelligence microcube, report developers often cram too much information into a report They are trying to get the microcube to act like an OLAP database This approach is doomed to failure When users drill within either a Web Intelligence or Desktop Intelligence report, they are drilling within a subset of cached data, as shown in Figure 14-2 When a user drills from year to quarter, the details for quarter already exist in the report If not, then the user can drill through to the details and send another query to the relational database The results are fetched and stored in the microcube Herein lies a challenge: if your relational database is well tuned, this drill through to detail could take a few seconds or a few minutes (hopefully
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