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component will always be used as a precalculated number and, more importantly, the underlying calculations will not change (as in the calculation of net profit), then we can look at precalculations to help with the querying process. If we find that the calculation may change over time (as in the approach we use for the planning process or the manufacturing process for a specific material) or that we need to use underlying basic key figures for some other activity, then we should upload the data as the basic key figures and let the query do the calculation.One of the more prevalent concerns surrounding the uploading of data is the need for consistency in the uploaded data. By that I mean, will the data be uploaded so we can combine the information together in a query, and will this make sense as well as be accurate and consistent Take, for example, the uploading process for a specific material. The material is sold throughout the world, and in each country you can buy the same product, but under different names and SKUs. For example, suppose the same widget is sold in both North America and Europe. In North America the characteristic value is 1234, but in Europe the value is 4567. We need to be sure that either during the upload or during querying these two material values are grouped together so that we can get the total picture rather than just one region s information. This means that the same material will be identified with different numbers and possibly different naming conventions. Now, in an ideal world we would use the functionality of MDM (Master Data Management) to do all the consistency checks to make sure that the master data is consistent and can be consolidated to generate a true view of the total amount of inventory of that specific material. In the real world, we may not be implementing MDM, so BI would have to take care of this for us. Therefore, we would need to look to the consolidated InfoObjects that are used for this purpose. These InfoObjects allow us to group/consolidate the data to query and get the appropriate information. These consolidated InfoObjects are part of Standard Business Content (SBC) and are discussed at length in 14. These are just of a few of the questions you ll need to consider many more questions are involved in the uploading process and the integration of the uploaded data and the query performance and format. This topic will come back numerous times during our discussions of query properties and the functionality of queries. Now that you understand the basics of a Data Target, InfoProvider, and InfoObject, we can review the specific types of Data Targets.
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An InfoCube is the central object in BI for the storage of data. It is the most used object for storing data and generating queries due to the relational structure of the tables. (Based on the architecture of your BI system, you may decide to generate all queries from a MultiProvider object, but that would be a decision specific to each company.) The structure of the InfoCube was set up specifically to be able to execute and run query processes as quickly as possible. Therefore, it s about 99.9% sure you will be using InfoCubes during your BI implementation. InfoCubes can answer numerous questions for you concerning reporting. For example, depending on the characteristics and key figures you have grouped together in your InfoCube, you can ask questions such as How much product am I selling in a specific region during a specific period of time What is the total P&L and balance sheet information for a company code during a specific year How much has a customer purchased of a group of materials and how does that amount for the current period differ from the previous period
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