How can you get your overall position in your money data-valuation activity ?
Adopting the cubic form in the design of any Owndated Webquantum related to it financial statement
The webcashaccounting and the "flashed position” (flash button displayed at the Do-G-Phone"
The source of data-valuation rights should be the WUW’s General Ledger project
An OLAP Cube is the key data structure used to ensure multidimensional functionality; it is similar to a table in a traditional database. The key difference is that cubes do not treat all the data the same as tables do but instead have categories of data called dimensions and measures.
Dimensions are used in OLAP to help simplify the visualization of the dataset. Figure 1 is an example of a data cube for a particular dataset. As one can see this data cube has 3 dimensions namely: time, location and product.
Drilling
Each dimension is a broad group title that allows you, the user, to get a broad sense of the entire dataset. In computer science, one could think of it as a layer of abstraction that hides the details. For instance the time dimension can further be subdivided into years, quarters, month, weeks; these are levels within the time dimension hierarchy. In order to get a more detailed view, OLAP uses drilling to traverse these various levels of the hierarchy.
Categories
Categories are members of dimensions. A category is basically an item that matches a specific classification. For instance for the time dimension, years is a corresponding category. There is a difference between the levels explained in drilling and the categories discussed here. Levels are the specific name while the categories are the instances in our dataset. For instance, in Figure 1, we have a 2003 category in our dataset but not a 2009 category, yet 2009 is a ‘year’.
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Online analytical processing, or OLAP (/ˈoʊlæp/), is an approach to answer multi-dimensional analytical (MDA) queries swiftly in computing.[1] OLAP is part of the broader category of business intelligence, which also encompasses relational databases, report writing and data mining.[2] Typical applications of OLAP include business reporting for sales, marketing, management reporting, business process management (BPM),[3] budgeting and forecasting, financial reporting and similar areas, with new applications emerging, such as agriculture.[4]
The term OLAP was created as a slight modification of the traditional database term online transaction processing (OLTP).[5]
The solution is the automatic construction following the cycle that starts when you trigger the smart contract that enables you for your personal Business Process as a Service created to give people the power to use the money data-valuation practice. Then you should create with US$ fiat 10.- = 1 O.W that is a digital object in property asset which becames 1 UUS$$ (universocial digital US dollar) in legal tender. In reason of the data-structure compounding your personalised digital object being each one of yours UUS$$ your dynamic accounting at your personal "#webcashaccount" requires processing your money's body data in it digital dynamic life. That's why your identity registration at the WUW's General Ledger is computed with the time of your money data-valuation to treat algorithmical business intelligence, allowing your creations of futures UUS$$, being your Personalised Digital Dynamic Savings, being yours digital registered properties Owndated Webquantums that has a cubic design, an OLAP Cube, Your personal Olap Cube to let you see your flashed position account displayed at your Do-G-Phone data-inducer.
Owndated Webquantum creations
