Analytical Need There are cases where you wish to know for a certain point in time, how much you have accumulated up until now.This is called Running Sum.Although it is possible to use this in the dashboard, we may need to have the running sum on eac...
Analytical Need Many times we would like to deep dive into our data and view it in a more granular fashion to conclude from it. Certain business needs might require us to use date-time hierarchies to help us understand performance trends such as Sale...
Rules To Live By When Designing An Elasticube A list of recommendations which should be considered when developing an elasticube. Start Small Build your ElastiCube incrementally. Start with only two tables, create an appropriate relationship between ...
Analytical Need There are cases where our data arrives in aggregate form, like in Google Analytics (where the lowest granularity level is daily). If we wish to free up clutter in the dashboard and prevent the user from figuring out which field comes ...
Analytical NeedIn many cases a hierarchy appears in the data structured as 2 levels - A parent and a child. The business user would like to see the entire hierarchy and analyze the data according to the different levels, but can't do that since they ...
Analytical NeedThis dimension table keeps every change that has been made. The user wishes to see historical data per the dimension and not just the current state.Example: Transactions per organizational hierarchies, price list, historical currency r...
Analytical Need For different use cases, it can be relevant to present a timeframe of different business entities and the relations between them. For examples, such use cases can be: Present hotel vacancies by room number or type Analyze ticket load ...
Analytical Need We may encounter a situation in which a table has several fields that together identify each record. Each of them may appear several times but their combination is unique. Modeling Challenge In our data model, we have 2 tables that ha...
Analytical Need We have one central source for our measures and multiple sources to slice & dice these measures. Modeling Challenge How do we build a schema that will enable us to perform our needed analysis?We will need to connect all of our tables ...
Analytical Need There are cases where we need to define an association between two entities. This association is comprised of the entities and not by each of them separately. For example, students & courses. We need to have a list of each student, a ...
Use Case:Sometimes, we would like to create calculations from the fact table and we need to have a continuous range of dates or in other cases, we need to count the number of employees (just as an example) that we have in the company.We strongly reco...
Analytical NeedA common use case is to know the number of new users in the system. It could be that same user appear in various months but we want to count each unique user only once.If we will use a simplistic approach of count distinct calculation ...
Analytical NeedThere are many cases where our data comes in with different granularity levels. For instance, Actual vs. Target where the actuals are at the product level and the targets are per sub category (higher hierarchy of the product). How can ...
Analytical Need‘Funnel analysis’ describes process flow, where in its beginning the number that we measure is relatively big, and in each step within the process this number is getting smaller along the way till the end point.The most common example ...
Analytical Need Working with 2 fact tables which have a direct 1:M relationship, and fetching measures from both. A common example from the retail industry is Order Header and Order Line Items tables Modeling Challenge A standard connection could cre...
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