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Analytical Need A common requirement in data analysis is to be able to view and compare slices of data from different time periods to current date. Business applications for this vary, from identifying trends to predicting future behavior, requir...
Data accumulation is SiSense's method for building ElastiCube data without completely refreshing a table. This post describes the data accumulation functionality and gives a user the ability to customize and optimize their ElastiCube build process.Th...
Analytical Need A key table (click the link to download a demo Data Model) is a central table that stores all the relationships between the primary key values. Modeling Challenge The main advantages of using Key Table: It helps to tidy up a ...
Source data that is flattened may require some or all of the columns of a source table to be transposed, in order to work seamlessly with SiSense’s functionality. This post will outline the cause and two possible solutions to this issue. The first so...
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 com...
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 We have multiple sources 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 t...
Analytical Need In a dashboard, we wish to analyze how our entities (sales, inventory, tickets etc.) behave and break them by several categories. However, not all entities share the same categories. We wish to avoid a situation in which selecting...
DescriptionA common visualization is a comparison between personal KPIs and the rest of the team KPI averages. The main challenge is when applying a security configuration, the other users’ data is filtered out Example A typical Elasticube for sales ...
Data is a beautiful mess. As data heroes, we spot the mess and get rid of it to highlight the beauty. Here are a couple useful tricks to detect incorrect data. We will assume a table that describes the number of meows made by each cat in each box, o...
For general information on types of data relationships, potential complications and how to resolve them, see the following articles: Data Relationships: Introduction to Many-to-Many Data Relationships: Check Type of relationshipData Relationships: ...
For general information on types of data relationships, potential complications and how to resolve them, see the following articles: Data Relationships: Introduction to Many-to-ManyData Relationships: Check Type of relationshipData Relationships: O...
The Problem Date information from the source is represented as an integer, with the format YYYYMMDD. We need the information to be represented as a date-time data type in Sisense. The Solution This will utilize a custom field to convert the valu...
For general information on types of data relationships, potential complications and how to resolve them, see the following articles: Data Relationships: Introduction to Many-to-ManyData Relationships: Check Type of relationship (You are here)Data R...
Analytical Need Using the lookup function to import data from one table to enhance another, based on specific conditions or filters. This might be required if we wish to import attributes from a table which is not unique. For example, a transpose...
This article outlines how to create a date table that flags whether or not a particular date is within a particular range, based off of the current date. For example, if today is the 100th day of the year, we may want to analyze information for the f...
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