Introduction Calculating transaction frequency for a given dimension is a common requirement across many verticals. e.g. Average Time Between Purchases by a Customer. Average Time between support tickets etc. While this can be calculated in SQL it ...
The point of this article is to provide a method to a value associated with the most recent data in a date selection. Implementation Step 1: in the Elasticube, create a field transforming the date field into an integer using the formula below. Then ...
Analytical Need Customer's fiscal year does not comply with the Georgian 12-month calendar and starts on a different date than January 1st. Example: Customer’s fiscal year is from April 1st to March 31. This means that April should be flagged as...
Analytical Need Market Basket Analysis is a data mining technique that is widely used to identify consumer patterns, such as which items are purchased together, or how the purchase of one item affects the likelihood of another item being purchased. ...
A relationship between tables specifies the field/s which the 2 tables have in common. In Sisense, we create relationships between tables in the ElastiCube. Poorly modeled data relationships can lead to one or more of the following: Complex data se...
Analytical NeedAnalyzing information by date can be very useful, but not every source data set provides enough information to do this kind of analysis.Modeling ChallengeWe will need to import a date table, which will act as a reference for all time q...
Introduction This article demonstrates how to avoid counting weekends and holidays when calculating the difference between two dates. Example - Average Shipping Time in Business Days Steps In order to ‘subtract’ two dates and avoid counting the wee...
Introduction In this post we'll learn how to create a drill down hierarchy for Days-->Hours-->Minutes-->Seconds. A general quick solution, in case you need the drill mostly for pivot table visualizations, would be to use the ElastiCube to model addi...
Question LAG & LEAD Functions are functions that give access to multiple rows within a table, without the need for a self-join. The LAG function is used to access data from a previous row, while the LEAD function is used to return data from rows fur...
In the past, the Postgres vs. MongoDB debate looked like this: you had Postgres on one side, able to handle SQL (and later NoSQL) data, but not JSON. On the other, you had purpose-built database management systems (DBMS) — like MongoDB, which was de...
The promise of Postgres JSON JSON support is the most interesting new Postgres feature of the last few years. It relaxes the primary constraint of SQL databases — the rigid schema structure — by letting you store semi-structured data in your tables ...
