When editing a cube or live data source, I'd like to be able to more quickly add another table.  Right now, you click on the  +DATA button at the top, and get presented with all the historical connections, etc. Instead, what if you add an "Add Table" button inside the Data Sources panel?: That is, under the triple dots in red, have a new option to quickly reuse that connection and add another table. Then you'd avoid the proliferation of connections, also (the yellow connection list, in my example). ... View more

There are many scenarios where a model contains data for many distinct groups, such as customers, and you want viewers to only have access to the data that pertains to their specific customer. This is easily implemented with row level security, when there is a data column that uniquely identifies each customer. But what if you have a requirement that certain types of viewers should see all columns of data per row, while others should not have access to certain columns? Here is an approach that can be implemented right out of the box in Sisense. The one prerequisite is that any table that contains sensitive data must have a column that uniquely identifies every row, i.e. a primary key column. For every table that contains sensitive data in certain columns, create a new table that contains the original table's primary key column, a binary "switch" column with a name like [Access Allowed] and a column for each of the sensitive columns. Remove the sensitive columns from the original table. Modify the import query to load only the non-sensitive columns in the original table. Modify the import query to load the new table with the primary key and sensitive columns of the original table twice, once with [Access Allowed] set to 1 and the second time with 0 and blank (or null) for all the sensitive columns. Associate the new table to the original table by primary key column Create a dimension table for secure access with the column [Access Allowed]. One row with value 0, one row with value 1. Associate the dimension table with the sensitive data table by the [Access Allowed] column. Set up a data security rule on this column, assigning the secure user group to value 1 and the general group to value 0 If there is a hierarchy greater than two levels of column-level data security, this model can be extended to create additional one-to-one related tables to the original table. ... View more

Summary: Live Model slow, can be fixed by prioritising a filter I use a Live Model to return info about a few records from a big dataset. One filter should efficiently narrow the big dataset down. But the server sometimes applies other filters or joins first, making it unusably slow. I want an option to tell the Live Model to fetch the important filter's items first, and then write those items into the filtering clause when writing the main query. That will cause the server to correctly discover that applying the important filter first is the most efficient query plan.   Details (I'm querying SQL Server, but I suspect other sources would also benefit.) Sisense documentation says "Analytical Engine inserts filtering clauses into the innermost SQL statement. This means that filtering is the first operation performed". Sometimes that helps performance. But it depends on the source server. If you apply multiple filters or joins, the server may decide to perform a less efficient one first, or it may parallelise. In my case, my query went from a few seconds to over an hour depending on the server's choice.  The problem is that the server can't estimate the cardinality of the "filtering clauses" entered by Sisense. For example: The server doesn't know that my "dimCustomer.[Customer Name] = 'Joe Bloggs'" filter returns only 100 rows from my fact table, whereas "dimDateTime.FiscalYear = 2022" returns 100,000,000 rows from the fact table. There is a solution. Instead of "Where Fact.[Customer ID] In (Select [Customer ID] From dimCustomer Where [Customer Name] = 'Joe Bloggs')", Sisense should first run the query Select [Customer ID]... query to find that Joe's ID is 5. Then put the result into the filtering clause, i.e. "Where Fact.[Customer ID] IN (5)". For a hardcoded ID like that, the server can estimate the cardinality, so it sees that filtering on [Customer ID] first will be more efficient that other query plans. Sisense mustn't just do that for all filters. If it tries prefetching "dimDateTime.FiscalYear = 2022", that'll return all 31,536,000 seconds, and then pass that back in the query as "Where Fact.DateTimeID IN (...)".  Solution: The solution I request is: Allow the Live Model developer to set a "Prefetch Filter Items" flag on a field. If it is set, when a widget or dashboard filters that field, then Sisense first creates a query "Select dimSomething.[Relationship column] From dimSomething.FieldWithPrioritisedFilter". Then, when building the main query, change the "filtering clauses" to be "Where Fact.[Relationship column] IN (<put prefetched values here>)". Reference: For reference: https://docs.sisense.com/main/SisenseLinux/analytical-engine-overview.htm: Analytical Engine inserts filtering clauses into the innermost SQL statement. This means that filtering is the first operation performed, minimizing the number of rows that need to be scanned in order to process the query. Complex filters, such as top ranking and filter on measure are significantly improved as a result. Proof of concept: Build a Live Model. FactA joins to DimB on ID_B and to DimC on ID_C. The source is SQL Server. In SQL Server, all three tables have millions of rows, and the FactA has foreign keys to DimB and DimC. DimB.Name has a unique name for each row. DimC.Type is 1 for half the rows, and 0 for half the rows. Create a widget that filters for DimB.Name=<some name> and DimC.Type=1. Use SQL Profiler to find the query your Live Model runs. Run the query; it should take over a minute or time out. Then change the "Where FactA.ID_B IN (Select ID_B From DimB Where DimB.Name IN ('<some name>'))" to instead be "Where FactA.ID_B IN (<copy paste the ID of <some name> here>)". It should run much quicker. The original query might run quickly without change, depending on server settings; if so, mess about with more complicated joins or ask me. In my setting key queries were reliably slow. ... View more

A nice feature in Microsoft SQL Server is the ability to see multiple data sets from queries in stacked windows. Currently only one query can be executed at a time and only display that one query's data set. It would be nice to be able to compare data by having multiple data sets appear at the bottom. Currently I have to open multiple browser windows to compare values and it can get a bit busy. It would be nice to compare 2 or more queries in the same window. Select * from table 1 where id = 123 Select * from table 1 where id = 456 data set for id = 123 data set for id = 456 ... View more

Currently the box and whisker plot is not supported when using a live model. When the widget is created, it has an error and won't show any data. We would really like that to be supported on the live model. Article showing that its not supported: https://docs.sisense.com/win/SisenseWin/live-connect.htm ... View more

At the moment, you can do row filtering in a Data Model, by applying an enforced filter.  This works fine in simple scenarios. In my case, I have 150 different users who each need to be able to see only their own data.  So I have to add them one-by-one to the data model's "Data Security" area.  Not only that, I have to do this to 10 different cubes, so this will be a lot of manual effort to set up and maintain over time as people come and go. What I'd like to be able to do is define a custom attribute on the User record, like "Location ID".  I'd fill it in for that user, entering "12345" for a particular user record.  That User is also a member of a group called "My Restricted Group". Then, I could go into the Data Security section, add an entry for the Location ID filter, applied to "My Restricted Group", and reference the "Location ID" number.  Then the system would enforce it at runtime -- is the logged in user a member of "My Restricted Group"?  If so, apply a fiter on the Location ID field, and fill it in with the value in their User profile. Then I only have to maintain the Location ID value in their user profile once, and only need to apply that Location ID filter once per cube, not 150 times per cube. ... View more

I would like to be able to run a "lineage/dependency" report in Sisense. Something that will tell me for all the cube/live data sources: - Data source name - Type (cube/live) - Dates of the data model (created, modified, last built) - Data sources being referenced and type (web service, database, etc.) - Details of each data sources (SQL Server, servername, database name) - Tables or objects being referenced by those data sources It's important for managing the environment to know what we are using, or have an easy way to know what data sets/dashboards would break if a table's structure were changed in the database. ... View more

We would like to configure multiple data security rules on a live data source table. With the available APIs there is a constraint to set one rule at a time. Having an API that accepts a collection of multiple rules is desired for our use case since we have more that 18,000 rules to be set. ... View more

For now, dimensions are displayed to the dashboard designer in the alphabetic orders of the tables / columns names. I would like the datamodel designer to have the control over sorting / grouping the dimensions. Ex : 3 tables Address Number Street City City Zip code Country Country Currently : the list of dimension will contain 3 groups: Address / City / Country The columns in each will also be sorted by alphabetic order.  Expected : the datamodel designer will choose how he want these columns to be displayed, for instance, under one single group : Address Number Street Zip code City Country     ... View more

Sisense ElastiCubes are the biggest consumer of our snowflake credits because we have to build our cubes every 30 mins to keep data fresh in Sisense. It would be useful to have time of the day level control on scheduling the build. Like Build daily at an interval only between the hours of x and y or other cron based scheduling. cron scheduling would be great since it allows us to set build windows, not build as frequently on weekends, etc. This would immensely help with cost saving. How quickly is it possible to have such a feature? ... View more

Hi Team,  When we import a lot of files (CSV for example), we have to select each file one by one. Could it be possible to select a lot of files with one click ?  Best    ... View more

In my datamodel, I want to delete 10 tables with names ending with "MySpecialSuffix". So, I go to datamodel list view and search for "MySpecialSuffix". I click delete on the first table. But then it loses my filter. So I have to re-type my filter for each table I want to delete. ... View more

See here: https://community.sisense.com/t5/technical-troubleshooting/refresh-schema-error/m-p/23594#M195 Refresh Schema fails when you have tables from two different schemas. ... View more

When creating a new table in an Elasticube, the area to write code into takes up a fraction of the screen space. Please make the pop-up to write code for tables stretch across the whole screen so users can see more lines of code at once. Or make the pop-up window adjustable so we can move it to be as big as we like.  ... View more

We propose adding a valuable feature to our dashboard UI: the ability to export a comprehensive list of all data models, including both Elasticubes and live models. This enhancement is essential for efficiently monitoring model changes before and after Sisense upgrades. Presently, this process involves manual actions like taking screenshots or exporting a text file using 'si' commands, but it lacks the capability to export live models and essential metadata such as data model type, owner, last modification date, last publication date, activity, and size. By introducing export functionality in formats like CSV, users will be equipped to easily track and compare models, quickly identifying any discrepancies or replacements. This improvement will significantly streamline model management and ensure seamless transitions during upgrades. ... View more