1. View all history of builds and its corresponding logs from the cubes. Because, I could not see the last build failure reason, if another build got started. I need to wait for another build to complete or fail. 2. View all history of changes and provide a way to revert as in Google docs for both the cubes and dashboards. Some times, if something went wrong, we should just be able to revert to the previous version and continue from there. 3. Provide a way to view the list of cubes in the queue waiting for the build. Also, allow remove or disable them for a period or rearrange the queue to build. This will help in prioritizing something manual on demand. 4. If a cube build fails due to the memory or other configurations issue, provide suggestions like what has to be changed and based on what before triggering another build. 5. Provide a page to derive the suggested the configurations like memory, cpu, timeouts etc by collecting details like 1. Number of cubes, 2. average cube size, max cube size, min cube size, or number of cubes by size range say <5g, <10G, <20G, <40G etc.., 3. Frequency of the build per cube etc.. 6. Provide a page to view all the slow running dashboards, slow running queries and some suggestions to improve it. 7. Some times, if a dashboard got changed and republished, it is not getting applied to all the users. Provide a way to view the version of the dashboard the user may view. 8. Between builds, if there is not much change in the data, Sisense build should go faster. Provide a way like one common place to build each table from other sources individually and keep it ready. From there, if we build say functional cubes, it should build in flashing fast using the locally stored data. I see the cubes are pulling the data faster from relational db but very slow from mongodb. Now, if we are pulling data from another sisense cube or from the source no big performance difference. 9. Also, I am not sure, if we are restarting the nodes, should we necessarily mark the cubes in queue as failed, instead adding back to the queue as it was before the restart and just marking the actual cube got failed should be good enough. More later .. Thanks, Muthusamy J ... View more

Currently, dynamic/parameterized datasets are not supported in BigQuery connections. You can parameterize the service account information, which is great, but it would be helpful to be able to use a parameter to swap the dataset in the BigQuery connection based on who's currently viewing the dashboard.   For reference, parameterized datasets and schemas are supported by other database engines: Azure Synapse MS SQL MySQL PostgreSQL Redshift Snowflake ... View more

Currently, the "Upsert" build behavior is only available for Build to destination. It would be great if we were able to utilize this feature in our Elasticube model where we are not building to destination. We have numerous tables containing created date as well as updated date that are attached to an id field but are unable to use the updated date field since this will bring in duplicate (or more) rows per id which we can not have. Ranking duplicates and filtering out is not a sustainable with the size of our datasets. The ability to look at the id and updated field would solve this issue without the need for a complex workaround in our data source (Big Query). Thank you! ... View more

It seems strange to me that each time I need to add another table to my model, I have to re-enter all the connection (or pick a recent connection). If i have 10 tables in my model, they all have their own individual connection information. If a server name ever gets renamed, it'll be a crazy headache for us. There should be a place where you define the distinct list of actual database connections (one per server or database), give it a name, apply security, etc. And then when you go to add a table to a data model, at that point you pick from the previously defined available list of connections. ... View more

For users who wish to receive their Dashboard contents using the Subscription service, Sisense supports embedded emails or PDF format only. For convenience and expedience, I would like to see support for users to receive compatible Dashboards (e.g. Pivot Tables) directly as an Excel attachment. This will help for users who wish to receive regular emails containing important data in Excel format for integration with other systems.  ... View more

At the moment, the caching period of live models is set for the whole instance which removed flexibility where you'd want the caching period to be different for exceptionally large models.  For example, we have a table we have to ingest via a live connection as it is too big for elasticubes - but wouldn't want the caching period for this live connection to be too "low" as it would cost a lot via AWS.  However, we would want a low caching period for low latency reporting ... View more