Create New Sample Data Sets with more data and more concurrent date ranges
Create a new sample data sets that have a lot more data, date ranges that are current to our dates today, has more scenarios that we see in all customers cases. Like more complex formula creations, displaying a wide range of different KPI's, have a more complex data model to show how dimensions and fact tables can work. Having a sample data set with custom code, custom tables, and custom column. Having one of the tables connect to a DW to show how the connection works as well.
SingleStore (MemSQL) Connector: Use CONCAT instead of Pipe operator (||)
The queries Sisense generates in some cases uses the pipe operator (||) to concatenate the strings. However, SingleStore has 2 different modes of treating the pipe operator, depending on @@sql_mode engine variable and PIPES_AS_CONCAT flag: flag is ON: pipe operator is treated as CONCAT and the Sisense-generated query works flag is OFF (default): pipe operator is treated as OR and the Sisense-generated query throws an error In order to avoid the ambiguity, I suggest that SingleStore (MemSQL) Connector uses CONCAT instead of pipe operator by default.
Preview table column in query builder
It would very helpful to be able to see the columns of a table in the Table Query section of the MySQL query build. Currently it just list the tables and you have to open another table then preview the table and scroll sideways to see the available column. You could create this in a tree view like SQL Sever does. This would help query writers by being able to see what columns belong to the tables, I included what SQL Server does for reference.
Different database connections on staging server vs production server
Hi, We have two cloud servers in Sisense: one for development (staging) and one for production. The staging server connects to our staging database. The production server connects to our production database. All cubes and dashboards are identical except for database connection strings and names. Our Git branching strategy follows these steps: Create a feature branch from staging. Make changes and push them to the feature branch. Open a pull request from the feature branch to staging. Test changes in staging. If approved, merge staging into master (production) to deploy changes. The Issue Git integration tracks database connection names, meaning both servers must either run on staging data or production data—this is not feasible for us. Proposed Solution We suggest implementing a decentralized environmental variable for storing database connections. For example: Use {database-server-name} as a placeholder in configurations. Set database-server-name = db_server_staging on staging. Set database-server-name = db_server_production on production. This would allow the same codebase to dynamically connect to the appropriate database without manual adjustments. Would love to hear your thoughts on this!Reusable/shared connection information for data models
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.Email Report Format - Add Excel support
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.Starred Filters visible to User or Group only
When using Starred Filters, end uses can create their own filter and save the selection for repeat use. However, any Starred Filter created will be visible to all users regardless of their Group or Parameter assignment. This is because these items are stored in the Data Browser as additional elements linked only to the data source and not to a user or group. As a result, this causes confusion, lack of control where one end users Starred Filters can be removed by another and concerns about data security. Appreciate utilising multitenancy would be a solution, however, this is not possible in all circumstances and requires a significant amount of additional administration. I am recommending a functionality change to control / limit the visibility of Starred Filters to the User or Group that created them.Here are some improvements looking for better usability
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
