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.
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!
Add a native connector and dialect for Dremio
We are using Dremio as a universal semantic layer to connect to several backend databases: PostgreSql, Oracle, HDFS, Snowflake. Using the Arraw flight jdbc driver allows the connection to Dremio, but often results in bad queries. I believe a custom dialect will be needed.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.Connection Tool - Programmatically Remove Unused Datasource Connections, and List All Connections
Managing connections within your Sisense environment can become complex over time, if there are a large number of connections, and connections are often added, and replace earlier datasource connections. In some scenarios unused connections can accumulate, potentially cluttering the connection manager UI with no longer relevant connections. Although unused connections typically represent minimal direct security risk, it's considered best practice to maintain a clean, organized list of connections, and in some scenarios it can be desired to remove all unused connections. Sisense prevents the deletion of connections actively used in datasources, safeguarding your dashboards and datasources from disruptions. However, inactive or "orphaned" connections remain after datasources are deleted or a connection is replaced, potentially contributing to unnecessary UI complexity in the connection manager UI. Connections can be of any type Sisense supports, common types include various SQL connections, Excel files, and CSV files, as well as many data providers, such as Big Panda. This tool can also be used to list all connections, with no automatic deletion of unused connections.
Coinbase Data Connector
Download: Coinbase Connector Introduction: This article will explain how to make a REST API connection to Coinbase's API Purpose/Benefits: This connector gives you the ability to pull in data about cryptocurrencies from Coinbase into your Sisense ElastiCube How to Install and Configure the Coinbase Connector: Step 1: Download the Connector and unzip the contents into your C:\Program Files\Sisense\DataConnectors\DotNetContainer\Connectors folder. *You may need to move your Rest dll file into the connector (replace the current one) - you can do this by going to C:\Program Files\Sisense\DataConnectors\DotNetContainer\Rest and copying the .dll to the Coinbase Connector Step 2: Restart the Sisense.Discovery and Sisense.CLRConnectorsContainer services on the Sisense machine Step 3: The driver has tables already configured for BTC, ETH and LTC You can add/remove depending what would you like to track: Step 4: Open the ElastiCube Manager, create a new ElastiCube and select the Coinbase Connector. Reference/Notes: Coinbase Website API Documentation
