Full-stack Web Developer at a tech services company with 51-200 employees
Real User
Top 5
2024-07-12T11:58:31Z
Jul 12, 2024
The SQL editor (SQL-Lab) is good to use when we don't have our own editor or when you want to try something fast. Apache Superset is easy to use because you can visualize everything with wizards. Overall, I rate the solution a nine out of ten.
It is a good visual solution tool in an open-source category. Our customers want to improve the business into a SaaS model. They analyze the telecom-based transaction data with SaaS, including the number of subscribers, usage of 4G and 5G networks, etc. The platform improved data analysis for our customers by providing a visualization library. We can drag visualization graphs to create weekly sessions. There is no need to implement any extra coding. It has no code interface allowing us to track the dimensions and measure the canvas. It automatically generates the chat once we select the graph. The most efficient features are data set creation and data manipulation. We can directly use the raw data table and summarize it dynamically by processing the data manipulation window. SQL Editor enhances the data scoring process, helping us write queries directly during dashboard discrepancy issues. We can store the query for future analysis as well. It enables a customizable integration with other data sources. The main benefit of using the product is the ability to access the data source without using any coding. Any user can create reports easily with minimal training. I recommend Apache Superset for customers who are considering open-source vendors. I rate it an eight out of ten.
Chief Manager at a computer software company with 5,001-10,000 employees
Real User
Top 10
2023-01-17T15:19:32Z
Jan 17, 2023
I rate this solution eight out of 10 because there could be some improvements in the commercials similar to what Tableau or Power BI offers. The advanced use cases aren't documented well and it does not have an intermediate cashing layer that can split up queries. Superset puts that entire responsibility on the domain user. I recommend this solution if you have a well-versed development team in Python.
Superset is fast, lightweight, intuitive, and loaded with options that make it easy for users of all skill sets to explore and visualize their data, from simple line charts to highly detailed geospatial charts.
The SQL editor (SQL-Lab) is good to use when we don't have our own editor or when you want to try something fast. Apache Superset is easy to use because you can visualize everything with wizards. Overall, I rate the solution a nine out of ten.
Overall, I rate the solution an eight out of ten.
It is a good visual solution tool in an open-source category. Our customers want to improve the business into a SaaS model. They analyze the telecom-based transaction data with SaaS, including the number of subscribers, usage of 4G and 5G networks, etc. The platform improved data analysis for our customers by providing a visualization library. We can drag visualization graphs to create weekly sessions. There is no need to implement any extra coding. It has no code interface allowing us to track the dimensions and measure the canvas. It automatically generates the chat once we select the graph. The most efficient features are data set creation and data manipulation. We can directly use the raw data table and summarize it dynamically by processing the data manipulation window. SQL Editor enhances the data scoring process, helping us write queries directly during dashboard discrepancy issues. We can store the query for future analysis as well. It enables a customizable integration with other data sources. The main benefit of using the product is the ability to access the data source without using any coding. Any user can create reports easily with minimal training. I recommend Apache Superset for customers who are considering open-source vendors. I rate it an eight out of ten.
The solution does not require a lot of maintenance. I rate Apache Superset an eight out of ten.
I rate this solution eight out of 10 because there could be some improvements in the commercials similar to what Tableau or Power BI offers. The advanced use cases aren't documented well and it does not have an intermediate cashing layer that can split up queries. Superset puts that entire responsibility on the domain user. I recommend this solution if you have a well-versed development team in Python.