Rolling out data visualization at scale via Grow
Overall Satisfaction with Grow.com
Grow is used by MarketScale for all data visualization requirements, specifically KPI dashboards. These are deployed for every department and business unit at MarketScale, in addition to having a dashboard for each of our clients. Grow allows us to easily build and maintain KPI dashboards from hundreds of data sources, while making it easy for less-technical users to build metrics.
Pros
- Scalability.
- White-labeled option.
- Ease of use.
Cons
- Increase integration count, instead of scaling back.
- Better support on specific API issues.
- Continue advancing full dashboard filtering/grouping abilities.
Grow doesn't have as many advanced analytics features and other capabilities as some other 'dashboard' platforms on the market. Simply, if you want a tool for internal use only that has high-level analytics capabilities (regressions, completely custom visualizations, modeling), Grow probably isn't the platform for you. To put it another way, if you have a team of data engineers and scientists doing complex analysis, Grow might not make the most sense.
However, if you understand the value of data/visualization/dashboards, but lack some of those skillsets in your company, Grow might be the perfect fit. Not only is it incredibly scalable and reasonably priced compared to other market solutions, but their transform capabilities really stand out. They have many native data transformations that mimic SQL coding of a dataset, without requiring any knowledge of SQL. They've converted these transformations to easy-to-use tools in the platform, which are perfect for the less-technical user.
However, if you understand the value of data/visualization/dashboards, but lack some of those skillsets in your company, Grow might be the perfect fit. Not only is it incredibly scalable and reasonably priced compared to other market solutions, but their transform capabilities really stand out. They have many native data transformations that mimic SQL coding of a dataset, without requiring any knowledge of SQL. They've converted these transformations to easy-to-use tools in the platform, which are perfect for the less-technical user.
Comments
Please log in to join the conversation