Sisense Fusion Analytics Platform | Ai-Powered Analytics
Embedded analytics has streamlined customer insights while data scaling remains a key improvement
What is our primary use case?
My main use case for Sisense during our three-year period involved a review, an implementation, and then a progression upgrade.
A specific example of how I used Sisense during that time is that we principalized it for the SaaS front-end platform, diversifying analytic dashboarding for our customer base and allowing them to use the relationships of the review products versus the actual outcome of the people who reviewed it and the analytics that supported that.
The key thing I want to add about how Sisense fits into our workflow is that we wanted to ensure the SDK packaging was flexible, which it is, and it has a solid API and SDK option package that we can work with for compatibility for our SaaS services, while also meeting our manpower requirements to drive costs down.
How has it helped my organization?
Reduced needs for additional hires was the biggest key component; we almost had zero cost spin-up outside the initial cost of the product package itself, and it was the overhead of manpower that mattered to us. Basically, to control costs, as we could not hire many extra resources, and the sustainment overhead was very low, allowing us to focus primarily on productivity rather than operational overhead.
What is most valuable?
The best features Sisense offers include ease of use and the ability to associate the API integration down to the dashboard, which made it a little less overhead for us to scale the product into our existing SaaS platform, along with the availability of professional services that helped to get our development off the ground.
The standout factors regarding the API integration and dashboarding for my team are that it can take standardized APIs that we have with JSON and other platforms, and it supports our writing of custom APIs, translating fairly well to the dashboarding process.
What needs improvement?
Areas where Sisense can be improved include AI integration, particularly effective deployment of the AI tool, rather than just having AI, and addressing the challenges around infra-scaling to support multi-cloud models instead of just a single cloud provider.
The needed improvements around scaling and AI integration include addressing the scaling functionality, particularly in disaster recovery, and enabling more effective synchronization or asynchronous functionalities with the DR services.
For how long have I used the solution?
I have been using Sisense for three years.
What do I think about the stability of the solution?
Sisense has been stable so far.
What do I think about the scalability of the solution?
Sisense's scalability is tricky; I would like to see more infra-scaling functionality for effective injection capacity and DR functionality.
How are customer service and support?
I find customer support for Sisense to be good.
I would rate customer support an eight on a scale of one to ten.
Which solution did I use previously and why did I switch?
I did not previously use a different solution before Sisense; this was a new attempt.
How was the initial setup?
Integrating Sisense with my existing data sources and applications was not difficult; I would rate it about an eight or eight point five on a scale of one to ten.
What about the implementation team?
The improvements I have mentioned are significant and pretty detailed.
What was our ROI?
I have not seen a return on investment in terms of employee numbers, but it has introduced a new potential source of revenue as a product we could integrate with our analytics tools for our customer base.
What's my experience with pricing, setup cost, and licensing?
Regarding pricing, setup cost, and licensing, the version six point three point one release was good initially, but I had to keep a close eye on costs, as it requires maintaining a tight format to avoid runaway costs.
Which other solutions did I evaluate?
I evaluated other options, although I was not present during those reviews, so I cannot specify the vendors.
What other advice do I have?
My advice for others looking into using Sisense is to ensure it fits your SDK guidelines, API guidelines, and is suitable for your customer-oriented goals rather than internal use. I would rate this review a seven overall.
Which deployment model are you using for this solution?
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Advanced Client Reporting That Fills the Gaps
Sisense is a great tool competent data analysis
Powerful Data Combination and Manipulation, in a Polished Package
Straightforward UI, Seamless Integrations, and Helpful Support
Developer-First AI Analytics That Makes Embedding in SaaS Easy
developer-first AI analytics
memory-heavy and slowness
Tenant level Customization
Sisense enables us to transform large volumes of farm, weather, satellite, operational, and supply-chain data into actionable insights for customers.