Sisense Reviews

Our main use case for Sisense is across our business finance models in the financial and accounting departments. We use it to develop and redesign the information stored in our project management software and our ERP systems for our company. It gives us the prospect to consolidate everything in a single, easy-to-manage tool. Sisense reduces the time it takes to obtain complex reports from many different data sources and controls a variety of formats in one single tool that enhances our BI platform and our internal and external resources delivered to our end clients seamlessly.

A specific example of how I use Sisense for our finance models and in project management is that it is a very robust and powerful, very accurate tool that helps to connect a wide variety of standard and unconventional databases or data sources. With proper assessment before its deployment, it delivers amazing dashboards and business reports that can consolidate different data sources, hence becoming a useful resource for both your business and your customer.

The best features Sisense offers include that it is fast due to its In-Chip methodology. It uses great visualization. BI becomes easy with Sisense. Millions of data can be loaded in a few seconds, which did not seem possible with other traditional reporting tools. It has a robust architecture and provides REST APIs to access it externally.

That speed impacts my workflow significantly as it represents the greatest step and latest in the business intelligence market. It provides In-Chip technology for accessing millions of data in the shortest span of seconds and provides the best visual efforts for our business data to make data-driven decisions easily.

Sisense has positively impacted my organization as it reduces the time it takes to obtain an optimal return on investments. It delivers the instant analysis required to merge our financial numbers and statistics with a pretty accurate dashboard landscape. Hence, we are able to make data-driven decisions easily.

Sisense has improved our decision-making speed and saved my team, especially the data team, time. They are able to focus on more strategic other tasks because Sisense has done the work of providing analytics and deep insights where we are able to make data-driven analytics easily.

Sisense can be improved as the usability of the application on mobile devices needs some improvement, especially navigation and filtering. Dashboards that are created by multiple users can be a bit of a hassle to share by the admins.

I would also add that there is no proper metrics regarding dashboards, tables, use, and workloads, effects optimization, and schema size.

The web version of the ElastiCube Manager does not do everything that the desktop application does and should be improved.

I have been using Sisense for the past five years.

Sisense is very stable as I have not experienced any downtime.

Sisense's scalability is impressive as it can crunch a lot more data and has consistently better performance, so it is very scalable.

Sisense customer support is proactive and responsive.

Positive

I previously used a different solution before Sisense, which was Qlik Sense.

My experience with pricing, setup cost, and licensing is that it is cost-effective, but for smaller organizations working under a tight budget, this tool might be a bit expensive for them.

I purchased Sisense through the AWS Marketplace.

I have seen a return on investment with Sisense as it is a dashboard tool that is great. It is very appropriate for delivering summary or exceptional data in a fashion that is easy to digest. It makes it very easy for us to make data-driven decisions and we are able to forecast our future predicament or future plans, hence increasing or boosting productivity in my organization.

My experience with pricing, setup cost, and licensing is that it is cost-effective, but for smaller organizations working under a tight budget, this tool might be a bit expensive for them.

Before choosing Sisense, I evaluated other options such as Business Objects and SRC.

Sisense is one of the best BI tools that can load more data and has consistently no downtime compared to other modern BI tools. It successfully retains the best of the cube world and also provides the power of the modern In-Chip visualization engine, making it a highly recommended tool.

Sisense is very suited to rapid data mashup for massive data sets and self-service BI deployment with a very smooth user experience.

Sisense solves a major issue like lack of actionable analytics, where we mainly use it for tracking all our key performance indicators and optimizing our sales pipelines for the future.

Sisense helps us monitor performance metrics and make informed decisions quickly, and it also helps us in creating reports for better understanding. It helps us to build dashboards for sales, marketing, and operations easily.

It is excellent for creating interactive dashboards that non-technical users can navigate, and it is also great for handling our extremely large data sets. For example, in our marketing teams, large data sometimes leads to slower performance that is frustrating.

Customer support is straightforward and responsive, and data discovery is exceptional. Big data services are amazing and secure, and the easy integration of APIs is beneficial.

The in-chip methodology is very effective because it allows millions of data points to be loaded in a few seconds and processed, enabling us to make data-driven decisions through the insights gained.

Sisense has positively impacted my organization as it has been one of the best tools available. I believe this is true because of its effectiveness. Since we can connect multiple data sources, we are able to make data-driven decisions more easily, and we have improved our marketing and sales strategies.

Additionally, technical support does not easily remote into our instances if we are hosting ourselves to diagnose issues quickly.

Sisense could have better connections to digital marketing tools, but I understand they are working on that.

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.

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.

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.

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.

I have been using Sisense for three years.

Sisense has been stable so far.

Sisense's scalability is tricky; I would like to see more infra-scaling functionality for effective injection capacity and DR functionality.

I find customer support for Sisense to be good.

I would rate customer support an eight on a scale of one to ten.

I did not previously use a different solution before Sisense; this was a new attempt.

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.

The improvements I have mentioned are significant and pretty detailed.

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.

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.

I evaluated other options, although I was not present during those reviews, so I cannot specify the vendors.

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.

My main use case for Sisense is data analytics, as I work a lot with data, using Sisense for visualizing my data to do data reviews, data reconciliations, and vendor reconciliations.

For example, in my field, I work with data sets that have hundreds of thousands to millions of records, and to work through that data in an Excel file is a tedious job that requires VLOOKUPs and filtering every time I get a new extract. Using a dashboard, every time my data is refreshed, the dashboard is automatically refreshed, and then I have my data visualized. I can filter it, export it much better, visualize it much better, spot trends, identify anomalies, and do forecasting much easier than I would in tedious CSV or Excel files.

Sisense has impacted my organization positively because it is a service that I offer to my clients, as they don't have the technical abilities but want to look at the data, so I make it easier for them to look at the data.

For instance, my clients don't necessarily go into their EDC every day, and if they want to visualize the data, they typically have to export and build something in Excel every time, which isn't automated. Now, they can just go into their Sisense dashboard, look at the dashboard, and see the data immediately.

The best features Sisense offers are the ease of use, ease of building dashboards, and my ability to use different connectors to collate different data sources into one central place where I can wrangle and combine my data and reconcile and review it all in one place, making it much easier.

In my day-to-day work with Sisense, by importing data, I have automated my data ingestion with scripts that run daily to ingest the data, allowing my users to get up-to-date data every day. This makes it much easier than manually going to EDC systems, exporting the data, and manually importing it, saving a lot of time and ensuring no human mistakes because the automation is validated.

Regarding Sisense's AI capabilities, I think it handles data compliance very well, as it doesn't send my data around to the LLM, which is much more compliant with my industry's requirements. This ensures my data isn't used for training without my knowledge, making it much safer.

Regarding Sisense, the AI functionalities of the AI assistant are lacking compared to others, and I think they can work on that to make it easier to use and broaden the scope. At this moment, it is much more focused on finances, which if improved would be a big gain.

I believe they are working on it, so it remains to be seen what they will add. I know they value my input, so I provided many comments to see which ones they implement. While I won't mention everything, I think they are aware of the needed improvements.

As for the accuracy and reliability of Sisense's AI capabilities, I think especially for my industry, it is not there yet and still lacks context, which results in it not being that accurate. However, they are working on it, and with support from newer LLMs, I hope it will get better.

I have been using Sisense for about five years.

Sisense is fairly stable, as I don't have any issues.

Sisense is scalable, but the scalability comes at a price, particularly when scaling my Elasticube sizes.

Customer support is very good.

I rate the customer support a 10 because they are very good.

While I can't share specific metrics, I can say that I do see a return on investment because my clients pay me for services they can't do, and it speeds up my data reviews.

My experience with the pricing, setup cost, and licensing was that it was cheaper than the bigger competitors. Those competitors have a bit more functionalities, so I think Sisense is fairly priced. However, the downside is that all the additional plugins come with a price, which isn't ideal.

Before choosing Sisense, I evaluated other options including Tableau, Spotfire, and Microsoft's solution, though I cannot recall its name.

On a scale of 1 to 10, I would rate Sisense a nine.

I give Sisense a nine because the AI component just needs to be perfected. However, they are very close to doing that, which means a nine is close to 10 and is a good score.

Sisense is deployed in my organization via a private cloud. I use AWS and Azure.

My advice for others looking into using Sisense is to consider scalability and plan for it from the beginning to avoid surprises later on if you need more scalability and realize it comes at a price.

As a data engineer, my main use case for Sisense is building data quality dashboards and dashboards regarding company finances, performance, and competitor analysis.

A specific example of a dashboard I built with Sisense is a competitor analysis dashboard, where we scraped data from around 300 competitor websites. The purpose of the dashboard was to predict the revenue of our competitors based on the data we have using Sisense dashboard technology.

My main use case for Sisense includes majorly using it for data quality dashboards, and we were also using Periscope in Sisense to create SQL-based dashboards. This is primarily about quality dashboards, competitor analysis dashboards, and performance dashboards of multiple products.

Sisense has positively impacted our organization because we have been using it for quite a while, and it suits our budgeting needs while being easy to use, allowing new trainees to grasp it within a week.

The specific outcomes I can share regarding Sisense's ease of use include fast onboarding, as new team members can begin using it within their first week, which I find remarkable. It also enables us to maintain the integrity of the data while creating quality dashboards at virtually no cost.

The best feature that Sisense offers, which is why we used it, is that it gives us more control, especially the feature of using JavaScript while making dashboards, as in Tableau we did not have the same control over where we wanted each number or graph.

Using JavaScript in Sisense made a significant difference for our team because we wanted more custom dashboards for the CEO, whose requests were very specific, and we created interesting graphs that we were unable to do in Tableau and other dashboard tools.

I think Periscope is really underrated in Sisense, as it allows you to make really quick dashboards using SQL, especially advantageous for data engineers and analysts. The feature to add emails to get alerts on dashboards is really cool as well.

We were using Sisense ElastiCube in our system, which I found really cool because it had high performance with caching engines, making it ultra-fast for analysts to create dashboards for presentations to the CEO and other teams.

Regarding Sisense's governance and security, I find it to be really good, especially the authentication aspect, as I never felt insecure regarding my data being compromised.

I believe Sisense can improve by integrating more cloud capabilities and developing a built-in AI tool to help users build dashboards in real-time, which would make it easier and could increase profitability.

I think that more integration of AI would be a significant improvement, and while I do not have any issues with performance, Sisense has been delivering well in that area.

I have used Sisense for three years in my role as a data engineer.

Sisense is indeed stable.

I think Sisense's scalability is pretty good, as we have built many dashboards at various levels, and it efficiently handles a large number of users.

I have not reached out to customer support frequently, only two or three times, and I found them really useful and quick to respond.

We were using Tableau before Sisense, and we switched primarily because Tableau lacked custom JavaScript-based changes, making it too rigid and slow for our needs.

I believe the return on investment with Sisense is overseen by upper management, but I see that we use it daily for CEO reporting, indicating we are utilizing it effectively.

We evaluated other options before choosing Sisense, including Power BI, which had similar issues, leading us to prefer Sisense, which has been adopted organization-wide, allowing different departments to use it collaboratively.

I chose an 9.5 out of 10 because its performance is really good, fulfilling its claims, but with the growth in AI and agentic workflows, I see opportunities for Sisense to improve by incorporating more in-house AI features.

I advise others looking into using Sisense that it depends on your use case, as having it at an organization level is quite beneficial.

Sisense was used for one of our clients to enable analytics and dashboards for their applications, which were supposed to get the data from different partners for that specific client. Sisense is white labeled and provides white-label data analytics. It is very easy to use and, compared to other platforms, it provides many good features. It is built on a modern stack, so it really stands out. That is one of the reasons we chose Sisense for this particular project.

Sisense is an API-first embedded analytics platform, which is really good. We have gotten a lot of ease integrating this specific platform with any applications, dashboards, or websites that we want to develop. It supports ElastiCube in-memory models, which are performant, and it supports different types of data. It allows the user to cater to different use cases and is a very fast aggregator across different data sources, giving you the historical context and helping in operationalizing your data. It mainly allows you to do embedding and white-labeling, so that's one of the main features of Sisense platform.

Because of the API-first approach, the APIs are quite easy to use, allowing us to create customized dashboards. Some of the other platforms, such as Power BI or Tableau, can feel restrictive. Here, we already had a customized dashboard that was developed for the specific platform. Because this is an API-first or API-led analytics platform, it feels like a plug-and-play system, allowing more customization power to the client rather than just using one platform as a whole for analytics and dashboarding. Also, because of ElastiCube, we have more control over how the data is processed, enabling us to do a deep dive into the transactional data and review the historical data.

Sisense positively impacts our organization by speeding up the process of getting and presenting the data to customers or stakeholders, which normally takes a lot of time due to curation and presentation efforts. The turnaround time for the project is quite good. We are able to bring the data in front of the stakeholders quickly, which was one of the major achievements and met our expectations.

The turnaround time with Sisense improves by around 30 to 40%. The stakeholders are quite happy because, in the past, they were stuck with platforms that were one platform for all use cases. Therefore, the turnaround time and the features provided by Sisense are excellent.

Sisense has some limitations, especially in rendering tables or graphs. For example, if you want to perform custom sorting or searching based on multiple columns, that becomes quite tricky. Providing more control over how the data is sorted or filtered would be quite useful. Additionally, it could provide more connectors to integrate with emerging different data sources to exponentially increase the amount of data it can handle.

Sisense should provide more support for CI/CD, as we found the CI/CD approach quite limited, which is something that can be worked on. Some data scientists suggested more features can be offered by providing different models for data analytics.

Sisense can improve by adding more features for handling complex schemas and making the pricing straightforward. The dashboarding features are good enough, but additional features could make it even more attractive. Also, CI/CD support or source control support would be really helpful.

I have been using Sisense for around one and a half years.

Sisense is stable.

Sisense works really well for simple to medium use cases and scales well, but it may face challenges with very complex use cases.

Customer support is good enough.

Neutral

We previously used Power BI, but for this specific project, we were looking for a better fit. The client was open to different solutions and not restricted to a specific stack, so we evaluated other products such as Power BI and Tableau before choosing Sisense.

We have seen a return on investment because these kinds of projects typically require more developers to create dashboards and models. Sisense is easier to develop and embed within existing websites or applications, saving effort in terms of man-days or man-hours. Due to the data presented to stakeholders, they are able to make informed decisions that impact the day-to-day operations of the client, giving them more insights into what's happening within their organization.

I advise others to keep an open mind, as they'll be pleasantly surprised by how Sisense can help. It effectively allows analysts to create self-service portals or reports, saving time from a coding perspective. Because it's quite user-friendly, you don't need to be a hardcore technical person—you can create the dashboards yourself if you have sufficient knowledge, which works better compared to Power BI or Tableau.

Sisense is a quite useful product. In cases where there isn't a large requirement or many use cases, the pricing might not be justified. It's important to figure out how many use cases are present to assess whether the investment is justified.

On a scale from one to ten, I rate Sisense an eight.

My main use case for Sisense is creating dashboards, C-level dashboards, and data analytics.

I can provide a specific example of a dashboard we have created using Sisense. We have created many widgets inside the dashboard with numerous business rules for creating these dashboards.

The best features Sisense offers allow complete transformation. We monetize Sisense to our customers so they can transform it into their application, and it works as a native application. It does not look like a Sisense app. The build process is robust in Sisense, using the ElastiCube to store the data, and we can load as many widgets as possible. The visualizations are very good when compared to other applications.

Sisense has positively impacted my organization by drastically reducing the time taken to build the data cube, and we can see real-time analytics. The time taken to create the reports and dashboards has been drastically reduced by at least 40%.

I don't see any shortcomings in Sisense. The ElastiCube data processing should be improved. The build process is already efficient, but there can be slight changes when handling large volume data sets.

I give Sisense a nine because the integration with some third-party tools is good, but Sisense is not able to handle three-dimensional data.

I have been using Sisense for around one year.

Sisense is stable and robust.

Sisense's scalability is excellent. It is scalable to a very large extent and we can integrate any third-party tools.

The customer support is good. We typically get responses within 24 hours.

Positive

I previously used Power BI. When compared to Power BI, the visualizations are very good in Sisense, so we have moved to Sisense.

I have seen a return on investment in that we can manage the Sisense environment with a very small number of users. We can have only one admin and we can have as many users as possible.

My experience with pricing, setup cost, and licensing shows that pricing is a little bit higher when compared to other applications, but that justifies the use case.

Before choosing Sisense, we evaluated Qlik Sense, Power BI, and Bold BI.

My advice to others looking into using Sisense is that it's always good to integrate Sisense with their existing systems.

My company has a business relationship with this vendor other than being a customer; we are a partner.

I rate Sisense nine out of ten.

I was looking into some of our business operations with tow truck companies. I focused on evaluating turnaround times for tow trucks to arrive on-site for accidents and how long it took them to clear compared to other tow truck companies. Essentially, I was comparing responsiveness among different tow truck companies.

The Sisense solution was very easy to set up, and its visualizations were effective. Creating dashboards was straightforward and it didn't take long to understand how the tool works, making it intuitive. Additionally, it offers two ways to access data: by cubing the data or hitting it live. Using the last two cubes for data visualization made more sense for efficiency.

I would like to see an improvement in the live data connection, specifically making the process faster. 

Additionally, incorporating more self-service capabilities would benefit the product.

I have used Sisense for about a year.

There was no downtime reported with the solution.

I did not encounter any scalability issues. However, the Security appeared a bit cumbersome for maintenance.

During the process, I had a fully dedicated resource on my team, and I engaged with them twice a week. The support was very good.

I evaluated ThoughtSpot. Ultimately, I chose ThoughtSpot due to its superior self-service capabilities, despite Sisense having slightly better dashboarding.

The initial setup was very straightforward. As this was a proof of concept, I was able to access test databases easily.

There was no significant difference in pricing between Sisense and ThoughtSpot. They were practically dead even from a pricing perspective.

I also evaluated ThoughtSpot. Sisense had better dashboarding capabilities, but ThoughtSpot's self-service capabilities were the deciding factor.

For teams already using tools like MicroStrategy, which also use cubes, Sisense could serve as an easy transition offering more capabilities. 

I would rate Sisense an eight out of ten.

For the use case, the tool is mostly used from an analytic point of view. We are focused on huge data size because the last time we worked with the tool, it was very good.

Sisense is one of the best, and that is because of the product itself. Sisense can integrate with multiple sources at one time. If you have many databases, you might have CSV files, Excel files, or any kind of data files that Sisense can connect and wrap up everything in a single time. Another thing is predictive analytics. I would say that they are using a lot of AI features to advise the end user to understand the data, which is valuable. The tool gives us a lot more answers to help us understand many parts of the data.

I would say that using Sisense on Linux's platform might not be advantageous for everyone. I am more familiar with Windows than Linux. With Windows, the system performs very fast. Even if your data size consists of like 10,00,00,000 loads or whatever, it works very fast.

When using Sisense, it is better to have some people with a very good understanding of Linux. I need more technical people who understand about Linux OS. Only two people would be enough to operate the tool.

I have been using Sisense for four or five years.

I haven't mostly found any problems with Sisense, so I would say that it is a stable product.

Scalability-wise, it is a great solution.

The solution's technical support is good. I rate the technical support a nine out of ten.

Positive

The scalability offered by Sisense is better than what Board offers. In Sisense, the AI feature associated with predictive analytics is good.

The solution can be deployed in a day.

The solution's technical support is good. I rate the technical support a nine out of ten.

Fr return on investment, the tool probably saves a bit of time. It might not be good enough for the region I work in currently. The time-saving part can offer a lot after the installation or implementation is completed. After implementation is completed, it can help businesses in a more valuable manner.

The pricing is subscription-based and on a yearly basis.

Compared to Power BI or Tableau, Sisense is much more expensive. Suppose you look at the features provided by Power BI or Tableau. In that case, it includes everything, making it pretty hard to compare the pricing of Sisesne with others because of the structure of the pricing of the other products. There are tools like Power BI and Tableau that offer support, and its pricing model may look cheap. If you like to have the full feature set or functions, there will be a lot of similarities between Power BI, Tableau, and Sisense.

Normally, you have to maintain it by upgrading the product quite often because of its Linux component since it has a lot more things inside of it, like Kubernetes. The tool has a version of the Kubernetes, and it also has a lot of versions of the server, which is why the problem is you have to upgrade it frequently.

I rate the tool a nine out of ten.

We use the solution to centralize all processes.

Before Sisense, we didn't have a single platform to monitor our performance data. As a performance advertisement organization, we needed a place to monitor all performances. Sisense helped us achieve this by pushing our data into one place. Now, anyone in the organization can analyze any data point they need without looking at multiple locations.

It is easier to get on board with Sisense because of their custom support team. You have a dedicated team to help.

Sisense is good in terms of visualization, but it has some drawbacks. For example, it doesn't have any way to sort or filter tables directly on the server side. Also, you can't have multiple tabs; it has a single dashboard.

Sisense has multiple levels of filtering, including similarities. Sisense has a huge customer base and is constantly adding plugins, so it is possible to create tables the way you want.

I have been using Sisense for one to two months.

The product’s stability has no issue.

I rate the solution’s stability an eight or nine out of ten.

30 users are using the solution, and we are planning to touch 100users mark.

I rate the solution’s scalability a seven or eight out of ten.

We used multiple other solutions, including Google Looker Studio, Quicksight, Superset, and Google Sheets dashboards. We wanted to consolidate all data, so we switched to Sisense.

Migrating our data to Sisense was not easy since we were in a very busy period, and there were some issues during the first few months. This prompted us to look for a super site and other solutions. We were able to figure things out with the support of the Sisense team. It was a painful process, but we are happy with the results.
The deployment took around two months and four or five people to complete.

I rate the initial setup a three out of ten, where one is difficult and ten is easy.

The solution is not affordable for small businesses. It is cheaper for at least mid-stage startups to large scale. To get additional add-ons and plug-ins built by Sisense, we would need to purchase them as an extra package. There are also some extra costs associated with adding new profiles to Sisense.

I rate the product’s pricing a nine out of ten, where one is cheap and ten is expensive.

There are multiple stages of the availability. The first primary thing is cost. The second one is how large your data is and whether you want to research data in real-time or if it's frequency-based. There are much better solutions like Superset or Looker. If you look at consolidated data that refreshes regularly, like once daily, Sisense is definitely on the good side. It doesn't offer anything extra except for the good visualizations. Sisense is on top of the market. There is an associated brand value. If you want to share reports with the clients, that would also be easier.

We were evaluating Sisense, but the pricing was too high for us. We decided to try it and purchased an initial membership plan for 10 or 13 people. We worked directly with the Sisense team, but for a long time, we could not onboard our dataset. We explored multiple solutions, including onboarding a sample dataset first or directly catching the data through queries inside items. This is their primary KPI and USP - you can write questions in site settings and people. We tried to host this somehow, but all of our attempts failed. After multiple discussions, I could onboard the queries directly with the help of the support team.

We have dashboards all over the place. It was getting tough for us to track down where the information was. We needed a central location where all the dashboards are present. We were also hopeful that the AI features in Sisense could help us point to deeper insights that we cannot find ourselves all the time.

We were evaluating between Sisense, Superset, and Looker Studio. And I think Sisense is relatively fast compared to Looker Studio, for sure. Looker Studio also has some build problems, such as the inability to support custom queries. So, it's not a scalable solution for us.

One person currently does maintenance, but we are considering two or three for this job.

Overall, I rate the solution an eight out of ten.