Sisense Fusion Analytics Platform

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.

Private Cloud

Amazon Web Services  (AWS )

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.

Public Cloud

Other

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.

What do you like best about the product?

I at first was new to the reporting world having zero exp in creating data cubes, creating widgest and putting data into a layout that looked presentable. Sisense came easy to me and if i ever hit a road block their site had loads of information to help guide me or their tech support was easy to schdule a meeting with so they could assist. My Customer Success Manager at Sisense Makhate always make me feel like a top priority when i reach out.

What do you dislike about the product?

Nothing. I find this product great and easy to use.

What problems is the product solving and how is that benefiting you?

I am able to pull in data from multiple different sources in order to generate reports for both company analytics as well as export reports to share with our clients that is easy to understand and be visualy appealing.

Recommendations to others considering the product:

This is a great tool and after spending some time learning everything it quickly becomes second nature.

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.

Public Cloud