Dashboard Software

While Tableau is a powerful analytics platform, there are a few areas that could be improved. The licensing cost can be relatively high, especially for smaller teams. When working with large data sets, dashboard performance can sometimes slow down and require optimization. Improving collaboration features and simplifying some advanced calculations would also make the platform even more convenient for everyday users. Review collected by and hosted on G2.com.

I use Tableau to convert large datasets into visual insights, highlighting trends and metrics. It simplifies understanding complex data, improves decision-making, and allows exploration of insights without technical skills. It efficiently turns raw data into dashboards, saving report preparation time. Review collected by and hosted on G2.com.

When reports start getting bigger with many visuals, performance can sometimes slow down a bit. It usually works fine but you need to design the model carefully if the dataset grows.

Also, learning DAX properly takes some time. Basic reports are easy, but advanced calculations definitely require practice. Review collected by and hosted on G2.com.

Power BI helps us convert warehouse data into meaningful reports that business users can easily understand. Instead of manually preparing Excel reports every time, we now have dashboards that update automatically when the warehouse data refreshes.

This saves a lot of time and makes it easier for teams to track important metrics and trends. Review collected by and hosted on G2.com.

I think it would be beneficial for more very specific examples of conversational analytics scenarios done as demonstrations to be available to view. Other than that, the process of using Kyvos has been very smooth. Review collected by and hosted on G2.com.

We have a lot of very large and complex data sets to look at, and typical BI tools limit our ability to look into the data quickly. We needed a solution to look for insight through conversational analytics that was scalable and that had a good relationship with our business context. Kyvos was by far the best option available after looking through the other choices made available to us. The results have been that our teams have been able to get much quicker insight with greater accuracy through asking questions in the way we would normally ask other people. Review collected by and hosted on G2.com.

I think there could be more guidance for different types of API connections for popular platforms like Shopify, Google Analytics, and Tableau. It can take time to get everything set up correctly the first time with Knowi's platform and API documentation. Review collected by and hosted on G2.com.

I use Knowi to dashboard ecommerce performance, eliminating the need for manual CSVs and handling data beyond Google Sheets limits. It ensures my data is current, saves time, provides easy consumption, and the onboarding and support help resolve issues fast. Review collected by and hosted on G2.com.

The initial setup for GoodData is not for the faint of heart. Petty complaint: When something goes awry in the defining of a metric, the error message is usually so vague it may as well say, "Something is wrong - figure it out." Minor annoyance. Documentation varies based on what you want to do. Review collected by and hosted on G2.com.

We were having five different people build reports five different ways, and numbers never agreed upon during meetings. It also allows non-technical people to view their data without having to ask for help each and every time, thus greatly reducing back and forth communication. And for clients that require visibility into their own performance data, the ability to embed our reporting into their site eliminates us from having to create a new reporting solution for them. Review collected by and hosted on G2.com.

I'm very new to Sigma so I don't know enough yet to go into specifics but I'd love to have a better guide on best training sessions to watch online depending on specific use cases. More generally as a new user I'd love to have a specific enablement pathway or classes to follow. Review collected by and hosted on G2.com.

Sigma allows me to pull in data from various sources and visualize it on a user-friendly platform. It makes complex data tasks easy without coding, and I can link data via specific columns using input tables and calculated fields. Review collected by and hosted on G2.com.

I think Hex is still figuring out the enterprise use case in general. I tried to use Hex's semantic features, but even though it was supposed to be in my plan, I was not able to access it until very recently. So I think, in terms of the admin panel or the platform itself, there might be some issues here and there. However, I think the team is very responsive whenever you do have a problem. I've noticed that it's very difficult to export from Hex. I wish there was a cleaner way to export the data files from Hex. Review collected by and hosted on G2.com.

I use Hex for data analysis, and it's great for starting my research. The generative AI tools help consolidate results, separate noise from signals, and explain findings simply. Its self-healing properties and natural language threads enhance productivity without much intervention. Review collected by and hosted on G2.com.

Despite its solid reputation in traditional reporting, TIBCO Jaspersoft does have some hiccups when it comes to modern analytics. You might run into performance issues with large datasets and complex reports, which often means a bit of extra tuning is required.

When you stack it up against tools like Power BI and Tableau, Jaspersoft tends to offer fewer advanced visualizations, has less robust ad-hoc exploration capabilities, and doesn’t quite deliver on AI-driven insights. This can make it less appealing for organizations looking for rich analytics and speedy data discovery.

Clients often find themselves navigating report complexity and dealing with unexpected email failures when handling large datasets, which can complicate troubleshooting. These challenges are definitely something for product managers to keep in mind as they work to meet customer needs. Review collected by and hosted on G2.com.

Jaspersoft is your go-to for dependable, governed, and automated enterprise reporting, which is key for keeping your data accurate, secure, and distributed in a controlled manner. It makes generating those pixel-perfect reports a breeze with options for scheduling, email, and secure channels like SFTP, all while cutting down on manual effort and minimizing risk.

With its role-based access control and multi-tenancy features, managing user groups and customers becomes a walk in the park, all while ensuring compliance is top-notch. Jaspersoft acts as a solid, embeddable reporting foundation that scales effortlessly across various use cases and supports your long-term product roadmaps without needing extensive customization.

Oh, and we’ve just made the leap from Jasper 8.0.3 to 9.0.0! This upgrade has tackled a bunch of client issues and made the user experience even better. Review collected by and hosted on G2.com.

As a first-time user, I found a few areas where Yellowfin could be improved. Some of the advanced features were not immediately intuitive, and I needed to spend extra time experimenting to understand how to use them effectively. I also sometimes felt restricted in how much I could customize certain charts and layouts—while it works well out of the box, making detailed adjustments to the appearance isn’t always simple. Overall, it’s a capable tool, but there is definitely a learning curve once you go beyond the basics. Review collected by and hosted on G2.com.

Yellowfin BI has enabled us to transform our ELR and Leave Administration case data into clear, actionable insights. Previously, much of our reporting was manual and reactive, making it difficult to keep up. With Yellowfin BI, we can now create dashboards and schedule reports that consolidate trends in grievances, corrective actions, leave volumes, turnaround times, and case outcomes all in one place. This centralized approach allows leaders to monitor workloads more easily, identify emerging issues sooner, and recognize opportunities for process improvement. Additionally, it has helped us standardize case reporting across the organization, leading to greater transparency and more informed decision-making. Review collected by and hosted on G2.com.

Regarding areas for improvement, I do have a few ideas.

I think the construction of frames could live in a separate canvas, similar to how Tableau approaches dashboards. This would offer the best of both worlds: plots would remain close to the queries that generate their data, while still allowing the creation of a dedicated dashboard that brings everything together.

There are also some smaller usability issues that can make the interface feel unintuitive at times. For example, when creating custom plots, individual marks cannot be named, which makes it harder to understand what each mark represents. Similarly, when multiple marks are used, it’s not always clear which variable is assigned to the secondary axis.

Some solutions also feel a bit hacky—for instance, adding vertical lines to indicate events by using bar plots, where it’s not always obvious how to control the bar width cleanly.

Overall, these are relatively minor points. They don’t slow me down in my day-to-day work, and I see them more as a wishlist than as real blockers. As with any tool, there is always room for improvement—but Count is already a superb product. Review collected by and hosted on G2.com.

Count solves the problem of fragmented analytics workflows by bringing queries, plots, text, and reviews into a single place, which makes analyses naturally self-documenting. This benefits me because I can always trace results back to their underlying logic and interpretation without losing context. It also addresses code duplication by allowing results to be referenced across tiles, in a way that feels similar to a DAG in dbt. As a result, I can break complex queries into clear, reusable components and iterate much faster.

Count also solves the rigidity of traditional dashboards by giving you control cells to define filters directly in the analysis. This gives me far more flexibility than organization-level filters and avoids the need for hacky workarounds. Another key problem it solves is reviewability: comments, interpretations, and feedback live right next to the data. That makes collaboration easier and decisions easier to justify.

Finally, Count reduces the risk of getting stuck with tool limitations thanks to a very responsive support team. Knowing that feedback is heard and often translated into product improvements makes me confident in relying on Count for my day-to-day analytical work. Review collected by and hosted on G2.com.

local data agent doesen't necessarily supoort the lateset JRE builds Review collected by and hosted on G2.com.

It helps us create a single source of truth for all of our disparate information sources. Review collected by and hosted on G2.com.

While SAS Viya is powerful, the transition from traditional SAS 9.4 can sometimes feel challenging, especially when certain procedures or workflows do not behave exactly the same way. Some advanced features require additional configuration or licensing, which can limit access depending on the setup. In addition, for new users, the interface and ecosystem can feel a bit overwhelming at first, particularly when navigating between different applications (e.g., Visual Analytics, Model Studio, programming). A smoother learning curve and clearer guidance for users migrating from earlier SAS versions would be helpful. Review collected by and hosted on G2.com.

SAS Viya helps solve the challenge of analyzing large, complex datasets efficiently while maintaining reproducibility and transparency. It provides scalable computing power, which is especially valuable when working with mixed models, high-dimensional data, or collaborative research projects. The integration of visual tools with programming also streamlines the workflow from data management to modeling and reporting. For me, this improves efficiency in both research and teaching, allowing me to demonstrate advanced methods clearly while handling real-world datasets more effectively. Review collected by and hosted on G2.com.

It does what it does great, though I'll still use Colab for my own personal work as I find it easier to get going quickly, whereas Deepnotes strengths lie with collaboration across a team. Review collected by and hosted on G2.com.

The key one being collaboration across the team is far easier with Deepnote than Colab, which unlocks greater insights that can be presented more professionally and shared easily. Review collected by and hosted on G2.com.

In general, there’s nothing I particularly dislike. A native Hyperline integration would be great, but that’s more specific to our tech stack and needs. Review collected by and hosted on G2.com.

Top of Funnel Visibility and getting Insights into our Pipeline Metrics. We look at the Equals Dashboard every single morning! Review collected by and hosted on G2.com.

Very little at this point. We experienced some initial performance challenges with dataset linking at large scale, but the Luzmo team responded proactively with a comprehensive solution in development (expected Q1 2026). The communication and support throughout has been excellent. Review collected by and hosted on G2.com.

Luzmo solves the challenge of providing embedded, white-labeled analytics dashboards for our multi-tenant SaaS platform serving enterprise supply chain clients. Rather than building a custom BI solution from scratch, Luzmo provides production-ready embedded dashboards that integrate seamlessly into our application while maintaining strict data isolation between clients through account overrides.

The multi-tenancy architecture allows us to deploy the same dashboard templates across multiple enterprise customers while ensuring each client sees only their data. This significantly accelerates our time-to-market for new client onboarding and reduces development overhead.

Luzmo enables us to deliver sophisticated forecast analytics visualizations—including complex metrics like wMAPE, Bias, and FVA calculations—without requiring our data engineering team to build and maintain a full front-end visualization layer. The Databricks connectivity allows us to leverage our existing data infrastructure while providing interactive dashboards.

The Luzmo IQ natural language querying feature adds significant value by allowing non-technical users to ask questions about their forecast performance data conversationally, reducing the need for custom reports and training.

Overall, Luzmo allows our small team to deliver enterprise-grade embedded analytics to multiple Fortune 500 clients without the engineering resources required to build a proprietary BI platform. Their team has been highly responsive to our scaling needs, with a new Databricks connector in development to further improve performance. Review collected by and hosted on G2.com.

It is not very efficient for non-Google products and sometimes it's paid for certain platforms. Setup is easy though it takes time especially when I need to blend the reports. Review collected by and hosted on G2.com.

If you are looking for data analytics tool for your enterprise then looker could be a good option as it is cloud based tool which can be accessed from anywhere. Also it's very straightforward yet powerful... Review collected by and hosted on G2.com.

Looker creates dynamic, live reports for Google digital ads that can be shared easily with clients and managers, streamlining workflow. Review collected by and hosted on G2.com.

Only constructive feedback I have is I wish there was a way to have data update immediately, but I don't foresee a workaround since this platform pulls data from outside software, and response times between the two will never be fully succinc - just the nature of the beast. Review collected by and hosted on G2.com.

Reporting, data analytics, real-time audit of employee budget, time entries, etc. Review collected by and hosted on G2.com.

They don't yet have support for Iceberg or Delta Lake tables, which has become increasingly important for some of our customers. Review collected by and hosted on G2.com.

Reveal provides embedded dashboards enabling our users to produce custom reports specific to their needs, without having to engage our team in custom development. Additionally, Reveal enables us to put our application data in the hands of data scientists, allowing a richer understanding of the data within our product. In total, we will save time as a development organization and our customers will save time as well dealing with custom reports. Review collected by and hosted on G2.com.

The Salesforce integration is not very self serve yet, needs some product development. Review collected by and hosted on G2.com.

Censys needed a faster, more efficient way to track cohort funnel conversion rates and report marketing metrics. Manual reporting was slow and fragmented, making it difficult to see how leads progressed over time. With Discern, we automated our cohort funnel reporting, reducing reporting time by 87% and gaining real-time insights into marketing program ROI. Leadership now has instant visibility into conversion rates, enabling faster and more informed decisions. Review collected by and hosted on G2.com.

If I had to nitpick, the initial UI for the truly deep engineering stuff can be a little much for new users, but once you get past the initial setup (which is covered well by Customer Support and training), the daily use is very intuitive. The Interactive Sessions feature is also amazing for cutting down on Spark job startup time, making my day-to-day work way more efficient. Review collected by and hosted on G2.com.

ILUM solves a few major headaches that were common in the big data world. The main problem is fragmentation—trying to stitch together separate, expensive data lakes and data warehouses, which leads to messy data silos, inconsistent results, and a lot of unnecessary work. Older proprietary systems like Cloudera or Databricks are costly and lock you in. ILUM gets rid of those problems. It's an open-source based Data Lakehouse platform that unifies everything.

For me as a user, this translates to tangible benefits. First, it is much faster. The interactive Spark sessions eliminate those 20-40 second job start times, and processing can be up to twice as fast overall. This means I'm not waiting on the infrastructure; I'm actually doing my job. Second, it's cheaper and more efficient. The platform is zero-license, Kubernetes-native, and runs anywhere (cloud, on-prem, hybrid), which drastically cuts infrastructure costs—we talk about 60% savings for clients. That budget can go to actual development, not just licensing fees. Third, it provides clarity and governance with features like automated Data Lineage and a central Data Catalog, so I can trust the data's quality and know exactly where it's been. In short, it lets me focus on the challenging and valuable work of data science and analytics instead of wrestling with complex, slow, and expensive tools. Review collected by and hosted on G2.com.