Dashboard Software

Tableau’s UI/UX can feel overwhelming for a new user, mainly because there are so many options and configuration settings to navigate. The onboarding support within the platform also sometimes feels limited, which can make the initial learning curve steeper than it needs to be.

Overall performance is strong for the basic features, but it can degrade when using live connections to slower databases.

Ask Data–type features seem intelligently designed in theory, but in practice they feel somewhat lacking and immature. It often misinterprets natural-language queries, which ends up making the work more complicated than necessary.

Customer support is underwhelming as well, with slow ticket resolution times. It also leans heavily on community forums and predefined solutions, which can feel insufficient when you’re stuck in a specific situation that doesn’t fit the standard answers. Review collected by and hosted on G2.com.

It solves the fundamental problem of having data that is only viewed in spreadsheets, while the underlying databases are typically accessed and interpreted only by technical users. Tableau generates reports from this spreadsheet, and we can update them each round after verifying that the spreadsheet contains the latest data. Review collected by and hosted on G2.com.

It's a great program, but it's not perfect by a long shot. It can be complex when you start working with formulas. It lags at time when the datasets are a bit larger. Lastly, power queries can be confusing and hard to interpret and understand. Review collected by and hosted on G2.com.

It helps me pull everything, from Excel files, SharePoint, and emails, together in one place. It saves me a lot of time, and helps me with collaboration since everyone can see the same report at the same time, and it's updated in real time. 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.

One downside of SAS Viya is that it can have a steep learning curve for new users, especially those without a strong analytics background. Additionally, the cost can be relatively high compared to other tools, and some advanced features require extra configuration, which can slow down initial setup. Review collected by and hosted on G2.com.

SAS Viya is solving the challenge of handling large, complex datasets and turning them into actionable insights quickly. Before using it, we struggled with slow processing and fragmented tools, but now we can perform advanced analytics, forecasting, and reporting in one unified platform. This has improved our decision-making speed, reduced manual effort, and increased overall efficiency across teams. 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.

Notebooks can quickly get messy once you start creating a lot of cells in the same notebook, and it’s easy to lose your place while scrolling to find the cell you’re looking for. I’m not fully convinced by this Notebook and App partitioning, because it feels clunky and confusing in practice. For example, when you’re working with tabs, it’s hard to tell in the Notebook which cells are associated with which tabs. I also found it strange that the order of cells shown in the App is different from the order in which they appear in the Notebook. Finally, I’d like you to offer a native way to push data to a Google Spreadsheet, since that currently isn’t possible. Review collected by and hosted on G2.com.

It helps me quickly solve the data-related questions I run into every day as a Product Manager. I use it to track the performance of my funnels and features, which makes it easier to stay on top of what’s working and what needs attention. Review collected by and hosted on G2.com.

It becomes slow (noticeably) when trying to process larger than normal datasets which is very annoying. When exporting excel files they always appear unprofessional (sub-totals and grand totals all stacked up) and i would never send an exported file to a client without having to re-format it myself. Also, every single time you make a query you must wrap the column name(s) in quotes which may be a small pet peeve but it is certainly frustrating when doing it over and over again. Review collected by and hosted on G2.com.

Before we used good data, we pulled data from about 3-4 places and somebody had to spend hours compiling it, and it wasn't even always correct. With good data all of our data is in one location and reports reflect what is going on in real-time so we are no longer making decisions based off of last weeks number. Review collected by and hosted on G2.com.

Honestly I don't see any so far: If at all, it requires relatively high technical skill. It cannot be used effectively by a "plug-n-play" BI Analyst.

If the price is an issue, one can consider self-hosting. Review collected by and hosted on G2.com.

I started off liking Tableau as a BI tool better than PowerBI.

Then, I could see the compute downsides and missing git repo in Tableau compared to Looker.

Then, I can see the issue that Looker is very expensive and that Looker is not dbt integrated, i.e. you constantly need to maintain two disconnected repos and make changes in two places.

Lightdash is by far the best BI tool out there today. Review collected by and hosted on G2.com.

Gets a bit laggy when workbooks have a lot going on lots of elements, big datasets, that kind of thing. Some of the advanced features aren't super intuitive at first, you kind of have to figure them out on your own. Not a dealbreaker but could be smoother. Review collected by and hosted on G2.com.

We were spending way too much time building one-off reports for people. Now with Sigma, teams can build their own dashboards and trackers we use it for migration tracking, client project reporting, and internal operations tracking. The Snowflake connection was easy to set up and stays reliable, so everyone has access to real-time data whenever they need it. People don't need to come to us for every little thing anymore, saves a ton of time. 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.

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.

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.

Only thing that looker has to work on is sometime it feels like their dashboard is not responsive or taking too much time to load respective filters especially when loading large historical data and also each time we need to click on submit icon to get the filtered data which can be automated in future Review collected by and hosted on G2.com.

Mainly it helps on solving data silos and as recently they integrated LookML in their backend logic, all our data stays in organized and also helps to create data models and relationships with them so that we can just use already defined field without writing complex SQL query which helps to speed up my workflow Review collected by and hosted on G2.com.

In Delta Sharing, there isn’t a catalog-level SELECT permission, and I sometimes think having that would be helpful. Also, when I use the Genie code inside a VM, it can make the website unresponsive at times. These are areas that could be improved. Review collected by and hosted on G2.com.

In one of our claims-processing migration projects, the client needed near real-time data availability for downstream applications. Previously, the architecture used Amazon Redshift as the data warehouse, with Jasper and Sisense consuming the data for reporting and analytics. However, that setup didn’t support real-time or near real-time streaming efficiently, which led to delays in data availability for downstream systems.

After migrating the platform to Databricks, we were able to substantially improve the data pipeline architecture. We implemented streaming along with optimized ETL pipelines, reducing the data refresh cycle to about 30 minutes. We also created a dedicated view that retains data from the previous run, so downstream systems always have a consistent dataset available while the next pipeline execution is still in progress.

Before, we struggled with delayed refresh cycles and a limited ability to meet near real-time data needs in our Redshift-based architecture. After moving to Databricks, we enabled faster ETL processing and improved near real-time data availability.

As a result, we reduced ETL refresh time to roughly 30 minutes and enabled near real-time access for downstream tools like Jasper and Sisense. Reliability also improved because the stable view continues to serve the previous run’s data during pipeline updates. Finally, the overall architecture became simpler by consolidating processing and analytics capabilities within Databricks.

Overall, Databricks helped us build a more scalable and efficient near real-time data processing platform, significantly improving the timeliness and reliability of analytics for the claims-processing workflow. 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.

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.

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.

One downside of Deepnote is that it can feel a bit heavy for quick, simple tasks, especially if you just want to run a fast analysis without the full collaborative setup.

It really shines in team environments, but for solo, lightweight work, it might be more than you need. Review collected by and hosted on G2.com.

At pro-nutrition, it keeps everything, data, analysis, insights, in one place, so I can focus on understanding patterns and making better, more personalized recommendations. Review collected by and hosted on G2.com.

I don't know if it's a Google setting or Coefficients setting, but at times when I need a SF report to push to Gsheets, there are too many rows I think (it can't go higher than 50-60K it seems) which isn't helpful for me, because we have a lot of data.

I love the free T-shirt you sent me awhile back. The blue one. Can you send me a new T? I like repping the brand. Review collected by and hosted on G2.com.

Enabling the latest calculations and refreshes of our Salesforce reports populating external dashboards and resources used by our sales team, ops team and executive team Review collected by and hosted on G2.com.