KPI Software

the one thing i struggle is to create dashboard layouts as it requires a plan in advance to build dashboards. makes it slightly time consuming Review collected by and hosted on G2.com.

i am able to build complex dashboards for various business use cases. it is highly versatile and hence creating meaningful reports seems much easier and fun. Review collected by and hosted on G2.com.

One thing I dislike about Microsoft Power BI is that it can have a learning curve, especially for beginners who are new to data modeling and DAX. Sometimes performance may slow down when working with very large datasets. Review collected by and hosted on G2.com.

Microsoft Power BI helps solve the problem of handling and analyzing large amounts of data from different sources. It allows me to clean, transform, and visualize data in one place, making it easier to identify trends and insights. This benefits me by improving decision-making, saving time on manual reporting, and enabling me to create interactive dashboards that clearly communicate data to stakeholders. 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 P.L.T.V. Model stuff took me way too long to figure out. And like, there isn’t an obvious place to start, you sorta just mess around until something clicks and also, the benchmark setup is okay, but I think it could be 2 fewer steps. Petty complaint, but the default colors on all the graphs are awful, and I end up changing them all the time. Support answers very quickly, which is good, however - sometimes the response is “go check the Docs”, and the Docs… are a lot. Review collected by and hosted on G2.com.

We had all of our marketing data scattered across multiple locations and none of us were looking at the same number, which made our meetings a disaster. Now we have all of the information in one location, and the sales team and the marketing team are at least fighting over the same numbers, which is a victory. Automating the Dashboards means I am not building the same reports every week. Review collected by and hosted on G2.com.

I would like the agent to have a few different modes - like "fast" or "thinking" etc. Review collected by and hosted on G2.com.

Hex makes data analysis and dashboard creation much easier, eliminating the need for a data scientist. I can do it all on my own by guiding the AI agent, which finds, transforms, and presents data. 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.

The software can be expensive compared to open source analytics tools, making it less accessible for small businesses or startups with limited budgets. Complex installation and maintenance. Review collected by and hosted on G2.com.

SAS Viya simplifies data management and integration, ensuring accuracy with real-time data. It streamlines reporting and analytics tasks, eliminating tool-switching to improve workflow efficiency. 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.

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.

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.

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.

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.

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.

What I dislike about Databricks is that Auto Loader can become frustrating when source data changes frequently, especially if column names or datatypes shift without warning.

For example, a field like customer_id may suddenly come in as cust_id, or a column that was previously a string may start arriving as an integer, which can cause schema drift and break downstream processing.

I also find it inconvenient when schema inference is not fully accurate, such as when nested JSON or semi-structured data is read incorrectly, because it then requires extra manual fixes and maintenance to keep pipelines running smoothly. Review collected by and hosted on G2.com.

Databricks is solving the problem of building and managing data pipelines at scale without so much manual effort. It helps with reliable ingestion, schema evolution, and orchestration, so teams can process data faster and keep pipelines more stable even when source files change.

For me, that means less time spent fixing broken jobs and more time focusing on transforming and using the data. It also benefits me by making batch and streaming workflows easier to manage in one platform, which is especially useful when data keeps changing. 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.