Dashboard Software

The main thing I dislike about Tableau is that it takes some time to get comfortable with it. When I first started using it, some of the advanced features and calculations were a little confusing. I also feel that dashboards can become slow when I work with large amounts of data. Apart from this, I find Tableau quite useful for my regular reporting and analysis work. Review collected by and hosted on G2.com.

Tableau is helping me convert raw data into simple and useful dashboards. Earlier, I had to spend more time going through Excel sheets and preparing reports manually. With Tableau, I can quickly see trends, compare data, and identify important information in one place. It saves me time and makes it easier for me to understand the data and share insights with my team. Review collected by and hosted on G2.com.

What I dislike about Microsoft Power BI is that its advanced features, particularly DAX calculations, data modeling, and complex transformations, can have a steep learning curve. Managing large datasets and complex reports can also affect performance. Additionally, licensing costs, workspace permissions, and sharing reports with external users can sometimes be complicated. Improving ease of use, performance, and licensing flexibility would make Power BI even more effective. Review collected by and hosted on G2.com.

Microsoft Power BI solves the challenge of consolidating data from multiple sources and converting it into meaningful business insights. It helps me automate reporting, create interactive dashboards, track key performance indicators, and identify trends more efficiently. Its integration with Excel, SQL Server, and other Microsoft tools reduces manual work, improves data accuracy, and enables faster, data-driven decision-making. Overall, it saves time, increases productivity, and provides better visibility into business performance Review collected by and hosted on G2.com.

Some configurations require a good understanding of compute resources, access permissions, and workspace settings. Troubleshooting slow jobs can also take time when data is skewed or transformations are not optimized. Monitoring compute usage is important because poorly managed workloads can increase cloud costs. Review collected by and hosted on G2.com.

It helps me to process data from multiple sources and transform it into a consistent format for downstream reporting. In an Azure environment, I can work with files stored in Azure Data Lake Storage, apply transformations using PySpark, and organize the results into bronze, silver, and gold layers. This makes it easier to implement data quality checks and maintain a repeatable ETL process. Review collected by and hosted on G2.com.

There’s a bit of a mindset shift in how you approach analysis. Instead of building queries from scratch each time, you rely more on the pre-defined models and structures.

Once you get used to that way of working, it actually makes analysis much more straightforward across the team. Review collected by and hosted on G2.com.

Our biggest challenge was working with large volumes of data without slowing down analysis. Queries used to get expensive and time-consuming, especially when multiple people were exploring data at the same time.

With Kyvos, we’re able to interact with data much more freely. It’s easier to explore trends, compare performance, and answer follow-up questions without worrying about query delays. Review collected by and hosted on G2.com.

I faced issue while trying to connect it with Cloud but now I read new version came with cloud native support. Review collected by and hosted on G2.com.

Transformation of data like cleaning, joining, and data preparation I am able to do with this tool and it is helping me for my daily job to medium transformations. Review collected by and hosted on G2.com.

The main challenge I’ve run into with Sigma is access and permissions. At times, it can take a while to get the right data sources shared with the right people, which can slow adoption for new users. That said, once access is configured properly, the overall experience is smooth, powerful, and easy to work with. Review collected by and hosted on G2.com.

Sigma is helping us centralize and govern our key reference data through the Reference Data Management app. Its write-back capabilities also let us push clean, standardized values directly back into our source systems. This closes the loop between analysis and operations, cuts down on manual updates, and helps ensure everyone is working from consistent, up-to-date data. Review collected by and hosted on G2.com.

I don’t see Hex currently addressing the downstream BI needs of users who connect to Tableau, get extracts, and load them into their environments as CSV or PDF files. I’d like to extend the Python libraries we use for coding so I can better extract data and carry it to the business. I also want to integrate Hex with Databricks and support version maintenance in the coding workflow. Review collected by and hosted on G2.com.

I use Hex’s workflow to work through data analytics problems on the business analytics side. Review collected by and hosted on G2.com.

Nothing. It is a great product for BI with a lot of chats Review collected by and hosted on G2.com.

We can now visualize information of our cubes that allows us to make dashboards near realtime in order to provide meaningfull information about call center usefull to take better decissions. Review collected by and hosted on G2.com.

What I dislike about Looker Studio is that it can become slow when working with large datasets or complex dashboards. Data blending and advanced customization can be challenging, and troubleshooting issues with calculated fields or data connectors is not always straightforward. Additionally, some features and integrations have limitations, making it less flexible for complex reporting needs. Improving performance, usability, and advanced data modeling capabilities would make it a more powerful tool. Review collected by and hosted on G2.com.

Looker Studio helps solve the challenge of analyzing data from multiple sources and turning it into meaningful, actionable insights. It allows me to create interactive dashboards, monitor key performance indicators, automate reporting, and share results with stakeholders. This reduces manual effort, saves time, improves data visibility, and supports faster, more informed business decision-making. Review collected by and hosted on G2.com.

Some corners of the UI/UX still have room to improve. A few of the admin and settings screens feel denser than they need to be, and there’s a learning curve in places. That said, they’ve taken big, visible steps over the last year—a refreshed dashboard UI, themes, and a much cleaner AI chat experience—and the trajectory is clearly moving in the right direction.

With AI, you still need to double-check the results, since it can sometimes get things wrong. However, they make it easy to validate during conversations that the AI has computed the right results. Review collected by and hosted on G2.com.

We moved to Knowi from a well-known cloud BI platform. The previous tool required pushing all of our data into its own store before we could visualize anything, which meant ETL pipelines to maintain, sync lag, duplicate storage costs, and our NoSQL data getting flattened along the way.

With Knowi, we unified analytics across all of our datastores without moving the data and launched customer-facing embedded dashboards much faster. Row-level security and secure embeds ensure each customer sees only their own data. The semantic layer keeps metrics consistent across every surface. And with the new AI and agentic capabilities embedded in our product, customers can self-serve answers that used to come in as support tickets and custom report requests, so our team can spend its time on the product rather than on one-off reporting. Review collected by and hosted on G2.com.

I find the SAS Visual Analytics application a bit rigid and would appreciate more flexibility. Review collected by and hosted on G2.com.

I use SAS Viya for data analysis and inventory management in my store, enabling efficient data handling with its data engineering tools. Review collected by and hosted on G2.com.

In terms of customizing the visual presentation of the dashboards, there is some room for improvement. There are times when I wish I had more flexibility in terms of format when I have to prepare risk reports for our insurance partners. Review collected by and hosted on G2.com.

It addresses the problem of fragmented risk information. With standardized loss metrics, I get less involved with resolving any discrepancies between different claims reports and more with proactive risk mitigation in our production lines. Review collected by and hosted on G2.com.

The cost is high, and I also have to keep track of my credit usage. Review collected by and hosted on G2.com.

Domo solved our fragmented sales reporting problem. Key business metrics like quota attainment, run rates, new business performance, pipeline, and lease maturity used to live across multiple reports, systems, and personal spreadsheets, and gathering and validating it all took significant time. Quarterly Business Review prep alone took each sales manager 10-15 hours; that work is now largely eliminated because everything lives in one centralized, validated platform. Beyond time savings, the biggest benefit is better decision-making: managers identify at-risk opportunities sooner, adjust forecasts throughout the month instead of waiting for quarterly reviews, and use the data to coach their teams week to week. Forecasting accuracy, customer retention conversations, and overall business visibility have all improved. Review collected by and hosted on G2.com.

I'm not sure there's much that I dislike, necessarily, about using Lightdash. At least for my use case, their pricing model works well. They are on top of releasing features and whatnot. I don't think there's necessarily anything I dislike about Lightdash.

Possibly there are features that I personally wouldn't use, or that the organization that I'm in may or may not need, but I don't think that's a reason to dislike it. I can't really think of any reason to dislike Lightdash. For us, it really has just always been helpful, and they provide an array of options in terms of, I suppose, data maturity.

What I mean by that is that, at times, folks wanted to write code, complete, entire React-based apps on top of data. They have data apps to possibly help with governance if that is the flavor. Dijour, Claude dashboards came out. They were able to match or integrate with that. For you, they have something around a semantic layer, and they have something around more standardized visual components for building dashboards.

This is really turning into "what I like about Flydash," and not a whole lot to dislike, I would say. Review collected by and hosted on G2.com.

I already discussed previously, but Lightdash is solving, I think, the problem, an underlying problem with BI: maybe the categories, dashboards, BI, or semantic layer, what have you. I think where they sit in the problem space or the solution space is that, for the Orderful data ecosystem, they are bridging data and the data consumer. I think that is maybe the spirit of what people typically describe as BI: what that's trying to solve.

I can say that they're trying to solve that. Thoughtfully, how that's benefiting us is that they keep coming out with an array of options that I can kind of just pull on when I need to. For example:

- Data apps for people who want to vibe code entire applications on top of data semantic layer options.

- Agentic analytics, when there's a use case for that.

- Integrating with Claude dashboards when that's the surface that people interact with.

I think another problem that is just generally widespread across the industry right now is just many interaction points, agentically, for both humans and agents. I think they're providing a solid amount of coverage over the sort of whack-a-mole kind of problem space that we're sort of dealing with, where people want to do more, do things more quickly, and have nothing stand in their way. They're providing people kind of a little bit more of a golden path with governance, but at the same time making it still easy for them to do what they want to do. I think that's what Dash is trying to solve. 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 succinct - 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.

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.

local data agent doesn't necessarily support the latest 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.

User interface-Some users feel the UI has aged or become cumbersome. For example, complaints about “inconvenient UI changes” in newer versions.

For non-technical business users (who want fast dashboards/visuals) the experience may not be as smooth as some more modern BI tools. Review collected by and hosted on G2.com.

Data silos and disconnected tools

Slow, manual decision-making

Limited collaboration between finance, operations, and strategy

Difficulty forecasting or modeling “what-if” scenarios

Complex reporting requirements Review collected by and hosted on G2.com.

As I mentioned in my previous comment, the main issue I have faced with Jaspersoft is service stability. The services sometimes stop unexpectedly, and we have to restart them manually. This has happened multiple times, and we have also received similar complaints from our clients. It would be great if this issue could be addressed to make the services more stable. Review collected by and hosted on G2.com.

It is the perfect combo of publishing your reports as well as handling reports and scheduling reports. For a common man it is a one click task. Review collected by and hosted on G2.com.

The service provided by the cloud team is horrible. We are a paying customer, with an annual commitment, and are having big issues when scaling that are not being solved by them. We don't have visibility into what is happening. Review collected by and hosted on G2.com.

Cube closes the gap between our data model and business metrics, supporting complex metric design with a scalable semantic layer and a useful caching layer. Review collected by and hosted on G2.com.