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Comparing the Natural Language Interfaces of GenBI Solutions

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Thanks to the rise of AI, it’s getting easier to ask questions about your business data using your own words.

One of the main benefits of Generative AI (GenAI) is its ability to process and respond to questions in the user’s natural language. It’s ushered in a wave of business tools leveraging natural language solutions, most notably in the area of business intelligence (BI).

For BI solutions, in fact, being able to ask natural language queries is more than just a cool selling point. The need to compose your business questions in the form of database query code has been the biggest barrier to entry for self-service business intelligence (SSBI) tools, and it’s arguably the main issue that has prevented truly democratic access to business data insights.

The new generation of GenBI tools meld GenAI and BI capabilities to enable users to ask natural language queries and interact with data intuitively – and much more safely than sharing proprietary secrets with ChatGPT or similar platforms. Skills in data management, extensive knowledge of charts, and data processing expertise are no longer prerequisites for producing useful and reliable data visualisations that serve as a base for your business decisions.

Now all you need to do is to choose which GenBI solution to adopt. There are already multiple options from a whole range of different organisations, from GenAI-centric startups like Pyramid Analytics and Akkio to established BI category leaders like Microsoft and Yellowfin. Each offering has a different interface, different user experience, and a different set of features. How do you make a choice?

This article is here to help. We’ll look at the natural language interfaces of five different GenBI offerings, and see how their usability compares.

Sisense

In recent years, Sisense has emerged as a way for developers to offer a white-label, embedded GenBI solution to their customers. It can be integrated into apps, websites, and other parts of the business IT ecosystem. Data platforms can use its range of GenAI “building blocks” to create customised analytics chatbots for clients.

The platform responds to textual queries written in natural language, drawing on a large range of graphs and charts. Auto-generated narratives accompany the visualisations to help non-data experts to understand what they see, also helping data scientists to share insights more easily to various stakeholders.

Users can formulate their own questions from scratch, or utilise the solution’s AI-generated quick-start questions to get the ball rolling. Sisense includes elements for customizable, easy-to-build dashboards that can meet every user need. The only drawback is that the solution can be complex to set up and requires frequent updates, although that could improve once it’s out of beta.

Pyramid Analytics

Pyramid Analytics is designed to enable any business user to access data insights, even if they have no data management expertise. It’s possibly the only GenBI platform that accepts both text and voice prompts, and it can understand and produce relevant responses to even the most vaguely-worded questions. Pyramid’s language model integrations can improve and sharpen the way your query is processed, so you receive the answers you need, not just the ones you asked for.

With Pyramid Analytics, you don’t need to know which is the best format for your data; the platform automatically selects the most appropriate graph, chart, or report format. You can also ask for changes via follow-up prompts. Every visualisation is fully manipulatable and dynamic, so users can zoom in and out, and select subsets of data for further investigation on or off the platform.

The Pyramid platform develops contextual narratives that tell a data story in ways that are easier to understand and share. It integrates with any data source, multiple large language models (LLMs), and other business tools, and can be embedded into any part of your business ecosystem. This makes it easier to access data and share your insights.

Yellowfin

Yellowfin’s GenBI offering is designed to meet the needs of both expert data scientists and ordinary, data-clueless business users. Users can type natural-language queries and receive the visualisation that the platform identifies as the best match for their needs – or take a shortcut and use the Quick Charts option.

More advanced users can choose how to create a report, explore data more deeply, and edit and adjust the visualisations they receive.

There’s a risk that over time, this attempt to appeal to everyone could lead to a lack of focus, but for now, users are happy with the range of options. Yellowfin supports a wide range of types of charts, graphs, and other visualisations, with pre-built dashboards, insights in the form of “guided results,” and the ability to embed reports into any app or webpage. This makes it easy for anyone to combine reports and visualisations into a dashboard or data story.

Akkio

Akkio is a GenBI startup that’s geared primarily towards marketing users. It has an intuitive interface, responds to natural language text prompts, and doesn’t require any code knowledge, making it very easy to use. The results can be embedded into any third-party location, including Slack chatbots and custom apps and websites.

With Akkio, speed is a priority, so you can submit a text query and receive a chart, graph, or report within moments. There’s an astonishingly large range of different visualisations and data exploration methods – in fact, non-expert users can feel overwhelmed and unsure which is the best to use.

On the other hand, Akkio’s data source integrations can seem limited compared with some competitors.

Microsoft Power BI

Power BI is Microsoft’s new GenBI addition to its familiar suite of business tools. It offers a massive range of visualisations and can connect to hundreds of data sources. As you’d expect, it integrates natively with any Microsoft product, making it simple to embed your visualisations and reports into any Microsoft services.

However, it’s arguable that its biggest selling point is that it’s made by Microsoft. Dedicated Microsoft users will want to add it to their existing suite, but those who aren’t already committed might think twice. Its “Q&A” natural language prompts and AI data discovery capabilities are a little sluggish compared with some alternatives on the market.

You need some familiarity with DAX to maximise Power BI’s features, and you’ll need to add the Copilot tools to access full GenAI capabilities.

The Choice Is Wide for GenBI Tools

The broad competition in the GenBI market is good news for business users, because it motivates each vendor to keep improving their offering. GenBI platforms are still in their infancy, so you can expect to see usability and capabilities continue to grow over the next months and years. Choosing the right one for your business needs can be challenging. As you weigh up all the factors, make sure that usability remains at the top of the list.

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