Ask Your Data Questions in Plain English with Natural Language Query

Natural Language Query

There’s no question about it: the business landscape today is driven by data. And to make the right decisions, you need to get answers from your data quickly and intuitively. 

Traditionally, getting insights from data required having expertise in complex query languages and being able to navigate intricate dashboards.  

Now imagine if, to interact with your data, all you had to do was ask questions in plain, everyday language. And in return, charts and graphs were generated within seconds, providing you the insights in a visual and textual format.  

That’s what Natural Language Query does, and yes, it’s really that easy. 

The Power of Natural Language Query

NLQ is like having a conversation with your data; you ask questions, and the platform provides answers in a comprehensible and actionable format. 

If data analysis is the lifeblood of business, then Natural Language Query features are a beacon of its modern simplicity and accessibility. Found in a range of Business Intelligence tools, NLQ empowers everyone in your organisation to tap into the wealth of data. 

In this article, we’ll delve into what NLQ is and how it can revolutionise the way your business harnesses data.

Top analytics platforms Sisense and Power BI both boast powerful NLQ features that we will also be exploring in detail. 

Why Your Business Needs NLQ

Data Accessibility for Everyone:

NLQ opens the door to data analysis for everyone in your organisation, not just data experts. Now, business analysts, marketers, and decision-makers can extract insights effortlessly.   

Quick and Easy Insights:

No more sifting through dashboards or writing complex queries. NLQ reduces the time and effort required to obtain answers, enabling real-time decision-making. 

Reduced Training Overhead:

With NLQ, there’s no need for extensive training in SQL or data analysis tools. Your team can start querying data immediately, lowering the learning curve.   

Enhanced Collaboration:

NLQ fosters collaboration by enabling team members from diverse backgrounds to access and understand data without relying on data specialists. 

How Does NLQ Work in Power BI?

Power BI’s NLQ feature, also known as Q&A, supports a wide range of natural language queries. You can ask questions about your data’s dimensions, measures, and metrics. You can also ask questions about trends, relationships, and anomalies. 

Power BI’s NLQ engine is trained on a massive dataset of real-world questions, so it can accurately understand and interpret your queries. Here is how it works: 

User Input:

Set up Q&A in Power BI, where you can add field synonyms for the fields and tables in your data, and you can train Q&A to understand questions and terms that people may use.   

Startup:

Double-click on any blank space in your dashboard to fire up the Q&A engine. Type your question into the box.   

Data Retrieval:

The NLQ engine sends the structured query to the connected data sources, fetches the relevant data, and performs any required calculations. 

Data Visualisation:

The NLQ engine generates data visualisations such as charts, graphs, tables, or narratives to present the results of the query. 

How Does NLQ Work in Sisense?

Sisense’s NLQ feature, “Simply Ask” uses a combination of natural language processing and machine learning algorithms to understand user queries.  

Simply Ask is easy to use and can be accessed from any dashboard or report.

Here is how it works: 

Query Formulation:

You need only type a question in the Simply Ask bar on the top right side of your dashboard. For instance, you can ask, “Show me sales by region for the last quarter.” The Simply Ask feature will also display suggestions for questions you can ask from your data. 

Language Processing:

Sisense analyses the query, breaking it down into its components, understanding the context, and identifying relevant data sources. 

Data Retrieval:

The platform retrieves data from connected sources, applies necessary transformations, and generates a visual or textual response. 

Visual Presentation:

NLQ results can be presented as charts, graphs, or textual responses, depending on user preferences. You can interact with the visuals to further explore the day. 

This way, you can generate an entire dashboard of automated visuals from Simply Asking the right questions! 

Benefits of Adding NLQ to Your Analytics

Getting Started with NLQ

Implementing NLQ in Sisense or Power BI is a seamless process. Here’s how to get started: 

Integration:

Connect your data sources to your platform of choice. 

Training:

While NLQ is user-friendly, providing basic training on constructing effective queries can boost user confidence. 

Experimentation:

Encourage users to experiment with NLQ and explore their data to unlock insights. 

Want to Know More?

Ready to embark on a data-driven journey with NLQ? Contact us to learn more about integrating it into your analytics toolkit of choice and unleashing the full potential of your data. 

Amna Ahmed, Datore

Amna Ahmed

BI Value Specialist
Helping small & medium businesses harness their data like an enterprise – at a fraction of the cost with Analytics as a Service.

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