Why You Need More Than Data Visualization Tools for Business Intelligence

Data visualization tools help turn complex data into intuitive charts, and enable faster understanding of key insights from large datasets. However, for most reporting needs, you need more than data visualization tools for effective business intelligence (BI).

For example, not everyone in a team may be technically proficient in SQL, or know how to consume data using charts, graphs and heatmaps. Assuming every user is able to glean insights from a visualization alone is risky when there's many more BI tools available.

In this blog, we cover the types of modern analytics capabilities you need from your BI and analytics solution today that compliment and enhance your data visualization usage.

Data visualization tools: A quick recap

A data visualization tool is a software that transforms raw data into a visual graph or chart. It helps you to easily understand complex information by simplifying the analysis process. Therefore, you can conveniently make data-driven business decisions.

Read more: What are embedded data visualization tools?

Why data visualization tools alone isn't enough for good BI

Data visualization tools can visually analyze large amounts of data. It is still used as the main method for data analysis. But there are plenty of capabilities offered in modern analytics and BI solutions, such as Yellowfin, which can compliment and extend the effectiveness of your data visualization and reporting efforts.

1. Contextual analytics

Contextual analytics refers to the direct embedding of a data analysis solution into the core workflow of your software. Traditionally, embedded analytics makes dashboards and data visualizations standalone modules of your application, which means users have to switch away from their transactional environment to use them. Contextual analytics goes a step further by delivering the required data (in your reports, dashboards, visualizations, etc) within the user interface and the transaction flow, helping make analytics (including your charts and graphs) become truly contextual and dynamic for end-users.

The seamless blend of analytics and transactions provides several key advantages. For example, it gives retail store managers instant access to daily demand forecasts and detailed visualizations of predictions within the same daily interface they use to process purchases, and provides an another option for creating shift schedules for upcoming weeks in graphical form, without having to switch away to another window to use.

In contextual analytics, charts, tables, and metrics effectively sit side by side with the transactional components of applications.  They bidirectionally communicate with each other. It enables the end-users to gain dynamic insights with just a single click. In this way, contextual analytics help you to make effective business decisions.

Does Yellowfin support contextual analytics?

Yellowfin supports contextual analytics. As a result, you can embed dashboards, automated analysis, and actions into your application’s core workflow. It allows you to seamlessly deliver analytics at the point of consumption. Therefore, you can empower the users with the necessary context and capabilities to support their decision makings.

See more: Yellowfin BI Suite

2. Data storytelling

Data storytelling is the concept of building a compelling narrative based on critical data and analytics. It’s the ability to effectively communicate insights using visualizations.

Can you explain to others how your business is performing by simply using the numbers in a graph? Obviously not. You need something more than a typical data visualization tool. With data storytelling, you can communicate a complex dataset more effectively, and convey key information through both visual and textual form. As a result, the audience can better understand important insights.

When used in the analytics solution, data storytelling can help you to add valuable context. You can use your data to create a compelling story, connecting a table of numbers with a interesting narrative of how you came to the data. It will allow you to emotionally connect with the audience. They will have a deeper understanding of your business. But more importantly, you can back up their understanding with data to make better business decisions.

How can Yellowfin help me with data storytelling?

Yellowfin offers narrative-building capability. It can help you to create compelling stories with data. It allows you to easily combine data and narrative. As a result, you can create intuitive, impactful, and data-driven reports and presentations.

As a business owner, you don’t want your audience to simply look at your company’s data. You want everyone to emotionally connect to your business. You want the data to be effectively explained and interpreted to the audience. With data storytelling, you can make complex information easily understandable for everyone. Therefore, the audience can easily get connected to the critical data.

Learn more: Yellowfin Stories and Present

3. Guided NLQ

Natural Language Query (NLQ) refers to an increasingly present self-service business intelligence reporting capability in modern BI solutions. It enables you to query data in your analytics platform by entering plain language requests into the user interface.

With NLQ, you can use your everyday language to find the necessary information for making business decisions. Simply type the terms or make a voice search. The BI tool will parse keywords and search relevant databases. Once the process is done, it will provide you with the result using a report or chart.

Let’s say that you use Google every day to find information. You type keywords in the search box. The search engine looks for information that matches your query. It provides the results with a set of answers.

Read: 7 Things About Business Dashboards You May Not Have Known

NLQ works in almost the same way. You can ask questions to the analytics platform in plain English. You will instantly get a response. It utilizes data modeling and machine learning technologies to parse questions for key terms.

NLQ helps non-technical users effortlessly find insights and make effective business decisions. They don’t have to spend time exploring dashboards and charts. Also, they don’t need to use any technical language, like SQL. Instead, they can make a query in plain English and instantly get the results. It can make their lives a lot easier.

Let’s say that your Sales team doesn’t have the skillset and time to pick up the relevant technical knowledge. How can they analyze data on complex reports daily? By using NLQ, they can effortlessly get the insights that they are looking for. In this way, it can simplify the process of data analysis.

Does Yellowfin support NLQ?

Yellowfin supports NLQ via its Guided NLQ capability. As a result, you can ask questions about your data and receive reports of your query. For example, you can ask the analytics platform to show you sales in terms of regions. You will instantly receive the information. Therefore, you don’t have to create any query using SQL. It can help you effortlessly perform any analysis.

Try it now: Yellowfin Guided NLQ