Running a business is all about leveraging data. With the help of several tools, such as text analytics, even unstructured data can be arranged to provide some beneficial insights, although the process may be complicated to understand. So, what is text analytics, and can it help your business? Find the answers below. 

The Relevance of Text Analytics

The information conveyed through various media needs to be aptly utilized by machines. Text analytics, thus, help in extracting machine-readable information from unstructured data. It helps in creating data-driven insights for businesses. 

Text analytics can also use data extracted from customer surveys or written feedback and convert it into machine-readable data.

What is Graph Analytics?

Graph analytics refers to the analyses of data in a graph format using nodes and edges which represent data points and relationships, respectively. It provides several useful insights which can help with decision-making. 

At a glance, graph analytics helps convey valuable information about the relationships in the network, including many-to-many relationships.

How are Text Analytics and Graph Analytics Different?

Both text analytics and graph analytics can be used for unstructured information. However, graph analytics makes use of graphs to visualize the data, unlike Text Analytics which can make use of both graphs and reports.

Essentially, the difference between the two is the final representation of the data. Additionally, graph analytics can be completed much quicker than text analytics as it involves fewer steps. However, it is essential to remember that, for such cases, graph analytics may not be able to provide accurate insights.

Can You Combine Graph Analytics and Text Analytics?

Common queries like “what is text analytics,” “how is it different from graph analytics?” often fail to account for the fact that graph analytics and Text Analytics can be used together.  

Although graph analytics is on the rise, it doesn’t mean that it has to be the sole method for data analysis. Instead, information gleaned from graph analytics can be improved further using text analysis. 

Hence, it is not about finding out which method you should be using but figuring out how you can use both together to get the best results. 

How to Use Text Analytics and Graph Analytics Together

Text analytics is not just a simple process. It involves various steps, from text analysis to text mining and more. Language is ever-changing, and text analytics involve the unenviable process of understanding what people are trying to say. 

Here’s where graph analytics can come into play. With the help of graph analytics, companies can leverage actionable insights. Graph analytics can help visualize the different contexts and meanings of various words and thus create a network that explains text analytics data better.

Hence, using both text analytics and graph analytics is vital for businesses to help in understanding data. While these tools are helpful on their own, they can provide more useful information when used together. 

When asking questions such as “what is text analytics and “is it better than graph analytics,” the answer can never be simple. Each tool has benefits and shortcomings, so businesses must focus on figuring out how they can get the best of both worlds.