How to Use NLP BI to Chat with Your Data

NLP-powered Self-service Analytics had guided Shane to get answers from data. And what Shane, a non-technical staff serving the sales department did was to type out a query in natural language to get an insightful answer to address his immediate need, without leaning on the expertise of technical personnel. The NLP-powered Self-service Analytics empowers every user, from technical, non-technical users to data engineers and data scientists. Anyone can ask questions and get relevant answers, and visualizations too. You can do away with the lines of codes, and find the shortest route to critical answers from data. As a non-technical user, you can type a question in natural language with the NLP fetching answers in the form of graphs, tables, and charts. NLP and NLQ powered Business Intelligence democratizes self-service analytics for every user, like the PowerBI Q&A, Tableau’s Ask Data, Simply Ask, Sisense’s Natural Language Query (NLQ) component, and Yellowfin’s NLQ self-service analytics making data and insights available to a wider group. How can you use the NLP BI tool for self-service analytics? In Logistics Converse, Ask On-time Deliveries, Get it Take this Logistics NLP-powered BI scenario. A user converses with data and uses simple language to reap the benefits of faster and better self-service analytics. That’s a key capability of NLP-driven search-driven analytics. The user can make an intelligent search and view trends related to one of its key metrics. How does the user leverage the NLP BI tool for self-service analytics? The user keys in the following question: Show me On-time deliveries for Dallas (for instance) for the month of December 2022. The NLP-powered BI tool comes up with a visualization chart and narrative that offers insight on the KPI. As a follow-up question, the user keys in another query. Show me on-time deliveries 2022 for Dallas vs On-time deliveries 2021 for Dallas. The NLP BI tool throws a graphical representation of the trend with respect to this Logistics metrics, which throws light on the improvements/Shortfalls with respect to on-time deliveries. Now, With the AI component of the tool combining with the NLP, the user can get insights beyond the ‘what’ of the ‘On-time delivery’ trend that can help take necessary actions to enhance On-time deliveries. Here’s another search-based self-service analytics scenario in Logistics that brings NLP to the fore. A trucking company uses Sensors and GPS for feeding monitoring data into its BI platform. As part of truck tracking, a user can key in this query. Show all trucks in Idaho. The NLP BI tool now responds with a map featuring all the trucks empowering the non-technical users to gain tracking abilities. BI Chatbot Assistant for Customer Service This BI chatbot is about to serve a customer service agent with critical data and insights. With the Bot integrated with the BI tool, the customer service agent queries the BI Chatbot Assistant to gather insights and address a customer complaint. And conversation with the NLP powered Bot begins when the agent querying the BOT about customer-specific details. It is where the Natural Language query (NLQ) in the search-based BI tool helps query the data and extract answers. Here are some sample NLQs that the assistant asks of the customer-related data.

• Tell me the number of issues faced by this customer in the last quarter 2022?
• Tell me the type of issue the customer faced?
• Show the resolutions provided to solve those issues?
• Can I get a graphical representation of the Issues and Resolutions for the last quarter 2022?

Now the Customer service agent is equipped with critical information about the customer before responding to the complaint. He comes to know that the customer has product upgrade issues earlier and also about the resolution provided to address the issues. With related historical insights about the nature of issues and resolution, the NLP-powered BI accelerates the agent’s path to resolution. All of this took minutes to go from the customer complaint to a resolution as compared to the hours of manual rigors it took to address the complaint. A Financial Institution cashes in on NLP to support regular monitoring This an NLP-powered ‘Chat with Data’ story. With both internal and external data about customers at hand, this bank leans on the Bot to chat with data and support risk analysis. The analyst keys in three different queries, relevant to his fact-finding drive.

• Tell me the total debt for all the credit cards used by Customer C
• Tell me Customer A’s total outstanding
• Show me Customer B’s late payment vs due date

With quick answers and visualization, the analyst augments his path to credit risk analysis. While the frequent need to extract insight and information is also well supported by the Bot integrated with the BI application. An executive at a Bank wants to gain insights into the Loan Performance, The executive turns to the bot for quick insights and visualizations by typing out these queries, for instance.

• Show me loan default by branch
• Show me loan approval count by branch

The Bot also serves the analyst in so many others, for instance, the analyst types the query as part of monitoring the liquidity risk.

• Show me the USD vs Euro exchange rate chart for the last 3 months

It just took minutes to gain required insights to support decision making. Healthcare & Smart Business Intelligence Bot

• Is there a Private Room to accommodate Patient A?
• Is the Doctor S available at 4.30 pm for patient (A) appointment?

The BI Bot provides with him key insights that empowers the staff to lay a course to an enriched patient experience. And the crucial factor that led to that experience is the ‘quick insight generation’ enabled by the NLP powered Smart Intelligence Bot. With AI joining hands with BI, voice assistants and bots have empowered users of all types to tap into self-service analytics and gain required business wisdom as when they want it. The future of NLP BI holds good with the user interaction with data and user experience about to reach a new high.