Natural Language Query Simplifies Report Creation in DataSelf
Most of us are familiar with how to use “natural language query” (NL or NLQ) when performing a search on the internet. Type a few keywords into a search engine like Google or Bing and you will quickly find pages addressing the topic.
Now DataSelf Analytics supports natural language query to assist users building new reports and dashboards.
“People just type a question about their corporate databases in DataSelf, and a report is created instantaneously with the accurate answer they were looking for,“ said Joni Girardi, CEO of DataSelf. “For example, type in ‘what are my open receivables?’ or ‘who were my top 10 customers by sales in 2019?’ and the answers immediately show up in DataSelf. It’s that simple!”
Just like searching on the internet, if the information has been pre-mapped by DataSelf and is recognized by the NLQ engine, a new report is created answering the user’s questions. This framework empowers users to make more timely informed decisions, while freeing IT from working on many reporting requests. More complex requests not addressed by natural language can be addressed by users who go through proper DataSelf training.
Natural language query is a fairly new technology that leverages artificial intelligence (AI) and machine learning (ML). As users type their questions, the engine parses the words and offers options for answering the question. In the example below, the engine offers two ways to address the “Sales by Salesperson by Month in 2019” question, where Invoice Date = 2019 or a filter for Sales = 2,019.
By selecting the option with Invoice Date in 2019, the engine creates the following report. Users can easily change the visualization into other chart or text formats – the 2nd screenshot shows the text format.
Here are a couple more examples of questions and reports generated:
“Top 10 Customers by Gross Profit in Q3 2019.” On the screenshot below, the mouse hovered over the bar for Customer: OMICLI and that shows a popup window with further details.
“Sales by State by Year as a Map”. See below a map for every year, and the sales represented by the color legend.
We’re seeing clients benefiting from natural language query in different ways:
- Finding answers to ad-hoc questions.
- Creating and saving new reports to share with others, integrate into dashboards, or embed into their ERP or CRM systems.
- When analyzing an existing report or dashboard, users can launch the natural language engine to further investigate those data trends.
- IT teams have seen a reduction in report demand because users are more empowered.
DataSelf provides NLQ, AI, and ML powered by DataSelf ETL, MS SQL Server, Tableau and Power BI, and preconfigured templates that get the system up and running quickly. The solution can be extensively customized. And to make things easier, there are pre-configured templates to Acumatica ERP and CRM, Infor CRM, HubSpot, Microsoft Dynamics 365 ERP and CRM, NetSuite, Sage 100, Sage 300, Sage 500, Sage CRM, Sage Pro, Sage X3, Salesforce.com, and other systems.
Natural language queries in DataSelf help decision makers easily find instant and accurate answers to their questions. And that starts by asking questions in plain English.
Pretty empowering stuff, wouldn’t you say?
Guest blog written by Joni Girardi, CEO and Founder of DataSelf.