Developers
August 7, 2020

Google’s Data QnA Lets Business Access Data Insights Instantly Using NLP

Accessing the data insights now can be easier. Google’s s NLP interface for analytics, Data QnA that is based on BigQuery data, enables business users to simply ask a question on their company’s dataset, and get instant answers.

Today we will talk about Google Announcing Data QnA. What is it? you might question, it's a natural language interface for analytics based on BigQuery data. It's currently in private alpha, also known as pre-beta.

What does Data QnA do? It helps you enable your business users to get answers to the analytical queries through natural language questions.

By using QnA it’s easier for non-technical users to access the data insights needed through natural language. You can maintain the business's governance and security controls.

QnA is based on the Analyze system that was developed at Google Research. Analyze uses a method called the semantic parsing. It analyzes and explores data using conversation. QnA enables anyone to analyze petabytes of data that are stored in BigQuery. Data can be used for many purposes such as chatbots, spreadsheets, and custom UIs.

Without this kind of service, most businesses request a dashboard report from the BI team and it can take from days to weeks, giving more work to the team that usually is already overloaded.

Self-service analytics

In this case, there is self-service access to analytics, without requiring to know the deep technical stuff, with the ability to improve productivity and business results. With QnA, you can put BigQuery data in front of the user. 

QnA is focused on one single thing: democratizing data insights for non-technical users. The self-service model we previously mentioned, is designed to speed up the speed of innovation, helping optimize the costs and allowing businesses to save capital and time, the two most important and most valuable assets. 

QnA not only allows self-service analytics for businesses but also federated data from Cloud Storage, Cloud SQL, and Google Drive. QnA is natively available through Google Sheets and BigQuery UI. Data QnA API is used to embed the service into other interfaces. You can also integrate QnA into Google Dialogflow.

With QnA, you can formulate free-form text analytical questions. There are auto-suggested entities while you type the question. The return of this input is an English interpretation and an SQL query. If the typed question is not clear, a message stating “What did you mean” pops up. Data Analysts can formulate SQL queries using natural language questions.  

QnA counts with a management interface designed for data owners. It allows business users to use the language they comprehend and commonly use. The majority of the time being English, and other languages available on demand.

QnA is available for BigQuery customers at no additional cost. All queries and storage are charged as per the BigQuery costs. You can access the Sheets through the Connected Sheets feature. Including G Suite Enterprise. 

QnA is available for BigQuery data in the US and EU. There are a couple of Google Cloud partners with whom you can work with. Accenture, Deloitte, EPAM, Mevenwave, SADA, and Wipro.

In conclusion, Data QnA has been announced by Google. It's a natural language interface for analytics. It's based on BigQuery data. It´s currently in the pre-beta stage, or private alpha. QnA helps you enable your business users to get answers to the analytical queries through natural language questions. With QnA, you can formulate free-form text analytical questions. There are auto-suggested entities while you type the question. The return of this input is an English interpretation and an SQL query. QnA is available for BigQuery customers at no additional cost. All queries and storage are charged as per the BigQuery costs. To round things up, QnA is focused on one single thing: democratizing data insights for non-technical users.

TagsGCPNLPNatural Language ProcessingBigQueryDataQnA
Lucas Bonder
Technical Writer
Lucas is an Entrepreneur, Web Developer, and Article Writer about Technology.

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DevelopersAugust 7, 2020
Google’s Data QnA Lets Business Access Data Insights Instantly Using NLP
Accessing the data insights now can be easier. Google’s s NLP interface for analytics, Data QnA that is based on BigQuery data, enables business users to simply ask a question on their company’s dataset, and get instant answers.

Today we will talk about Google Announcing Data QnA. What is it? you might question, it's a natural language interface for analytics based on BigQuery data. It's currently in private alpha, also known as pre-beta.

What does Data QnA do? It helps you enable your business users to get answers to the analytical queries through natural language questions.

By using QnA it’s easier for non-technical users to access the data insights needed through natural language. You can maintain the business's governance and security controls.

QnA is based on the Analyze system that was developed at Google Research. Analyze uses a method called the semantic parsing. It analyzes and explores data using conversation. QnA enables anyone to analyze petabytes of data that are stored in BigQuery. Data can be used for many purposes such as chatbots, spreadsheets, and custom UIs.

Without this kind of service, most businesses request a dashboard report from the BI team and it can take from days to weeks, giving more work to the team that usually is already overloaded.

Self-service analytics

In this case, there is self-service access to analytics, without requiring to know the deep technical stuff, with the ability to improve productivity and business results. With QnA, you can put BigQuery data in front of the user. 

QnA is focused on one single thing: democratizing data insights for non-technical users. The self-service model we previously mentioned, is designed to speed up the speed of innovation, helping optimize the costs and allowing businesses to save capital and time, the two most important and most valuable assets. 

QnA not only allows self-service analytics for businesses but also federated data from Cloud Storage, Cloud SQL, and Google Drive. QnA is natively available through Google Sheets and BigQuery UI. Data QnA API is used to embed the service into other interfaces. You can also integrate QnA into Google Dialogflow.

With QnA, you can formulate free-form text analytical questions. There are auto-suggested entities while you type the question. The return of this input is an English interpretation and an SQL query. If the typed question is not clear, a message stating “What did you mean” pops up. Data Analysts can formulate SQL queries using natural language questions.  

QnA counts with a management interface designed for data owners. It allows business users to use the language they comprehend and commonly use. The majority of the time being English, and other languages available on demand.

QnA is available for BigQuery customers at no additional cost. All queries and storage are charged as per the BigQuery costs. You can access the Sheets through the Connected Sheets feature. Including G Suite Enterprise. 

QnA is available for BigQuery data in the US and EU. There are a couple of Google Cloud partners with whom you can work with. Accenture, Deloitte, EPAM, Mevenwave, SADA, and Wipro.

In conclusion, Data QnA has been announced by Google. It's a natural language interface for analytics. It's based on BigQuery data. It´s currently in the pre-beta stage, or private alpha. QnA helps you enable your business users to get answers to the analytical queries through natural language questions. With QnA, you can formulate free-form text analytical questions. There are auto-suggested entities while you type the question. The return of this input is an English interpretation and an SQL query. QnA is available for BigQuery customers at no additional cost. All queries and storage are charged as per the BigQuery costs. To round things up, QnA is focused on one single thing: democratizing data insights for non-technical users.

GCP
NLP
Natural Language Processing
BigQuery
DataQnA
About the author
Lucas Bonder -Technical Writer
Lucas is an Entrepreneur, Web Developer, and Article Writer about Technology.

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