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Search-Based Analytics In vizB

By |July 26, 2021 August 24th, 2022No Comments

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Introduction

Search-based analytics is a search engine for your company data where users can ask questions like “what was the total revenue last year “ or  “show me the sales by location” and get actionable insights like charts and tables.

Why is search-based analytics needed?

There are several data analytics or business intelligence tools available in the market where users must import the data and select the visualization and create a dashboard based on the business needs. Which would take hours or even days to create the dashboard which requires a data analyst or data scientist to create a dashboard.  Whereas in search-based analytics users can ask questions in plain English and get actionable insights and visualizations in a dashboard immediately.

Natural Language Processing (NLP)

NLP is used to convert human language into machine understandable language which helps the analytics search engine to understand the questions given by the user. Creating search-based analytics is complicated so that’s why search-based analytics are customized by the customer’s specific use case. This process often involves adding custom terms and synonyms to the NLP library, mapping relationships, adjusting variable names, and customizing the visualization selection logic.

How search-based analytics helps in vizB

When a new user in the company logs into vizB would not be aware of the static visualization available on the vizB dashboard and he doesn’t know where to find what he is looking for. So here is where the search-based engine comes into play as it would give immediate insights on what the user is looking for.

search-based analytics process in vizB

When the user gives the input question in English the text is mapped with the NLP library and converted into a text format that is accepted by the ln2sql module available in python. Then the ln2sql module converts the modified text to SQL query which helps to fetch the data from the database and finally the visualization is shown in the dashboard. Here the ln2sql codebase is updated and modified for vizB’s use case.

Conclusion

Here we have seen how vizB plays an important role in search-based analytics which helps in fetching data instantly and visualizing it based on user’s needs by typing simple questions in English.

Hari Prasad

Author Hari Prasad

Hari Prasad, an AI Engineer at DCKAP and a machine learning enthusiast passionate about cutting-edge technology, always curious about learning new tools, likes to participate in hackathons and to solve real-world problems.

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