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In this blog post, we will compare the data analytics capabilities of NLSQL and ChatGPT-4o using the same dataset and questions. The dataset used for this comparison is an open dataset from the US Census, containing import-export trade balance transactions worldwide by product groups between 2008-2023.

We began by sending a CSV file containing the full dataset to the latest ChatGPT-4o model. The first question asked was, "What is Canada crude oil import last year?". ChatGPT-4o replied that there was no data for crude oil imports by Canada for the latest year in the provided dataset. However, this was incorrect, as the data was present in the CSV file. We then asked the same question to NLSQL.
NLSQL bot responded, "Thank you for your query. As per the data available, the import of crude oil from Canada to the USA was 92531.63 million USD in the last year." This answer …

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NLSQL Open Demo containing import-export trade balance transactions worldwide

In today's competitive business landscape, organisations must continually adapt and evolve to stay ahead of market trends and customer demands. One key strategy to achieve this is by leveraging advanced analytics tools and platforms to harness customer data, improve insights, and make informed decisions regarding product assortments, marketing campaigns, and operational efficiencies.

Data-driven decision making (DDDM) is the practice of basing decisions on data analysis rather than intuition or observation alone. This approach enables organisations to make more informed decisions, as they can identify patterns, trends, and correlations that might not be immediately apparent. By leveraging advanced analytics tools, businesses can gain a deeper understanding of their customers, products, and operations, leading to improved decision making at all organisation levels and a competitive edge in the market.

Adoption of artificial intelligence (AI) and machine learning (ML) in analytics: AI and ML technologies are becoming increasingly prevalent in advanced analytics tools, …

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Discover NLSQL use case for Retail

Artificial intelligence has been transforming industries across the globe, and the world of analytics is no exception. With the growing demand for efficient, accurate, and accessible data analysis, AI analytics as a service is emerging as a game-changing solution. In this blog post, we will explore how NLSQL, an innovative AI tool, offers a seamless analytics experience through its integration with Microsoft Teams and its easy deployment from Azure Marketplace. We will also discuss the pricing per API usage and how the self-service platform can be customised to cater to various use cases.

NLSQL is a cutting-edge AI tool that enables users to access and analyse data using natural language queries. By leveraging advanced natural language processing and machine learning algorithms, NLSQL simplifies data analysis, making it accessible to users with varying levels of technical expertise. With NLSQL, users can simply type their questions in plain English, and the AI …

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Try it out from Azure Marketplace

NLSQL is a powerful Natural Language Processing for data analytics tool designed to revolutionise the way Clinical Research Organisations (CROs) analyse and interpret clinical trial results. By leveraging AI-driven technology, NLSQL enables users to access and analyse complex data sets using simple, intuitive questions. This innovative approach to data analytics offers several key benefits for CROs working with Clinical Trials Results databases, including:

1. Enhanced accessibility: NLSQL allows users to easily navigate through vast amounts of clinical trial data by asking questions in natural language, such as "Show me subjects pie chart by Adverse Event Term" or "Can you provide subject count with at least one AE study-wise?" This user-friendly interface eliminates the need for specialized training in data analysis and empowers all team members to access the information they need.

2. Faster data analytics: By harnessing the power of AI, NLSQL can quickly process and analyse large volumes of …

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Download One Pager for Clinical Trials Data Analytics

The healthcare industry is experiencing an unprecedented influx of data, thanks to the rapid advancements in technology and digitalisation. The ability to analyse and make sense of this big data is crucial for healthcare providers to improve patient outcomes, streamline operations, and reduce costs. Natural Language Processing (NLP) is one such technology that has shown immense promise in transforming the way healthcare organisations manage and analyse their data.

The Intensive Care Unit (ICU) is a critical department in hospitals where patients with severe and life-threatening illnesses or injuries are monitored and treated. To ensure the best possible outcomes, clinicians must be highly vigilant and proactive in identifying potential complications and making informed decisions. The recently developed tool by NLSQL provides clinicians with timely and accurate information on potential downstream complications. In this blog post, we will explore how this cutting-edge technology can help doctors in early detection and mitigation of …

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Watch short video on how it works