Can AI Analyse Data?
The world is witnessing an unprecedented growth in data generation, and the ability to analyse this information has become vital for businesses and individuals alike. Artificial intelligence (AI) has emerged as a powerful tool for data analysis, and Natural Language SQL (NLSQL) is one of the many AI-driven technologies that enable efficient and effective data analysis. In this blog post, we will explore how AI, particularly NLSQL, can revolutionise the way we analyse company data.
Natural Language SQL (NLSQL) is an AI-driven technology that allows users to query and analyse data using natural language instead of traditional SQL code. This innovative approach simplifies the process of data analysis, making it more accessible to non-technical users who lack expertise in SQL or other programming languages. With NLSQL, users can simply ask questions in plain English, and the AI system will interpret the query, generate the appropriate SQL code, and return the desired results.
NLSQL leverages natural language processing (NLP) and machine learning algorithms to understand and interpret user queries based on structured data. For unstructured data you have to transform your unstructured data to structured by leveraging OpenAI API or Structurizer App in Microsoft Team. The main challenge of unstructured data to structured conversion is defining categories based on your business needs. Once categories are defined you can generate a new structured table based on previously unstructured datasets. Here's a step-by-step breakdown of how AI Qualitative Data Analysis works then:
1. User Query: The user submits a natural language query, such as "What were Walmart total sales for glass bottle CocaCola 330 ml in March 2024?"
2. API call for Query Interpretation: The NLSQL client Azure Marketplace app processes the query, sending it to NLP to SQL API.
3. The NLSQL AI system generates the corresponding SQL query based on the user's input, identifying the relevant keywords, entities, and context based on customisation prerequisites. It takes for 0.5 seconds for API response with SQL code and proper action instructions for NLSQL AI client app (generate report, build data visualisation, calculate business indicator, etc. )
4. Data Retrieval: NLSQL Azure Marketplace client App executes SQL query on the connected database, and the data is retrieved inside customer IT ecosystem.
5. Result Presentation: The retrieved data is presented to the user in a comprehensible format, such as a table, chart, or graph usually in Microsoft Teams App or any other chat interface.
AI-driven technologies like NLSQL are transforming the way we analyse data, making it more accessible and efficient for users of all skill levels. By leveraging natural language processing and machine learning, NLSQL simplifies the data analysis process, enabling users to obtain insights quickly and make data-driven decisions. As businesses continue to embrace AI, the potential for NLSQL and other AI-driven data analysis tools will continue to grow, unlocking new opportunities for innovation and growth.
