An Informative Guide to Artificial Intelligence in Data Analytics

Data analytics is the process of extracting insights from observing and analyzing a collected dataset. Traditionally, several tools played their part in one or the other processes of data analysis. Apart from the tools, there are formulas that need to be applied to data and get understandable results from it. However, AI  in data analytics has changed the way it works. AI increases speed and accuracy, is capable of handling large data smoothly, and can utilize intelligence to provide helpful insights. Let us understand briefly about data analysis and the role of artificial intelligence in data analytics.  

How Does Data Analysis Work?


 

Data analysis is the process of analyzing data to extract information from it. When we use AI in data analytics, it is mainly utilized in the following 3 processes: 

Data Ingestion and Preparation 

Before beginning to analyze data, it needs to be collected, cleaned, and sorted. This process is called preparation. Artificial intelligence can automate this process of gathering and organizing data. It also corrects inconsistencies and eliminates outliers. Previously, this process of data preparation would be time-consuming, but with AI, it can be done within minutes.  

Advanced Analysis 

AI-powered analysis is more advanced and precise compared to traditional analytical tools. Machine learning technology allows AI tools to correlate data with a large amount of external and internal data sets. This way, AI tools can discover hidden patterns and anomalies that were not predefined in the tool. Such a tool helps forecast market trends and customer patterns for businesses.  

Output and Visualization 

Traditional analytical tools would not visualize the output in a manner understandable to laymen. However, artificial intelligence helps convert numerical or statistical data into graphs, charts, and pictures, making it more useful for newbies. This feature facilitates access to data analysis for everyone, irrespective of their knowledge of statistical terminology. 

How is AI Transforming Data Analysis 

AI is a transformative energy revolutionizing the data analysis sector. Over time, it has become a very important part of the data analysis process.  AI in data analytics automates tasks, calculates data, analyzes, provides insights, and also suggests improvements. AI makes data analysis easy and convenient for everyone to the point where one can ask an AI-powered chatbot a simple analytical question, and it gives a result in a conversational form. Now, let us see the types of AI in data analytics for a clear understanding.  

Types of Application of AI in Data Analysis 

AI-powered data analysis is divided into the following types. It utilizes different approaches to fulfill specific functions. In conclusion, AI-powered data analysis can be used to analyze what happened in the past to what can be done in the future. AI’s analysis works in different ways, which can be used alone or in combination for desired results.  

Descriptive AI 

Descriptive data analysis is the process that answers questions related to history. This application of AI in data analytics offers a descriptive report of what happened in the past. This is based on the data collected in the past. It may include organizational activities, profits, losses, patterns, etc.  A large amount of data can be processed and wrapped up in a simple report within minutes.  

Diagnostic 

The diagnostic approach uses AI in data analytics to answer the “why” question. This approach focuses on the root cause of changes in the statistical data. For example, an increase in sales of certain products or a decline in orders from a certain region. The diagnostic approach finds out the cause of changes and facilitates preventive or improvement measures accordingly.  

Predictive 

Predictive analysis is one of the best applications of AI in data analytics. This approach incorporates historical data and real-time scenarios to understand “what may happen” in the future. Predictive analysis is almost like descriptive analysis except for the time they are dealing with. One speaks of the past while the other speaks of the future.  

Prescriptive 

The prescriptive application of artificial intelligence in data analytics is a corrective measure suggested by AI to help businesses. It observes both the organization and the company to provide suggestions that can be implemented to improve the business. Prescriptive Analysis is the most advanced use case of AI in data analytics.  

Benefits of Using AI in Data Analytics 

AI is a saviour for data analysts as it assists them in making informed decisions and predictions. Some of the common benefits of using AI in data analytics are: 

  • Improved Decision Making 

  • Cost-Efficient 

  • Better Customer Experience 

  • More Productivity 

  • Enhanced Risk Management 

Conclusion  

AI is gradually becoming the backbone of every industry. When it comes to data analysis, it fits perfectly because both fields are dependent on data. Both artificial intelligence technology and the data analytics sector are fueled and limited by data quality, variety, and amount. The application of AI in data analytics is the perfect measure to boost the growth of any business. AnavClouds Analytics.ai is a reputed AI development company that provides both Generative AI services and data analytics services for businesses. Book a consultation session with them and prepare your company for the AI-powered era of the future.  


Source: https://www.anavcloudsanalytics.ai/blog/artificial-intelligence-in-data-analytics/

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