2023 began with a boom of AI that could be used by every business person. ChatGPT took the world by storm. Then slowly, AI is becoming accepted widely across several applications in diverse industries in different forms. But what role does AI play in data analytics? And how does AI data analytics make use of machine learning algorithms for constantly monitoring huge volumes of data and automate the time-consuming work which is normally done by a data analyst?

We will find all the answers to these questions and more in today’s blog.

So, let us begin.

What is AI Data Analytics?

AI data analytics is the subset of business intelligence which makes use of machine learning techniques for discovering insights and finding patterns and relations in the data. AI for data analytics is the process of automating a lot of work which a data analyst would generally perform. The aim is not to replace the analyst but to improve the data analysts’ capability to speed and scale the level of data analysis along with monitoring granular data.

AI data analytics is yet another form of analytics which will be the future of analytics. Augmented analytics makes use of machine learning and artificial intelligence to discover patterns in the data along with valuable insights without the involvement of any data scientist. WebDataGuru uses AI data analytics for its platform and that helps in discovering better and more efficient ways to do your business.

Impact of AI on Data Analytics

1. Efficiency and Speed

AI tools help in processing data quickly as compared to humans. The insights a business can gain from the analysis are accurate. Thus, organizations can act on it and make relevant decisions. Humans might not remember all the commands of the data analysis libraries. However, AI data analytics looks for these commands and suggests alternative approaches for analysis.

2. Fact-checking

With AI and data analytics, businesses can detect inconsistencies in the data. If the results of analytics are out of sync than expected, AI chatbot can help with the investigation. Some AO models also highlight the potential issues even before they occur.

3. Data Democratization

AI can help in achieving more democratized access to data. With the help of natural language processing in AI chatbots, businesses can enable non-data users to analyze high-volume data sets speedily to extract key insights. Thus, with AI in data analytics, it becomes easy to get access to complex datasets without being acquainted with the technical language related to data science.

4. Automated Reports

With the help of AI data analytics, you can completely automate the report generation process. Instead of creating the reports manually for each analysis, the AI tools will generate reports quickly and automatically. The automated reports ensure that the employees have access to the same information regardless of their background or location in a timely manner.

How AI can do Data Analytics

1. Machine Learning

AI makes use of machine learning algorithms to process huge volumes of data for identifying patterns and creating AI models based on that. The machine learning model works based on the information fed. It displays trends based on the learning and offers relevant output depending on the request.

2. Natural Language Processing

NLP enables computers to interpret human language. AI algorithms read massive amounts of text to learn the meaning of words and respond to the user input. AI can analyze the input text to generate new content and summarize the current information.

3. Computer Vision

Computer vision deals with how computers see and interpret videos and images. It helps in analyzing the huge amounts of video and image content to identify the patterns. AI tracks motion, extracts feature from images, and identifies faces.

Benefits of AI in Data Analytics

1. Speed and Efficiency: AI can process and analyze vast amounts of data much faster than humans, saving time and resources.

2. Accuracy: AI reduces human error, providing more accurate and reliable insights from data.

3. Pattern Recognition: AI excels at identifying patterns and trends in data that might be missed by human analysts.

4. Predictive Analytics: AI can forecast future trends and outcomes by analyzing historical data, helping businesses make informed decisions.

5. Automation: AI automates repetitive and mundane tasks, allowing human analysts to focus on more complex and strategic activities.

6. Scalability: AI can handle large-scale data analysis, making it suitable for businesses of all sizes, from small startups to large enterprises.

7. Personalization: AI can analyze customer data to provide personalized recommendations and experiences, enhancing customer satisfaction and loyalty.

These benefits make AI a powerful tool in transforming how organizations analyze and leverage their data.

How to use AI in Data Analytics

1. Generating Code and Debugging Errors

First of all, AI would be used for generating code and debugging errors in data analysis. It can help in complex tasks like visualizing huge databases and building models for machine- learning. If you have written complex code for yourself and have issues explaining it, AI can comment for you on the code. This way, you can save time on the documentation process.

AI can also help with code completions. You can start typing a function and AI will complete the rest of the code depending on the information in your comment. AI tools can debug the errors so the process of looking for a solution gets short significantly.

2. Explain Analysis and Insights

In data analytics, it is important to explain the insights and go deep into data to extract in-depth business insight. It is here that AI comes into the picture. AI-based data analytics can explain the behavior of a specific data on the chart and offer deeper information.

A business can ask straightforward questions such as why the sales decreased in March or which was the best quarter of the year revenue wise. The AI chatbot will scan the datasets and find the trends and patterns which would offer answers to your questions.

3. Creating Synthetic Data

Another benefit of AI-driven data analytics is the production of synthetic data. It has been predicted that future AI models will be trained mostly by the synthetic data. It can be useful for machine learning engineers or data scientists. AI can also help data analysis with automated data imputation. It can help in filling the datasets with missing values in a quick and accurate manner.

4. Create Dashboards and Reports

AI is useful in creating reports and interactive dashboards. AI-driven tools such as price monitoring, competitive analysis and market trends can be used to aggregate data from several sources into a user- friendly report. One doesn’t need any prior experience in the field of data visualization. You need to select the data and the AI will automatically format it into a graph or chart. AI can also be used for creating aesthetic charts for generating captivating ideas for the dashboards which are relevant to the analysis.

5. Automated Data Entry

Data analysts who use Excel and other spreadsheets frequently can easily automate the process of data entry from images. It is particularly helpful while collecting large amounts of data from documents and images, allowing entering required information without manual intervention.

Traditional analytics is different from generative AI for data analytics. AI is not meant to replace traditional analysis but to assist it in improve the process. AI is changing the face of analytics in several industries such as marketing, customer insight, manufacturing and supply chain, eCommerce and retail, finance and banking, and healthcare and medical research to name a few.

Dive into The AI Game with WebDataGuru

This is the time to discover how AI algorithms seamlessly swift through massive datasets, extracting meaningful patterns and insights that were once elusive. As now, it’s not just about analytics; it’s also about predictive prowess, enabling you to anticipate trends, customer behaviors, and market shifts with unprecedented accuracy. Bid adieu to the olden days of drowning in data and say hello to actionable intelligence that empowers your business strategy in more than one way.

Are you ready to turn the page on conventional analytics? Then, your future awaits just a click away. Book a free Demo Now!