Did you recently use any generative AI tools and wondered if AI could also analyze business data for you? You guessed it right! These AI data analysis tools remove bottlenecks from business data analysis by automating most parts.
AI is transforming the data analysis sector as we know it. Various generative AI tools now take natural language as prompts and produce actionable insights. AIso is eliminating the need to form a robust data analytics department.
What Is Data Analysis?
Data analysis is collecting, organizing, analyzing, and visualizing data. The analysis part includes applying mathematical or statistical formulas depending on the scenario you want to resolve.
For example, applying the statistical mean analysis to understand what is the average sales volume for a product across regions. Or the Break-Even Analysis to understand when your business is neither profiting nor losing from a specific product or service.
From collecting data to final visualization, there are many steps. The standard steps that most data analysts follow are inspecting the raw data, cleaning it, transforming data, and finally, interpreting.
How Data Analysis Help in Business Decision Making
Data analysis helps you to make critical business decisions by providing you with some numbers. For example, you would like to invest in the SaaS business. To understand which SaaS product would bring in the most revenue and profit margin, you need to analyze the revenue data.
As an example, a recent report from Spendesk shows that businesses and end users would spend $195.20 billion on cloud application services products. Therefore, if you trust this data analysis, you should invest in cloud application services.
How AI Helps in Business Data Analysis
AI data analysis uses cutting-edge computational technologies like machine learning, natural language processing, deep learning, and neural networks when slicing and dicing your raw data. It automates most of the data analysis part, so you can sit back and ask it to produce the insights you are looking for.
AI data analysis removes various bottlenecks from the business data analysis process. With a generative AI powered by data analytics, your employees can simply give commands in natural language and get the actionable insight they need.
For example, look at the following simple data analysis that ChatGPT did for me:
I provided an imaginary sale volume, buying price, and selling price for a few smartphones. The generative AI tool analyzed the data in less than a second and generated the following:
A formula to get the net profit from buying price and MSRP
Profits from the given devices’ sales
And finally, a suggestion to sell which product to get the maximum profit
In summary, AI data analysis tools offer the following:
No code approach to data analytics.
Anyone with basic knowledge of mathematics and statistics, along with business management ideas, can produce actionable insights from AI data analysis tools.
These AI tools reduce the requirement for dedicated data analysts and scientists to a few so that you can save on staffing costs.
AI data analysis tools can explore hidden patterns and actionable insights from your business data in seconds. This would take human data scientists months.
AI Data Analysis Tools Vs. Traditional Data Analysis Tools
Features & Functionalities
AI Data Analysis Tools
Traditional Data Analysis Tools
Do not require a full department of employees. A few data analysts or scientists would suffice
Require more personnel compared to AI tools
AI tools can generate actionable insights faster and better without pre-programming
You must pre-program your data analysis project to get the actionable insight you want
Certain AI data analysis tools can generate novel insights that you were not expecting
These data analytics tools are always dependent on a human operator and programmer and suffer from human errors heavily
Human Error and Dependencies
AI tools, once deployed for production, are self-sufficient AI tools are free from human errors and risks unless the back-end programming is flawed
These data analytics tools are always dependent on a by human operator and programmer and suffer from human errors heavily
AI data analysis tools are dynamic and quickly adapt to business model changes
Traditional data analytics tools are static and would not change unless your data scientists reprogram the tools
AI tools directly answer why there is a certain change in the revenue or operations performance
These tools mainly answer a series of “What Questions” in your business so you can figure out the “Why”
AI tools are truly driven by data, not the hypothesis
Traditional data analytics tools are always hypothesis dependent
These tools mainly answer a series of “What Questions” in your business so you can figure out the “Why”
You must plan a detailed project ahead of the actual data analysis event so you get actionable results
Now that you know the importance of data analysis applications for your business, here are the premium tools businesses can choose.
Microsoft Power BI
Microsoft Power BI is a prominent application that uses AI to offer powerful business insights by creating a single source of truth. All you need to do is to ask a query, and this business intelligence software will generate interactive visual reports using next-gen AI tools. The application uses end-to-end data protection for datasets, dashboards, and reports.
It can convert raw data into engaging visuals and a drag-and-drop report canvas that anyone can use without any hassle. Power BI also supports integration with different apps (Power Apps, Power Automate, Dynamics 365, Azure, SharePoint, Excel, Salesforce, etc.) for quick decision-making.
Zoho Analytics is a powerful analytics tool for automated insights. It even has an AI-powered conversational assistant named Zia. It provides crucial analytical business insights from raw data within seconds using NLP.
You can start a conversation with Zia to get answers to your queries. The assistant will help you quickly get to critical business decisions through meaningful insights such as KPIs and powerful visualizations.
Whether you ask queries about sales, marketing, or finance data, it will offer complete visibility into your business. Moreover, it can perform smart interpretation and suggestions, predictive analysis, and on-the-go analysis; while supporting integration with ChatGPT.
Polymer Search is an AI-driven business intelligence tool that enables you to produce engaging and easy-to-understand dashboards and performance reports in minutes. Powered by an AI data analytics engine, the tool suggests you the data analysis formulas and data visualization elements you need to use in your reports.
The tool is carefully baked for the business niches like eCommerce, business operations, sales, and marketing. It comes with a vast list of data connector integrations, and the list is growing steadily. You can feed raw data using XLS, CSV, Google Sheets, Facebook Ads, Google Ads, Shopify, Jira, Linear, and more.
Akkio is an AI/ML tool for data analytics and BI, and it also helps you to create machine learning models using AI to develop your own AI apps for custom business data analytics.
The Chat Data Prep module helps you in cleaning, organizing, and transforming raw data. You do not need to run complicated Python scripts or SQL database query commands. Just ask the Akkio AI to append, merge, convert formats, etc., and the tool takes care of the rest.
For natural language processing, there is the Chat Explore module. After loading data from sources like Salesforce, Big Query, Google Sheets, etc., you can simply ask the AI model the insight you need, like “What was the sales volume in the past year?”, “How is Tom performing in the sales team?”, etc. questions. You get prompt replies with charts, graphs, tables, and dashboards.
KNIME brings you an open-source analytics platform. You can customize it the way you want to fit the data analytics project of your business. It has robust workflow automation to speed up the data collection, transformation, analysis, and visualization process.
However, the automation modules are only available if you buy a basic or better subscription. If you need an affordable spreadsheet automation and data science development platform, you can check out KNIME.
Insight7 helps you to understand the feedback of your products or services directly from the end users and clients in a few seconds. With Insight7, those days are gone when you would need to collect customer conversations, phone transcripts, etc., and analyze what the users have been saying for months. Now, you can simply connect the data sources to this AI data analysis tool and ask questions in natural language.
The tool will crunch through terabytes of interviews, NPS data, support tickets, and call transcripts. Then, generate data visualization along with suggestions on how to improve the product so customers will engage more.
Do you have a lot of customer conversations in emails, phone call transcripts, and chats? Do you also have data from interviews, focus groups, and online reviews? Feed them to Notably’s AI and get summaries and insights in a few seconds.
Also, it comes with popular templates like Business Stakeholder Interview, 4 What’s, Jobs to be Done, and more, so you can skip the setup and go directly to the insights you need.
Are you a small business? Do you run data analytics learning schools or platforms? Are you a large business with terabytes of raw business data sitting idle in silos? Start using Kanaries to see the difference in minutes, if not seconds.
Its augmented analytic engine processes the raw data you feed and generates professional insights, patterns, forecasts, and suggestions to grow the business the way you want.
It also has the necessary modules to perform automatic data preparation for your data science projects. If you already have a robust data analytics division, the tool can become a part of it and generate insights alongside existing data experts.
AI Surge Cloud
AI Surge Cloud helps your data science department do more research and develop actionable insights by offering a low-code data fabric. The primary use of this AI tool is for data preparation and data analysis. Since it works like a data fabric, you can use it in any industry, like software development, marketing, sales, retail, etc.
Besides offering a data fabric platform, the tool also helps you to develop data visualization dashboards. The tool also helps you generate recommendations, BI, and predictive analytics by pulling and transforming data from many third-party data sources.
Do not let information barriers slow down the growth of your business. Move to Seek AI and make the most generative AI-powered database queries to modernize your business analytics. Now, data science teams do not have to make ad-hoc requests as this software empowers business users to utilize their data sets.
Seek AI prevents you from reacting blindly to industry trends without critical insights. It uses built-in Workflow technology (patented) to ensure high accuracy in data analysis. You can securely connect this compliant platform with various data warehouses such as BigQuery, Snowflake, Redshift, AWS S3, SQL Server, and Synapse.
How to Choose the Best AI Data Analysis Tool
Understand the data analytics complexities and technologies you would need now and in the future. Accordingly, choose software that can support those.
The AI tool must come with total privacy. It should not send conversations to the developer without informing you or your team.
The AI data analysis tool must possess advanced data encryption and role-based access so you can secure confidential business data easily.
Perform extensive accuracy testing before finalizing.
Explore the technical support and developer documentation support from the AI data analysis tool developer.
By now, you should have learned which Ai data analysis tools are making a buzz in the market. These are the best tools you can get to put your business’s data analytics operations on autopilot mode. Give the above tools a try and choose the one that suits your business the most.
Tamal is a freelance writer at Geekflare. After completing his MS in Science, he joined reputed IT consultancy companies to acquire hands-on knowledge of IT technologies and business management. Now, he’s a professional freelance content… read more
Rashmi has over 7 years of expertise in content management, SEO, and data research, making her a highly experienced professional. She has a solid academic background and has done her bachelor’s and master’s degree in computer applications…. read more