Data analysis is more vital now than ever before. And, even if you are an experienced data analyst, you will need the correct AI tools to analyze data.
There are numerous tools available to view, analyze, and track your data, allowing you to gain the insights you require to reach your objectives. But, with so many tools available, how can you determine which one is best for you?
What exactly can AI tools do for you and your data?
How Is AI Utilized in Data Analytics?
With AI getting more evolved by the day, it is becoming a more powerful, efficient, and approachable solution for data processing.
Some modern applications of AI in Data analytics include:
- Finding insights: AI can analyze massive volumes of data to identify trends and patterns that can assist users in finding the insights they need to better their sales and marketing operations, customer interactions, engagement, and other areas.
- Streamline data analysis: By consolidating all data into a single solution, users may receive a more comprehensive overview of their data, making it easier to understand and track.
- Expect results: Predictive AI allows users to create forecasts and assess different scenarios to determine which one has the best likelihood of success.
Furthermore, no other solution can handle all of the problems that AI does, or analyze data more efficiently and intelligently.
Why should you utilize AI Tools for your Data Analysis?
So, you already have access to your website’s analytics or marketing data; what can AI do for you?
You can use AI to ensure that all data is analyzed uniformly. Because AI is free of human bias and can analyze massive amounts of data at breakneck speed, it can forecast how your ads will perform and even offer preemptive insights to guarantee you’re capturing all information.
This enables you to review and manage your data even if you are not a data scientist. After all, with AI tools, you can bypass the time-consuming and costly process of designing algorithms and get directly to analyzing your data.
The best 10 AI tools to analyze data
There exist some of the best AI tools to analyze data:
1. Polymer
Polymer Search is a sophisticated AI-powered solution designed to transform your mundane data into a more streamlined, powerful, and flexible database. All of this was accomplished without writing a single line of code.
Polymer augments your spreadsheet with powerful AI to help you examine and comprehend your data with a few clicks. There is no lengthy onboarding procedure or training films to watch. Simply submit your spreadsheet to Polymer and it will be quickly transformed into a simplified database that is easy to navigate.
Simply join into your free Polymer account and upload or share your spreadsheet from the cloud. Polymer Search will then encrypt and analyze your data, transforming it into a powerful web app that is simple to search and study.
You can further edit the web app with numerous layouts at any time to find the one that best meets your current requirements. The “Smart Pivot” tool can also be used as a powerful and upgraded pivot table.
Polymer is the most basic approach to using AI to analyze data, while also providing easy visualization tools and nearly endless ways to interact with your data.
2. Tableau
Tableau is an analytics and data visualization tool that enables users to engage with their data without having to code.
The platform is simple to use, allowing users to build and change dashboards and reports in real-time, as well as share them with other individuals and teams. It has all of the capabilities anticipated of such tools, such as support for databases of different sizes and multiple display options for users to study their data.
Tableau users can also run the platform in the cloud or on-premises if they choose a more hermetic environment for their data.
3 . MonkeyLearn
MonkeyLearn is yet another no-coding platform that includes AI data analysis features that allow users to visualize and rearrange their data.
The platform includes several AI-powered text analysis tools that can rapidly analyze and visualize data to meet the demands of the user. Users can configure text classifiers and text extractors to automatically sort data based on subject or intent, as well as extract product attributes or user data.
The tool includes many integrations to work with whatever tools are already in use, as well as a basic and intuitive UI that matches the platform’s simplicity.
4. Microsoft Power BI
The platform enables users to import data from virtually any source and begin building reports and dashboards as needed. Users can also create machine learning models and utilize other AI-powered tools to aid with data analysis.
Microsoft Power BI is a well-known business intelligence application that also allows customers to sort through their data and visualize it to gain insight.
The platform includes many interfaces, including a native Excel integration, and a UI that is faster and more responsive than competing options, albeit at a premium price.
5. Sisense
Sisense is yet another data analytics platform that enables analysts and developers to organize and analyze their data.
The platform is simple to use, with numerous drag-and-drop capabilities and a responsive user interface designed to streamline the process. Sisense also allows users to utilize their “In-Chip” technology and select between RAM and CPU to handle data, which speeds up computation when dealing with massive datasets.
Despite its limited visualization features, the platform is a decent choice for users with basic visualization and reporting needs who want to work with smaller datasets.
6. Microsoft Excel
Microsoft Excel was the best data analysis tool when it was first introduced, and it still is now.
Users can utilize Excel’s Data Analysis Toolpak to analyze and process data, generate basic visualizations, and quickly filter through data using search boxes and pivot tables. Excel also allows users to design machine learning models without coding, calculate data from clusters using formulas, and even create complicated neural networks.
Although Excel’s capabilities have evolved, it is still limited by its spreadsheet paradigm and steep learning curve, even when no coding is required.
7. Akkio
Akkio is a business analytics and forecasting application that allows users to examine data and estimate possible outcomes.
This no-coding platform includes lead-scoring tools that allow users to qualify, segment, and prioritize hot leads. The forecasting tools enable users to use their existing data to make future predictions on virtually any dataset.
The program is quick and easy to use, and it includes a few important connections for transferring data to and from other tools.
8. Qlik
QlikView is another business intelligence and data visualization tool that allows customers to evaluate their data using AI technologies.
The platform includes a variety of data exploration options as well as a versatile platform that is suitable for both technical and non-technical users. Teams may easily collaborate on the platform by manipulating their data with simple drag-and-drop editors and processes.
Despite its great functionality, the platform’s hefty cost and comparatively modest AI feature set make QlikView a preferable alternative mainly for those who can fully utilize the platform.
9. Looker
Looker, another no-code data analysis and business intelligence product from Google Cloud, with powerful capabilities and many integrations.
Looker can process big databases, create various dashboards and reports, and consolidate all of your data sources into one. The platform is also capable of extensive data modeling features and has the advantage of being Google-backed.
Although the platform is simple to use, it lacks versatility, and creating reports from scratch can be time-consuming.
10. SAP BusinessObjects
SAP BusinessObjects enables non-technical users to analyze, visualize, and report on their data while connecting smoothly with the rest of the SAP suite.
It provides customers with access to AI and machine learning technologies for data modeling and visualization, better reporting, and dashboarding. Users can also access predictive forecasting features to acquire a deeper understanding of their data.
Although the platform’s pricing has been reduced, the cost of the solution, particularly when purchasing platform licensing, can still be prohibitive. As a result, this solution is best suited for SAP clients that can benefit from an AI data tool that works with the other SAP tools they already have.
Summary
AI tools can let you go deeper into data than ever before. You can utilize them to gain insights, identify trends and patterns, and make better data-driven decisions. With artificial intelligence becoming more economical and available to people, it is wiser to implement it sooner rather than later.
Begin by importing your first spreadsheet into Polymer and seeing how simple it is to analyze your data with the help of Polymer’s strong AI.
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