Analyzing data to get valuable insights has now become crucial for every business. It helps them to truly understand and make wise choices based on their data. For this, companies use AI-powered tools.
- Intro to AI Tools for Data Analytics
AI tools for data analysis are software or programs that use artificial intelligence to automate tasks involved in a data analytical procedure. They use machine and deep learning for data collection, cleaning and organizing, predictive analysis, and segmentation. With these tools, teams can process, analyze, and interpret hefty amounts of data, unveiling concealed insights. Hence, they are widely used by industries, from finance to healthcare, to improve efficiency, correctness, and decision-making.
- Statistics for AI Data Analytics Tools
Data analytics and artificial intelligence will make gigantic jumps in the coming years!
According to one statistic, the global data analytics market size, which was around 30 USD billion in 2022, is forecasted to reach 393.35 USD billion by 2032. Another report says that the market size of data analytics is likely to surpass 745.15 USD billion by the year 2030, and that of artificial intelligence is predicted to soar to 2025.12 USD billion.
- Benefits of AI Tools for Businesses
Merging data analytics with artificial intelligence brings plenty of benefits for business. Of them, we’ve shared the major ones below:
- Boost in efficiency and productivity
AI introduction into data analytics automates tough data processing activities, which take humans a bit longer to finish, rocketing efficiency. For example, AI algorithms can crunch through tons of datasets and detect relevant trends and behavior quickly. It speeds up workflows and squeezes the time from months or weeks to days or even just hours! This allows teams to be creative and focus on more essential projects, boosting overall productivity.
- Cost savings and resource optimization
Organizations can cut expenses and save time through data analytical tasks automation. This is made possible by using AI analytics tools. They enable lightning-fast evaluation, fewer false insights, and a drop in human work. Their speedy and accurate data handling capabilities minimize the need for a lot of human intervention. Moreover, AI can also optimize resource allocation, making sure to use the available assets to their maximum potential.
- Recognition of advanced patterns
AI algorithms are brill at spotting intricate patterns in datasets and revealing interactions, trends, and anomalies. They use advanced ML models, such as convolutional neural networks (CNNs) and recurrent neural networks (RNNs) to detect visual data trends and understand repeated patterns in historical data. Large datasets may be processed and analyzed by these models with a level of accuracy and depth that is not possible with human analysts.
- Improved insights & decision-making
AI tools offer data-driven insights that assist in making sound decisions. Such innovations can help firms uncover fresh opportunities and optimize their strategy by forecasting shifts and looking at habits. As a result, reliance on tedious and time-consuming older techniques is reduced. With the help of AI predictive analytics, businesses can lower risks and understand forthcoming patterns, which empowers them to make smart choices for their company.
- Top 12 AI Tools for Data Analytics
There is a sundry of AI tools that companies use in 2024 for data analysis. But we’ve talked about the top 12 ones that companies prefer the most.
Tableau is a standard data analytics and visualization platform that lets you craft dynamic visualizations and dashboards without coding.
The AI platform is user-friendly and allows users to make and edit their reports and dashboards instantly and share them with other individuals and teams smoothly. It has every AI-fueled capability one would want, supporting databases of any size and providing users with many visualization options that help them in fast data investigation. Plus, it’s available as a cloud or on-premise solution.
However, Tableau is not suitable for huge datasets. Besides, it’s expensive compared to other tools, costing around $12 a month.
MonkeyLearn is an easy-to-use, no-coding tool that focuses on text analysis abilities to help firms visualize and rearrange data.
The tool makes it easy for users to extract insightful information from unorganized data sources, like social media, emails, and customer reviews. It enables both technical and non-technical users to develop custom text analysis models according to their needs via its user-friendly interface and multiple pre-built models. Also, it offers smooth integrations with well-known apps and programming languages.
But MonkeyLearn is ineffective when used with data other than text and its efficacy relies on how good the input is.
Akkio is a no-code business analytics and forecasting platform that permits users to examine their data and predict possible results.
It comes with lead-scoring features so users can qualify and segment their lead lists, which helps them identify and prioritize hot leads with comfort. With its forecasting feature, users are able to make future predictions on any dataset using the data they already have. Apart from that, Akkio has a generative AI function and also allows for the creation of personalized chatbots.
Yet, the platform’s integrations are limited and it might lack advanced functions for complicated data science requirements.
Sisense is a business intelligence tool that speeds up product innovations by infusing data-driven insights into applications.
This tool is popular for its intuitive interface, strong analytics skills, and smooth integration with different data, which help users get in-depth, real-time company performance insights. It also gives users the option to utilize their “In-Chip” technology and process data using either RAM or CPU, which speeds up calculation when working with big datasets and comes with flexible tools with SDKs and APIs allowing tailor-made solutions.
Sinsense has limited visualization options. Still, it’s a decent choice for users with simple reporting and visualization needs.
DataRobot is an enterprise AI platform that automates and expedites the building and deployment of machine learning models.
The platform is easy to navigate and its interface is very user-friendly; besides, it helps businesses make data-driven decisions quickly. It is a terrific tool for individuals without coding expertise and for enterprises that need automated machine learning capabilities for predictive analysis. Thus, DataRobot substantially increases efficiency, saves time, and cuts down the need for constant human intervention.
Despite offering high automation and ease of use, small businesses might find DataRobot pretty expensive.
AnswerRocket is one of the powerful data analytics tools that helps companies sift useful insights from a mountain of data in seconds.
With this platform, users can swiftly explore and visualize data by asking queries in simple words. It uses ML and AL to simplify and accelerate the data analysis process. This robotic execution of mundane chores and fast replies to distinct inquiries boosts productivity and positively impacts a company’s output. It’s highly recommended for any company looking to make more intelligent data-driven decisions.
Although the tool is fantastic overall, it has some bugs and limitations and the dashboards are not up to date in the background.
Power BI is another intelligent tool built to allow users to navigate and visualize their data to extract valuable insights.
IT professionals, business analysts, and business users in different industries can use it to import data from numerous sources and create dashboards, datasets, and reports. It also gives them the ability to integrate ML models with AI-infused features to enhance the depth of analysis and offers seamless integration with Microsoft products and robust data protection.
Even though, it has incredible capabilities, it offers advanced features at a high price, requires sophisticated preparation of data, and doesn’t have a straightforward interface.
Qilk, a leading data analytics tool helps companies design compelling and customized data visualizations, dashboards, and reports.
It has an intuitive interface and a range of data connectivity choices. Using Qilk, users can explore and analyze huge quantities of data from various places to discover hidden insights and make sensible decisions. Moreover, its facile drag-and-drop editors and workflows help teams work together and share reports and dashboards within the firm with ease.
In spite of Qilk’s superb functionality, it is only suitable for people who can fully utilize it due to its higher price tag and rather limited array of AI powers.
H2O.ai is a prominent platform for democratizing AI and enables large machine learning for companies and individuals in multiple sectors.
The tool is well-liked for its open-source, in-memory architecture and lets data scientists and analysts develop and deploy ML models to carry out predictive analytics. Because H2O.ai supports a variety of ML techniques, it excels at assisting in a wide range of data analysis work. Its scalable architecture, which promises excellent examination and sorting of growing data quantities, is its biggest asset.
The UI, however, looks cumbersome, and successful execution calls for technical know-how. Also, H2O.ai still lacks customization.
KNIME is a flexible open-source platform designed for data analytics and smooth integration with scores of platforms without much coding and effort.
KNIME is exceptional when it comes to work-sharing practices and workflow mappings. It also offers a complete toolkit for data analysis, which includes predictive modeling, machine learning, and ETL processes. The tool is easy to use and with visual process flow, it makes it more comfortable to work and grasp the model. Additionally, it provides assistance and technical advice to all new users.
Though the software is really good, it slows down during the installation of extensions. Plus, its deployment is not as easy as development.
Polymer is another open-source tool that empowers users to make engaging data visualizations and dashboards without coding.
With an intuitive interface, Polymer makes visualizations and dashboards accessible and allows users to embed data presentations in a breeze. It uses modern AI tools to analyze data and get rich insights. Also, it gives users the option to customize their data according to what they need. Apart from that, it offers diverse integrations with tools, such as Shopify, Google Ads, Facebook, etc.
The tool is really impressive, but it has some drawbacks. Its pricing is fairly high, and users may need some time to fully get its new features.
Julius AI is an important data analytics platform with a unique ability to analyze, visualize, and animate complex data in no time.
The tool’s interface is straightforward, making it simple for everyone to navigate. Users can download and share visualizations and conversations seamlessly with their team. They can chat with their data to make data analysis enjoyable and obtain valuable insights. Julius provides excellent resources and prioritizes data security with strict access control measures. Plus, the integration of ChatGPT enhances its versatility.
Nevertheless, Julius lacks an API, doesn’t provide real-time support, and could have more third-party plugins.
If we look at these top AI tools for data analytics, each one comes with specific features and capabilities that meet your unique data analytics requirements. However, to select the right AI tool, you first have to identify what problems you want it to solve. Then, compare the features and capabilities of various tools and prefer ease of use and strong support. Also, see if the platform offers integrations with existing systems.
- Closing Thoughts
The list of AI tools we’ve discussed above will shape data analytics in 2024. It doesn’t matter if you’re a data analyst, a data scientist, or an IT professional, these AI tools will assist you in using AI to get more details, leading to better decision-making and sparking novelty in your company. Thus, companies need to keep informed of the latest refinements in these tools to stay ahead!
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