Top 10 AI Data Analytics Platforms for Business Intelligence

Data is one of the mandatory attributes of every business and organization. Since globalization and digitization expanded worldwide, countless bits of data are generated in every blink of an eye. Eventually, data analytics tools became necessary to segregate, categorize and analyze this bulk.  If manual management is a hassle for you, AI data analytics tools are now available to automate your work and generate the desired information!

Top 10 Analytics Platforms

Advanced data analytics tools are designed with machine learning and AI principles to understand the requirement and execute the analysis accordingly. The following data analytics software tools are currently trending for business applications.

1. Sisense

If you plan to use AI for data analysis, Sisense can help you with an easy-to-integrate platform. This data analytics software combines with any existing database tech-stack to collect raw data and analyze it according to the dashboard settings.

It performs ELT data integration using the Elasticube platform to represent the results in tables, charts, or selective outputs. Of all the data analysis tools, Sisense can be used by multiple employees for diverse business data analytics to get data-driven solutions for all.

Pricing: This AI data analytics platform offers a customized package with all the required solutions and services. You can request a price quote and try the free trial version for testing.

Pros:

  • Easy-to-apply AI data analysis on multiple work platforms.
  • Creative dashboard for quick management.
  • Allows integrating third-party plug-ins.
  • An entirely guided platform for big data AI

Cons:

  • Tutorials aren't plenty enough for every detail.
  • It doesn't report database changes through emails.
  • More data or analyzing columns can slow down the software.

2. H2O

If you require advanced big data AI analysis for various predictions and fraud detections, H2O provides an open platform to design a fully-automated data analytics software. Developers can create a robust platform based on machine learning and natural language processing to extract data from docs, images, or audio files.

Models can flexibly manage multiple models in distributed categories to arrange, analyze and obtain creative outputs. This platform also offers innovative apps for various industries and plug-ins to enhance AI in business intelligence.

Pricing: H2O offers customized packages instead of fixed subscriptions. Users can request demo consultations and try the 14-day free trial version.

Pros:

  • Offers AI cloud platform for integrated storage and analysis.
  • Allows designing and developing customized AI data analysis tools.
  • Customer support offers hands-on tutorials.

Cons:

  • Users need to know Python/R programming.
  • Highly suitable for data scientists and developers.

3. Obviously

Obviously, one of the easy-to-use data analysis tools offers a creative platform to implement AI-driven analyzing models for every organization. Users can integrate databases or upload the files, choose the required model and get the automated platforms to predict any result using AI for data analytics.

The platform uses drop-downs and clicks to set icons to create models in no time. Unaligned data files are also adjusted using data dialog converters.

Pricing: Provides two packages, Basic and Pro, with varying services and features. Charges depend on models and predictions used.

Pros:

  • No code demanding AI data analytics
  • Can share models to multiple devices.
  • Developers can modify apps using low-level API languages.
  • Can check what-if scenarios along with predictions.

Cons:

  • Users have to stick to the app-built models.
  • In-depth modifications are only possible in custom apps with prior programming knowledge.

4. Scale

Scale is an overall big data AI analysis tool designer and a versatile platform implementing AI in business intelligence. You can instantly access advanced ML and NLP-based models for any business prediction, data analysis, and document categorization.

Using AI for data analysis, users can annotate the data files, collect or generate various data segments from files, segregate them into defined categories, and evaluate to get AI-driven results. The systematic approach also favors effective data storage.

Pricing: Provides two packages, Rapid and Enterprise, with varied data, image, and video annotating tools. Charges are applicable only for the services used.

Pros:

  • It offers various annotating tools suitable for all data formats.
  • Can generate synthetic data from raw inputs.
  • No code, ready-to-use AI data analysis tools.

Cons:

  • Code modifications aren't possible.
  • Can't integrate multiple user devices on a single platform.

5. Iseek

Iseek offers an entirely trained bot model to arrange and analyze the data among the top data analytics tools famous for extensive features. Iseek's AI for data analytics uses machine learning and natural language processing to normalize all the data formats compatible with the models, decipher desired data to analyze, and produce creatively designed output presentations.

Its models, implementing AI data analysis, support continuous data segregation and systematic auditing without any delay.

Pricing: No fixed subscriptions are available. Users can directly contact them to customize their services.

Pros:

  • Can collect vast data from several resources.
  • The platform provides fully-automated machine learning bots for analysis.
  • Easy-to-use and no code implementation.
  • Converts and adjusts any data to the required format.

Cons:

  • Services are limited to the medical and publishing industries.
  • Users can't modify the models according to their will.

6. Opentext

One of the top software using AI in business intelligence, Opentext's Magellan analytics is a broad prospect for every organization seeking complete data integration.

Using AI for data analytics, the models extract desired data information (including sensitive words) to analyze them and derive graphical or statistical results. Users can also integrate their plan with cloud and managed services for overall monitoring.

Pricing: Doesn't have any fixed subscriptions. Clients can approach customized model development.

Pros:

  • Analytics also offers consultancy and cloud services.
  • Users can export the analyzed data.

Cons:

  • Models are based on REST API format.
  • No free trials are available.

7. Metabase

A single platform to manage and monitor sales and revenue effectively; Metabase is an exclusively designed business data analytics software. You can link multiple users to build, share and export data and manage your company-wide KPI dashboard with creative analysis and graphical tools.

It deploys AI for data analytics by extracting information through SQL tables and interpreting them according to the filters applied.

Pricing: There are three managed packages, Starter for $85 pm, Pro for $500 pm, and Enterprise for customized solutions. It also offers an open-source deployment environment supported by DockerImage or Jar files.

Pros:

  • Models work with all SQL databases.
  • Can share and export data to multiple gadgets.
  • It creates dashboards with filters for data categorization.

Cons:

  • The app could be confusing to navigate easily.
  • Big data AI analysis might get stuck in between.

8. Softtek

One of the vast data analytics tools for multinational businesses, Softtek offers integrated services to manage data and deploy AI in business intelligence systems.

The platform’s AI data analysis uses high-tech robotic and intelligent digital automation to manage the bulk of information taken from various resources like text, image, or audio. It also deploys cognitive automation to enhance machine learning principles for reducing human intervention.

Pricing: There are no subscriptions as the team negotiates the charges as per the services offered.

Pros:

  • Multiple services for overall AI data analysis.
  • Talented team working on a global platform.
  • Suitable plans for every industry and business.

Cons:

  • Suitable for vast enterprises.
  • Users don't have any choice to modify the platforms or services.

9. Qlik

Qlik is a brilliant choice for instant data arrangement and simplification if you search for simple-to-use data analysis tools. With swift drag and drop facilities and multiple data source management, the software can implement AI for data analytics to obtain creative results. The platform offers AI-driven search icons and easy navigation to produce interactive reports with innovative data representation.

Pricing: Provides business subscription plan for $30 per month and Qlik sense enterprise plan for customized services. It also has a 30-day business trial package.

Pros:

  • Can manage multiple data sets in a single click.
  • Interactive data representation for easy understanding.

Cons:

  • Data visualization can improve.
  • More layout features can enhance the performance.

10. IMB Analytics Platform

Also known as IBM's Watson, this AI data analytics tool is a cutting-edge technology to collaborate and manage multiple business applications. The entire analytics platform leverages several data analytics software like Cloud Pak for data deployment, Db2 Warehouse for extensive cloud data storage, DataStage for data categorization, Infosphere for 360-degree data management, and Watson Studio for big data AI analysis.

Using AI for data analysis, you can train the model and automate it for obtaining intuitive results instantly.

Pricing: IBM's Watson provides subscriptions like the Plus edition for $30 per user per year and the Professional edition for $80 per user annually. They also have a trial version.

Pros:

  • Automated models designed with advanced machine learning.
  • Easy to use and integrate platforms.
  • Users can access multiple guidance tutorials.

Cons:

  • Real-time data analysis isn't possible.
  • Multiple features of the dashboard can be confusing.

Conclusion

AI for data analytics simplifies the user's tedious job of giving input, categorizing the files, or searching for the desired output. These data analytics tools can be modeled to present the selected analysis in an intuitive and ready-to-use format.

All the top software discussed here are easy to install, suitable for versatile businesses, and capable of big data AI analysis to keep a constant track of the humongous amount of data generated every time.

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