10 Best AI Tools for Predictive Analytics [2024]

Introducing the 10 Best AI Tools for Predictive Analytics: With the evolution of technology, predictive analytics have served as a powerful tool for decision-making. These AI tools serve as a crucial resource for businesses. Developers and large businesses generally use these analysis tools to help in forecasting as per the data analysis.

Finding a model that demonstrated utility in predictive modelling was a complicated process that may take weeks or months of experimenting with various data sets, investigating various hypotheses, and validating several prototypes.

What are Predictive Analytics Tools ?

Predictive analytics tools use past and present data to forecast future trends and possibilities. They employ advanced techniques like machine learning to uncover hidden patterns and make informed predictions, aiding decision-making in various industries.

Key Points:

Function: Analyze data to predict future events and estimate probabilities.

Techniques: Use machine learning, statistical models, and data mining.

Benefits: Identify risks and opportunities, optimize resource allocation, personalize customer experiences, improve fraud detection.

Examples: Predict customer churn in marketing, assess loan risks in finance, predict patient readmission in healthcare.

Top 10 AI Tools for Predictive Analytics List

Now that we’ve learned about predictive analytics tools, Predictive analysis uses the following tools to help businesses make better decisions by analyzing data and predicting future trends. So, here are the 10 best AI tools for predictive analytics of 2024 along with their features, pricing, and pros & cons.

1. Google Cloud BigQuery

BigQuery is an advanced AI solution for accurate predictive analysis. It can analyze and manage data using geospatial analysis, business intelligence, and other features. BigQuery serves as an analysis engine that can analyse terabytes in seconds and petabytes in minutes.

Features:

• This analysis engine can maximise its flexibility by analysing data from storage.
• Data Scientists and developers can use libraries with familiar programming like Python, Java, JavaScript, and Go.
• Its ML documentation can discover, implement, and manage data tools for business decisions.

Pros:

• It fetches data quickly by automatically optimising queries.
• It can efficiently manage data across multiple databases.
• The editor and query builder can analyse new queries quickly as they have an intuitive interface.

Cons:

• Users cannot search for specific columns using the search function.
• Using Excel to upload a database can be time-consuming.
• The error message can be more customizable to correct errors.

Pricing: ₹4.15 per GB per Hour

WebsiteLink: https://cloud.google.com/bigquery?hl=en

2. Microsoft Azure Machine Learning

Azure Machine Learning is a machine learning predictive analytics. It can accelerate and manage the machine learning project cycle. Engineers and data scientists use it to train and deploy machine learning operations (MLOps).

Features:

• The quick ML model helps in deployment, management, and sharing for MLOps and workplace collaboration.
• It provides users with built-in security, compliance, and governance to function machine learning workloads.
• The data-driven decisions help in building transparency and accountability.

Pros:

• This analysis engine deploys web service efficiently.
• It is a centralised platform for machine learning.
• The experiment creation process is made easy.

Cons:

• Python code is hard to apply and run on this predictive analytics.
• It only has a limited number of models.
• To use it, the user requires a good internet connection.

Pricing: Free or paid for $9.99 per ML

Website Link: https://azure.microsoft.com/en-in/products/machine-learning

3. Qlik Sense

Qlik integrates AI into predictive analytics for business success. It allows users to have curiosity-driven and open-ended exploration at any skill level. Its discoveries lead to transformative changes and promising outcomes.

Features:

• It supports analytics features like data discovery, data mining, ad-hoc analysis, and predictive modelling.
• The users can add narratives and context to the analytics.
• The enterprise provides guided analytics, custom analytic applications, self-service data visualisation, and embedded analytics.

Pros:

• The users get a free 30-day trial, and various beneficial features are available during this period.
• It improves data literacy for the users, regardless of their previous skill set.
• With the search features, users can get quick responses.

Cons:

• The users can sometimes fail to download information to Excel.
• The prices for some add-on features can be expensive.
• The users with large teams can find it to be costly.

Pricing: $2700/month (Premium) with a 30-day free-trial and $20/user/month (Standard)

Website Link: https://www.qlik.com

4. SAP Predictive Analytics

SAP Predictive Analytics is an advanced AI solution for accurate predictive modelling. It has a user-friendly interface that allows users to create, operationalize, and monitor predictive models.

Features:

• The data sources like Java database (JDBC), SAP, XLS, and HANA are connected to it.
• The users can rely on SAP visual intelligence for data acquisition and manipulation.
• It is in integration with SAP Lumira workflow.

Pros:

• The cloud-augmented feature helps users to create audience segmentation based on their reviews.
• It is a multi-user platform which makes collaboration between organisations quick and easy.
• The SAP Analytics Cloud allows product managers and editorial administrators to ensure compliance, equity, and data privacy regulations.

Cons:

• The learning curve is a bit steep for the new users.
• The reports generated only have limited capabilities.
• The data analyst needs better customization options according to the business needs.

Pricing: Paid for Rs. 35,912.93/year/5 users

Website Link: https://www.sap.com/products/technology-platform/cloud-analytics/what-is-predictive-analytics.html

5. Sisense

Sisense is a machine learning predictive analytics tool that allows users to visualise and analyse data from different sources. It has a user-friendly interface to report and explore data.

Features:

• It can connect to various data sources like spreadsheets, cloud services, web applications, and databases.
• The data preparation tools can clean, transform, and shape data.
• Features for data security and governance can protect user’s sensitive data.

Pros:

• The chip methodology makes it the fastest data analyst.
• Business Intelligence is easy with this data analytics as it has great visualisation.
• As compared to other tools, it loads millions of data in fewer seconds.

Cons:

• The user may face issues with widgets, dashboards, and filters.
• The dashboard gets republished after every single change.
• Data cubes, Runs, and failures are unstable.

Pricing: Free or paid for $25000/year

Website Link: https://www.sisense.com/

6. TIBCO

TIBCO is a future-proof AI tool for forecasting and trend analysis. It can unlock real-time data, which makes decision-making smarter and faster. It unifies data for better control, access, and trust.

Features:

• The high-level metadata model allows heterogeneous metadata management.
• A data provisioning request initiates the creation of a materialised view for the third party.
• It has data discovery to define relations between data elements and metadata assets.

Pros:

• The dynamic dashboards and interactive visualisation make it easy to use.
• It provides mobile access across various platforms.
• Its integration with other software helps in deriving data.

Cons:

• Due to its high cost, it is suitable only for larger organisations.
• Simple one-click reports can easily form anything apart from needing to be detailed.
• It lacks embedded business intelligence and production reporting.

Pricing: $400/month (Basic) and $1500/month (Premium)

Website Link: https://www.tibco.com/connected-intelligence

7. MATLAB

MATLAB is an AI-based advanced analytics that creates a productive environment for engineers and scientists for visualisation, data analysis, and numeric computation.

Features:

• It develops a high-level programming language for complex mathematical operations and algorithms.
• Both the command-line interface and graphical user interface create an interactive environment.
• It is compatible with operating systems like Windows, macOS, and Linux.

Pros:

• The drag-and-drop features make it easy to use for non-coders.
• The online- community can be helpful at the time of any issue.
• It is also a great tool for visualisation of data.

Cons:

• It can be expensive for independent groups.
• The response on this tool can create hindrances while working on sensitive data.
• Many times, it has proven to be inefficient while performing basic functions.

Pricing:

• INR 16,250/year (Academic)
• INR 2,95,000/year (Start-up)
• INR 74,000/year (Standard)

Website Link: https://www.mathworks.com/products/matlab.html

8. Adobe Analytics

Adobe Analytics is one of the best tools for predictive analytics in 2024. It allows users to mix, match, and analyse data at any point in time and also provides users with in-depth analysis, predictive intelligence, and versatile reporting.

Features:

• There are multiple ways available for data collection from any source.
• The data-driven decision-making is possible through the web and mobile apps.
• The users can create and manage alerts based on data anomalies.

Pros:

• The user can create custom calculated metrics.
• Users can create an alert and also receive notifications when alerts are triggered.
• The users can build an automated report and usually receive it by Email.

Cons:

• This data analysis tool can be costly.
• The technical support services are not helpful.
• The Beginners find it hard to use as it requires a high level of expertise.

Pricing: Paid for $2000-$2500/month

Website Link: https://business.adobe.com/products/analytics/adobe-analytics.html

9. Akkio

Akkio is a data-driven decision-making tool with AI in 2024. It is easy to use to create, deploy, and manage machine learning models without the need for any knowledge of data science.

Features:

• The developers can drag and drop pieces of code or algorithms.
• Pre-built algorithms help users in simple model development.
• It supports programming languages like Java, Python, or C.

Pros:

• No coding is required in this platform, allowing anyone to create predictive models with data.
• The chat data prep feature allows users to use plain English in tables.
• Used in various industries like churn prevention, fraud defection, etc.

Cons:

• The stability level, reputation, and support are not equal to other well-established AI platforms.
• The predictions and number of models that a user can create can be limited.
• Due to the low level of flexibility, it provides fewer customization options to its users.

Pricing: Paid for $49/user/month (Basic), $99/user/month (Professional)

Website Link: https://www.akkio.com

10. Dataiku

Dataiku is an advanced AI solution for accurate predictive modelling. The purpose of this tool is to help users make better decisions relating to business.

Features:

• Both coders and non-coders can prepare their projects in a shared space.
• It has built-in features like data profiling, charting, and statistical analysis.
• The analytic dashboards and data products help users share day-to-day decisions with the business.

Pros:

• The users can monitor their tasks.
• The visualization tools like Tableau are integrated with it to provide graphs and plots.
• It provides services to both coders and non-coders.

Cons:

• It provides limited community support.
• When dealing with multiple data flows, it can get confusing.
• The non-coding template can lack in various parameters.

Pricing: Free or paid for$0.01/ year

Website Link: https://www.dataiku.com

AI Tools: Free vs. Paid for Predictive Analytics

Free AI predictive analytics tools offer basic features suitable for small-scale projects with limited budgets. They do not provide advanced functions to their users. On the other hand, paid AI predictive analytics tools have customization tools, comprehensive features, and a dedicated support team making them ideal for complex businesses.

Recommended AI Tool for Predictive Analytics – AzureML

The choice of the best AI tool for predictive analytics depends upon the user’s needs. BigQuery helps with large datasets, and AzureML offers a variety of algorithms and integration. Qlik has intuitive visualisation, SAP focuses on business integration, Sisense provides user-friendly analytics, TIBCO has real-time data, MATLAB is better for numerical computing, and Dataiku provides collaborative data science.

Conclusion

In conclusion, we can say that the above-mentioned 10 Best AI Tools for Predictive Analytics in 2024 are capable of enhanced data-driven decision-making for businesses. They can learn algorithms and predictive modelling and help in making informed choices. These AI tools open doors for more efficient predictive analytics.

10 Best AI Tools for Predictive Analytics – FAQs

Are there open-source options for predictive analytics?

Yes, tools like H20.ai provide open-source predictive analytics.

What trends can we expect in the future of AI tools for predictive analytics?

In the future there can be advancements in automated machine learning, with integration of AI tools in various industries.

How do these tools address ethical consideration in predictive analysis?

Many AI tools have features that provide transparency, and fairness to the users.

How do these tools handle big data in predictive analytics?

Some of the AI tools are specially built to handle predictive analytics on large datasets.