20 Best Predictive Analytics Software for Data-driven InsightsWhether you're a small startup looking for data analytics tools for free or an established enterprise, these best predictive analytics software will provide the best data-driven insights to make informed decisions.
Predictive analytics software is increasingly vital to modern business operations. By crunching data, predictive analysis software, with the help of AI, can identify trends and patterns in customer behavior and market fluctuations.
This practice helps organizations improve decision-making, save costs, reduce risks, and increase revenues. In this article, we will discuss the best predictive analytics software available in the market today. So, without further ado, let's get started!
Best Predictive Analytics Software for Improved Decision-Making in 2023
These predictive analytics software solutions have been ranked based on customer feedback, ease of use, affordability, scalability, and accuracy to provide the best predictive analytics software available.
If you find one that fits your needs better, feel free to make your own decision. Read on to learn more about the top predictive analytics software.
Speaking about predictive analytics software, Altair is a great option. One of its AI products, Monarch, is a desktop-based, self-service data preparation system that offers easy access to clean data and data blending. Moreover, they also provide HyperWorks, which drives the product lifecycle from concept design to detailed product development.
Additionally, Altair has OptiStruct in their product lists, an industry-proven structural analysis solver for linear and non-linear problems under static or dynamic loadings, while HyperMesh provides a high-performance preprocessing environment for the most significant models. Also, You can look for more predictive analysis tools from their suite of software solutions.
Notable features of Altair:
- Offers predictive solutions to fit any size organization
- Includes a comprehensive suite of predictive analytics software
- Easy access to clean and blend any type of data with Monarch
Domino Data Lab
On the second recommendation, consider Domino Data Lab. It is one of the best tools for predictive analytics that enables teams to quickly build, share, and manage models in one place. This makes it easier to track model performance and simplifies deploying industry-level models.
Moreover, you can use their cloud platform or on-premise installation for team collaboration with tools like automated deployments, project management, and model monitoring. Moreover, when it comes to scalability, it provides the ability to scale your predictive models as needed without needing extra maintenance.
Notable features of Domino Data Lab:
- Easy deployment of industry-level models
- Ability to manage models in one place
- Automated deployments, project management, and model monitoring
- Ability to scale predictive models as needed
SAP Analytics Cloud
Who doesn't know SAP Analytics Cloud? It is one of the best predictive analytics tools free that helps businesses get insights from their data. This powerful tool is a cloud-based software with predictive analytics, predictive model planning, and predictive document capabilities. This software also provides various data representations for presentation purposes and multiple planning tools and tasks to create data.
On top of that, its mobile application allows users to access analytics from anywhere while users can use Artificial Intelligence (AI) to predict future results. Thus, predictive analytics business is easy to achieve with SAP Analytics Cloud.
Notable features of SAP Analytics Cloud:
- A Cloud-based software for faster computation
- Multiple planning tools and tasks to create data
- Access analytics from anywhere with the mobile application
- Users can use Artificial Intelligence (AI) to predict future results
You can rely on Alteryx, a predictive analysis software, to manage big data. It is a powerful predictive analytics and AI platform that organizations use to perform predictive analysis, predictive modeling, and predictive reporting.
Whether it's data preparation, predictive model development, or predictive visualization, Alteryx offers an integrated suite of applications to handle all tasks efficiently. What's more? Predictive insights are delivered in easy-to-understand visualizations that users can share with stakeholders. This one of the best predictive analytics tools free from Alteryx will provide you with the insights you need.
Notable features of Alteryx:
- Integrated suite of applications for predictive analysis, modeling, and reporting
- Delivery of predictive insights in easy-to-understand visual
- Powerful predictive analytics and AI platform
With our strategically designed marketing solutions
Discovering Qlik Sense, it feels like you have hit the software goldmine! It is a software for predictive analytics that provides complete access to advanced predictive analytics. It allows users to prepare data, build models, visualize, and monitor their outcomes over time. Users can easily use this software for reporting, visualization, and contextual analysis of complex datasets.
With the help of Qlik Sense, you will be surprised by the generated results. So, if you are looking for software to help you with predictive analytics in big data, this is one of the best software tools available.
Notable features of Qlik Sense:
- Comprehensive software suite providing access to advanced predictive analytics
- Ability to prepare data, build models, visualize, and monitor outcomes
- Ability to report, visualize and contextualize complex datasets
IBM Watson Studio
When looking for software for predictive analytics, IBM Watson Studio is one of the best options. It offers various features and integrations with other data tools, enabling predictive analytics operations. The product has an intuitive interface that is easy to understand for beginners and allows users to manage AI models effectively.
Regarding the software with data analytics tool list features, IBM Watson Studio provides data analysis, data science, deep learning, object storage, and more. IBM Watson Studio is an excellent choice if you want software that can offer efficient predictive analytics in big data.
Notable features of IBM Watson Studio:
- Wide range of features and integrations with other data tools
- Intuitive interface easy to understand for beginners
- Ability to manage AI models effectively
- Cost management capabilities, improve business process agility and outcomes, compliance, and risk management
No more feeling dizzy while looking for a data analytics tools list. With the help of Databricks, you can conveniently manage predictive analytics in big data. It is a software for predictive analytics that allows users to analyze and collaborate on data at scale quickly.
Databricks is well known for product functionality, performance, strong consulting partnerships, and services expertise. Moreover, the data lake house architecture of Databricks helps take analytic capabilities up a level; job and code management is easy with the newly designed interface. Choices for scaling vertically/horizontally are available through cloud provider connectivity.
Notable features of Databricks:
- Data platform allowing to analyze and collaborate of data at scale
- Product functionality, performance, strong consulting partnership, and services expertise
- Data lake house architecture helps take analytic capabilities up a level
- Job and code management is easy with the newly designed interface, and options for scaling vertically/horizontally are available through cloud provider connectivity
Making a summary of predictive marketing analytics is easier than ever with the Board. It is a data analytics tool that helps monitor, plan, and summarize a company's most important financial and economic aspects.
The intuitive interface makes it easy to create well-organized reports without advanced knowledge. On top of that, it is integrated with all the data sources used by a company. It has an intuitive interface that makes predictive analytics easy for anyone without advanced knowledge.
Notable features of Board:
- Comprehensive data preparation & predictive analytics capabilities
- Ability to monitor, plan and summarize a company's most important financial and economic data
- An intuitive interface that makes it easy to create well-organized reports without advanced knowledge
- Basic concepts for creating more complex solutions supporting activities from financial management to sales forecasting
This data science platform provides comprehensive support for the analytics lifecycle, including model building, data engineering, trust and transparency of AI models, collaboration, and governance. RapidMiner is a powerful data mining software used by data scientists & analysts in various industries. It is used to capitalize on Industry 4.0 initiatives, improve risk management, optimize patient care, innovate with consumer, vehicle, and factory data, and digitally transform customer journeys.
With RapidMiner, you will have a data analytics tools list that is complete and ready to use for data-driven decisions within an organization.
Notable features of RapidMiner:
- Comprehensive data analytics platform for data science lifecycle
- Ability to improve risk management, optimize patient care and innovate with data from consumers, vehicles, and factories
- Support data-driven decisions within the organization
DataRobot stands out with its end-to-end data platform and ability to bring together disparate data and users across the entire AI lifecycle. Earning itself a good position in the data analytics tool list.
DataRobot provides an enterprise-grade solution that simplifies data science processes by automatically building, deploying, monitoring, and maintaining machine learning models. Furthermore, data scientists can collaborate seamlessly with data engineers, IT operators, and business analysts to ensure data security and robust predictive capabilities and secure the models' scalability.
Built for multi-cloud usage, DataRobot is designed to run on any combination of public clouds, data centers, or at the edge.
Notable features of DataRobot:
- End-to-end data platform to bring together data and users across the AI lifecycle
- Automatically build, deploy, monitor, and maintain machine learning models
- Multi-cloud usage to run on any combination of public clouds, data centers, or at the edge
Still tight on budget? Fret not, because Google Cloud provides data analytics free tools that support predictive analytics and data-driven decisions within organizations through its free trial. The platform offers data services such as BigQuery, Data Studio, and Cloud Dataprep for data engineering, Machine Learning APIs for data mining, and much more.
These capabilities allow you to create fool-proof predictive analysis of critical KPIs. The AI Platform provides a suite of data analysis tools, data processing services, and engineering solutions for predictive analytics businesses.
Notable features of Google Cloud:
- Comprehensive data platform allowing to analyze and collaborate of data at scale
- Provides a suite of data analysis tools, data processing services, and data engineering solutions
- 90-day trial with $300 free credit to take advantage of data analytics free tools
Are you looking for software that provides accessible predictive analytics and data analytic tools for data visualization? Tableau is an option, and it comes with a popular data analytics tools list to generate data visualization. With its drag-and-drop interface, users can easily do visuals and calculations. Even those who don't know about analytics can understand data with this platform. Users can create dashboards and worksheets with Tableau to produce data analysis and visualization.
Notable features of Tableau:
- Free data analytics tool for data visualization, from simple to complex data
- Drag and drop interface helps in visuals & calculation
- Dashboards & worksheets are created for predictive data analysis & visualization
- Can be understood by anyone who doesn't have any knowledge of analytics
SAS Advanced Analytics
You can consider SAS Advanced Analytics as a data analytics tool in your best predictive analytics tools list. SAS Advanced Analytics provides users with statistical analysis, predictive modeling capabilities, and data mining functions that can be used to analyze data from structured and unstructured sources.
Examples of SAS Advanced Analytics products include Base SAS, SAS/STAT, SAS Studio, and SAS/GRAPH. Thus, data scientists and analysts can easily access data, discover insights, combine data sources, and develop models with the help of this data analytics tool.
Notable features of SAS Advanced Analytics:
- Statistical analysis & predictive modeling capabilities
- Data mining functions used to analyze structured & unstructured data
- Easily access data, discover insights, combine data sources & develop models
- Products from the suite are available a la carte or in bundles, such as SAS Analytics Pro
While looking for data analytics software tools with predictive modeling capabilities, the KNIME data analytics platform certainly deserves a place in the best data analytical software list. KNIME is an open-source data platform for data preparation and machine learning.
It supports data scientists, engineers, IT operators, and business analysts & ensures data security & scalability of the models with flexible deployment options from cloud to on-premise usage. Additionally, data scientists can take advantage of automation & reuse capabilities to reduce data preparation time and increase their efficiency in data exploration.
Notable features of KNIME:
- Open source data platform for data preparation & machine learning
- Automation and reuse capabilities to reduce data preparation time and increase efficiency
- Flexible deployment options from cloud to on-premise usage
- A great user interface for data overview and usability, even for less tech-savvy users
You can also consider Amazon Forecast predictive analytics models software that uses machine learning to deliver accurate forecasts. Thus, creating accurate estimates for businesses can be quickly done with the help of these data analytics software tools. It uses historical data (price, promotions, economic performance metrics) from web services, and data from IoT devices to create predictive models for businesses. On top of that, data scientists can take advantage of data visualization for data exploration & data modeling with Amazon Forecast.
Notable features of Amazon Forecast:
- Fully managed service uses machine learning to deliver accurate forecasts
- Uses historical data from web services and IoT devices to create predictive models
- Provides data visualization, making it beneficial for predictive marketing
Adobe Analytics is a cutting-edge predictive analytics software renowned for its advanced capabilities in delivering actionable insights from vast data sets. As a part of the Adobe Experience Cloud, it empowers businesses by giving detailed predictions of future outcomes. Executives can assess these predictions to make data-driven decisions, optimize customer experiences, and enhance overall performance.
This predictive software leverages Adobe Sensei integration to unlock the core capabilities of Big Data at unprecedented speeds. This predictive analytics platform uses high-end AI and machine learning algorithms to uncover future scenarios with past patterns.
Notable features of Adobe Analytics:
- Anomaly detection with statistical modeling
- Contribution analysis to unearth hidden patterns within your data
- Intelligent alerts to report anomalies beforehand
- Ad hoc analysis to create customized projects
JMP’s predictive analytics tools are not your everyday Joe that just fulfills your basic needs. Their predictive software uses deep knowledge of AI/ML to create solutions that propel your decision-making game.
JMP’s predictive and data analytics software tools (JMP pro) use modern techniques like regression, neural networks, and decision trees that allow you to create better models and make better decisions. The software also uses many machine learning methods and algorithms to enable a simple and effective model that generates insights faster.
Notable features of JMP Pro:
- Uses Predictive Modeling and Cross-Validation to avoid overfitting
- Repairable Systems Simulation to manage system repair, downtime, and cost incurred
- Reliability Block Diagrams to fix weak spots and predict future system failures
Minitab Statistical Software
In the conversation of predictive analytics solutions, we have to include Minitab Statistical Software. This one of the best tools for predictive analytics analyze current and past data to uncover trends, predict patterns, unravel anomalies and identify hidden relationships between variables. Minitab Statistical Software leverages open-source languages like R or Python to ensure future scalability and integrate ML algorithms such as Classification, Regression, and Decision trees to boost your capabilities further.
Notable features of Minitab Statistical Software:
- Complete predictive analysis tools to glean important insights from your big data
- Powerful reporting with Graph Builder to get multiple graph options for the same data set
- Easy to use software even for non-tech enthusiasts
- 24x7 support for better customer service
Oracle Crystal Ball
Oracle is a company everybody knows. Whether you're an IT enthusiast or not, Oracle is a name that is hard to avoid. Just as the company has taken almost every aspect of computer technology under its wing, predictive analytics has followed suit.
Oracle Crystal Ball is a spreadsheet-based predictive analytics solution delivering forecasting, simulation, and optimization services. The predictive software features a decision optimizer that allows users to generate insights based on past data and make strategic business decisions. You can get a glimpse of the Oracle Crystal Ball with a free trial.
Notable features of the Oracle Crystal Ball:
- The complete package includes an Oracle crystal ball and a decision optimizer for insight generation
- Powerful risk analysis and uncertainty management
- Provides deployment of Oracle Crystal Ball within the shortest time possible
- Easy-to-use reporting and dashboarding features
FICO Predictive Analytics
Want scalability of open source and the quality of a patented AI technique? If yes, then FICO Predictive Analytics is the one for you. The predictive analytics platform by FICO develops and deploys predictive models that promote data-driven decision-making with intelligent and reliable insights.
FICO Predictive Analytics features a rich patent portfolio to create state-of-the-art machine learning models. Moreover, it also enables you to perform What-if analysis and simulations to forecast outcomes so that you can take necessary actions.
Notable features of FICO Predictive Analytics:
- Easy-to-use dashboards that give insights at a glance
- Provides the lowest latency and highest precision event processing
- Integration with best open-source tools for better flexibility
That Promote Your Product's USPs
What is Predictive Analytics Software?
Predictive analytics software is a sophisticated tool that uses AI and ML algorithms to study historical data patterns and forecast future outcomes. Predictive software ingests pools of data (structured and unstructured data) from various sources and processes it via complex statistical and machine-learning models.
Why Use Predictive Analytics Solutions?
There are several reasons for using predictive analysis tools for your business. Businesses need to think ahead and to do that, they first need to evaluate the past to study patterns and trends that can give insight into the future. This is exactly where predictive analytics benefits the organization. Let’s explore some reasons for using predictive analytics for better automation and insight generation -
The traditional method of finding patterns and forecasting outcomes was mainly manual. Which meant these activities were time-consuming and were largely based on guesswork. Predictive tools take significantly less time for these activities. Moreover, the predictions generated through Predictive Analytics Software are backed by data.
2. Reduce chances of errors
It's no secret that manual data inputs and analyses are prone to errors and unreliability. Whereas, with automated predictive analytics software, executives become free of the menial tasks of data entry into a system to draw out conclusions. Predictive software leverages the capabilities of digital automation and predefined tools to generate clear and reliable results.
3. Risk Management and Fraud Detection
Predictive analytics is largely beneficial in identifying potential risks and detecting fraudulent activities in real-time, enabling businesses to mitigate risks and enhance security measures. These programs can analyze the behavior and purchase patterns of a customer and detect any suspicious activity which might be considered an anomaly. Fraud detection with predictive analytics is widely popular in banking and finance.
Who Uses Predictive Analytics Software?
With the benefits and use cases of predictive analytics and AI increasing every passing day, the applications of such software are also spanning across industries, departments, and countries. Today, organizations use predictive analytics in a nearly endless number of ways. Below are some of the sectors and departments where predictive analytics proves its worth -
- Finance and banking
- Marketing and Advertising
- Retail and E-commerce
- Manufacturing and Supply Chain
Kinds of Predictive Analytics Software
Predictive analytics uses different methods and techniques to deliver compelling results viable to businesses. Here are some of the kinds of predictive analytics that are largely used in the industry -
- Regression Analysis: Regression is a widely used analysis technique that examines the relationship between dependent and independent variables. It finds key patterns in big data sets and determines how one variable can influence the movement of an asset. Regression Analysis is used to predict numerical outcomes and quantify the strength of dependency between variables.
- Decision trees: Decision trees refer to a schematic, tree-shaped diagram that defines a course of action or shows a statistical probability. As the name suggests, a decision tree has a tree-like structure, with each branch depicting a choice between several alternatives. It helps us choose the best path by evaluating different factors at each step. If we’re talking about predictive analytics, decision trees work by analyzing data and creating a tree-like structure of decisions based on specific features.
- Neural networks: Neural networks are powerful techniques capable of modeling extremely complex relationships. These powerful algorithms are revolutionizing the field of predictive analytics by mimicking the brain's ability to learn, adapt, and make complex decisions. Through "deep learning," neural networks can automatically learn intricate patterns and correlations within massive datasets. The more data they're fed, the smarter these networks become.
- Time Series Analysis: Time series analysis aims to analyze data sets collected over time to identify patterns and trends. It is commonly used for forecasting future values based on historical data.
Potential Issues with Predictive Analytics Software
No good thing is only good. The same goes for predictive analytics also. Despite the mountains of benefits that AI technology offers its clients, some drawbacks still make executives question their capabilities for a moment. Let’s explore some of the limitations of predictive analytics.
- Bias and Fairness: Predictive analytics can perpetuate biases present in historical data, leading to unfair and discriminatory outcomes.
- Data Quality: Inaccurate or incomplete data can adversely impact the accuracy and reliability of predictions.
- Overfitting: Overfitting occurs when models perform well on training data but fail to generalize to new data, resulting in poor predictions.
- Interpretability: Complex predictive models like neural networks usually lack transparency. Thus, making it challenging to explain their decisions.
- Privacy Concerns: Predictive analytics may involve sensitive data, raising privacy and security issues if mishandled or accessed by unauthorized individuals.
In summary, predictive analytics is now a necessity more than a preferred tool to have in your grasp. With market dynamics always changing, predictive analytics allows you to gaze into the future and evaluate your options to make decisions backed by statistical data. Predictive analytics is being used more and more every day. Even after the debate of business intelligence vs. predictive analytics is still going over the engineers, the benefits of predictive analytics software cannot be overlooked anymore.
Moreover, besides understanding what is predictive analytics, business owners also need to consider their business needs & budget as they decide on the right data analytics software tools for their business.
If you are a developer, a company, or someone with a finished product or have a soon-to-be-released app, send an email to MobileAppDaily, and list your product by exceptionally talented app experts. Visit our website to see all the new and intriguing content we publish daily. Sign up for our newsletters to learn more about MobileAppDaily.
We hope this overview of popular data analytical software tools can help you make the best decision for your business!
What is predictive analytics?
Predictive analytics falls under the data analytics umbrella that utilizes AI algorithms and machine learning (ML) techniques to make predictions about future outcomes. Predictive analytics studies historical data patterns fed into the program and uses various models and methods to make predictions to identify corrections, patterns, and relationships between these datasets.
Why is predictive analytics important?
As consumer demand is changing like ever before, businesses need to put extra effort into monitoring several aspects of consumer behavior, sales patterns, and purchase history to create more personalized experiences for their customers. Moreover, to survive in a competitive landscape, companies also need to be a foot ahead of their competitors to gain a competitive edge. They can achieve this edge by predicting future trends and opportunities to get the first-mover advantage.
Here are some major reasons that solidify the importance of predictive analytics in today's world -
- Enhance supplier networks
- Provide deep customer insights for better relationship management
- Predicting churn and Customer Retention
- Helps in making revenue projections and budgeting decisions
How much does predictive analytics software cost?
Every good thing comes at a price, and predictive analytics software is no different. Predictive analytics is no piece of cake, and the price for integrating this technology reflects in its demand and average budget.
The prices for predictive analytics software have been soaring for the past few years. However, by knowing your core requirements, you can choose a predictive solution that suits your needs and doesn't burn a hole in your pocket.
As of 2023, the price for an effective predictive analytics solution can range anywhere from $1000 per year to $10,000. The quotations largely depend upon the size of your big data and no of users needed.
What's the difference between predictive analytics and machine learning?
Predictive analytics and machine learning come from the same family but differs a ton in their core purposes and functionalities. Let's take a look at these distinctions.
Predictive analytics is a vast concept that involves using historical data, statistical algorithms, and data mining techniques to predict future events. It aims to uncover patterns and relationships in data to make informed predictions about what might happen in the future.
Meanwhile, Machine learning is a part of the predictive analytics ecosystem. ML includes using algorithms and statistical models to enable computers to learn automatically and improve their performance on a specific task without additional programming by an engineer.
What is the difference between Business intelligence vs Predictive analytics?
Though objectives and tasks of business intelligence and predictive analytics often overlap, there are several distinctions that can help you get a clear understanding between the two. Let's take a look at Business intelligence vs predictive analytics -
- Business intelligence is about performing descriptive analytics to gain insights and understand what has happened and why. In contrast, predictive analytics is about discovering patterns in historical data to forecast future outcomes.
- Business Intelligence helps in data-driven decision-making by providing insights into current performance via data visualization. Predictive Analytics, on the other hand, assists in proactive decision-making to better plan and strategize future business decisions.
- BI typically works on structured or processed data to prepare results and dashboards. However, predictive analytics can work with structured and unstructured data using machine learning and statistical algorithms.
She is an avid writer of technology and trending mobile apps. When she is not busy updating you about the tech world, she spends time reading books and playing guitar.
your Product’s growth