Managing data correctly is all about predicting the future. That’s what analytics is all about; analyzing trends in data so businesses can make better and more informed decisions that improve business processes.
Of course, this is easier said than done. Even if data is managed flawlessly, making accurate predictions about business metrics can still be incredibly difficult and, more importantly, time-consuming.
No one is a data wizard, but there are tools out there that can give you the magic you need to turn data into actionable insights that improve your business.
One such tool is predictive analytics software, which helps data analysts of all kinds see what past data says about the future.
While these tools can't tell you what will happen exactly, they can tell you what huge amounts of data say is likely to happen. And the data never lies.
What is predictive analytics?
Predictive analytics is a branch of advanced analytics that uses historical data, statistical algorithms, and machine learning to predict future outcomes. It uses patterns in past and present data to forecast potential future events, trends, or behaviors.
This process involves collecting and analyzing large datasets to identify relationships and trends, which can then be used to make predictions about future events. The goal is to provide insights that can help organizations make informed decisions, optimize processes, and anticipate challenges before they occur.
The core of predictive analytics lies in its ability to provide actionable insights by converting raw data into meaningful predictions. This can be done by humans, but most organizations nowadays turn to predictive analytics software to do the job for them.
How does predictive analytics tools work?
Predictive analytics software collects and processes data from various sources – including databases, spreadsheets, and online sources – and analyzes patterns, trends, and relationships in the data.
The software then creates a predictive model by training machine learning algorithms on historical data. This model is a mathematical representation of the relationship between the input data and the predicted output. Once the model is built, it can be used to make predictions on new or unseen data.
Predictive analytics tools continuously update the predictive model over time by incorporating new data as it becomes available. This allows it to provide more accurate and dynamic predictions in the form of dashboards, reports, or visualizations, enabling decision-makers to understand future risks, trends, or opportunities, and take appropriate actions accordingly.
Features of predictive analytics software
Predictive analytics software offers a range of features designed to analyze data, build models, and generate forecasts. Some features offered by the industry’s best software include:
1. Data Integration
Predictive analytics software can integrate data from multiple sources, such as databases, APIs, spreadsheets, and cloud platforms. This feature allows the software to gather and merge diverse datasets to generate comprehensive insights.
2. Data Preprocessing and Cleaning
Before building predictive models, the software provides data cleaning and preprocessing tools. This includes handling missing values, correcting errors, eliminating duplicates, and transforming data formats to ensure the dataset is clean, accurate, and suitable for analysis.
3. Advanced Statistical and Machine Learning Algorithms
The core of predictive analytics lies in the algorithms it uses. These algorithms can include regression analysis, decision trees, clustering, neural networks, and other machine learning techniques. The software applies these algorithms to find patterns and relationships in the data and build predictive models.
4. Automated Model Building
Many predictive analytics platforms feature automated model-building capabilities. The software can automatically select, train, and test multiple models, choosing the best-performing one based on criteria like accuracy and efficiency, which reduces the time and expertise needed to develop models.
5. Predictive Modeling and Scoring
Once the data is processed, the software can create predictive models based on historical patterns. These models are used to score new data, helping predict future behaviors, trends, or risks. The scoring system ranks or categorizes outcomes based on the likelihood of specific events occurring.
Best predictive analytics software tools
Whether you are a data scientist, analyst, or business leader, choosing the best predictive analytics software for your business is crucial for making data-driven decisions that improve your business.
Here are ten of the best analytics tools and solutions that help you get the data-driven insights you need to make better business decisions.10. Altair RapidMiner
Altair RapidMiner is a powerful predictive analytics platform known for its user-friendly interface and incredible ML-powered solutions for making the most out of data. The platform comes with a suite of data preparation, machine learning, and model validation tools, enabling users to seamlessly ingest, clean, and analyze large datasets. Its no-code and low-code environment also makes it ideal for organizations looking to democratize AI and machine learning across various departments without requiring extensive programming knowledge. For more advanced users, it supports integration with popular data science languages like Python and R to offer flexibility. For those with less technical know-how, it offers a drag-and-drop workflow for building predictive models, making it accessible to both novice and experienced data scientists.
With Altair, users can connect unstructured and siloed data sources, modernize analytics applications while supporting legacy systems, and expedite team collaboration to produce meaningful, high-impact results quicker and easier than ever before. The platform can automatically suggest relevant algorithms, optimize models, and handle feature engineering, drastically reducing the time it takes to develop high-quality predictive models. This, combined with built-in data visualization and reporting tools, allows users to quickly interpret and act on insights to make better business decisions.
Altair RapidMiner
Altair RapidMiner is a powerful predictive analytics platform known for its user-friendly interface and incredible ML-powered solutions for making the most out of data. The platform comes with a suite of data preparation, machine learning, and model validation tools, enabling users to seamlessly ingest, clean, and analyze large datasets. Its no-code and low-code environment also makes it ideal for organizations looking to democratize AI and machine learning across various departments without requiring extensive programming knowledge. For more advanced users, it supports integration with popular data science languages like Python and R to offer flexibility. For those with less technical know-how, it offers a drag-and-drop workflow for building predictive models, making it accessible to both novice and experienced data scientists.
With Altair, users can connect unstructured and siloed data sources, modernize analytics applications while supporting legacy systems, and expedite team collaboration to produce meaningful, high-impact results quicker and easier than ever before. The platform can automatically suggest relevant algorithms, optimize models, and handle feature engineering, drastically reducing the time it takes to develop high-quality predictive models. This, combined with built-in data visualization and reporting tools, allows users to quickly interpret and act on insights to make better business decisions.
Oracle Advanced Analytics
Oracle Advanced Analytics is a comprehensive predictive analytics tool designed to enable organizations to gain valuable insights from their data. It combines powerful statistical analysis, data mining, and machine learning capabilities, seamlessly integrated into Oracle's database and cloud environments. This integration allows users to analyze vast amounts of data efficiently, leveraging Oracle’s in-database processing to reduce the time and complexity typically associated with predictive analytics. With a user-friendly interface, Oracle Advanced Analytics empowers both data scientists and business analysts to build and deploy predictive models without requiring extensive programming skills, making it accessible for a broader range of users.
One of the key features of Oracle Advanced Analytics is its robust algorithm library, which includes a wide variety of machine learning techniques such as regression, clustering, and classification. Users can apply these algorithms to uncover patterns and make predictions based on historical data. The software also supports automated model building and evaluation, ensuring that organizations can quickly adapt their strategies based on evolving insights.
H20.ai
H2O.ai is a leading open-source predictive analytics platform that empowers organizations to harness the power of artificial intelligence and machine learning to derive actionable insights from their data. Founded with the mission to democratize AI, H2O.ai offers a suite of tools that facilitate data preparation, modeling, and deployment. Its key features include an intuitive user interface, automated machine learning (AutoML), and support for various algorithms, including deep learning, ensemble learning, and gradient boosting. Additionally, H2O.ai supports integration with popular data science languages such as R and Python, making it accessible for a wide range of users—from data scientists to business analysts.
The benefits of H2O.ai extend beyond its user-friendly interface and robust modeling capabilities. Organizations can achieve faster time-to-insight with its automated processes, allowing teams to focus on strategic decision-making rather than tedious data preparation tasks. The platform is designed for scalability, enabling users to process large datasets and deploy models in real-time, which is critical in today’s data-driven landscape. H2O.ai is also recognized for its commitment to transparency and interpretability, providing users with tools to understand model performance and predictions. These attributes, combined with its open-source nature, have positioned H2O.ai as one of the leading predictive analytics solutions available today.
Adobe Analytics
Adobe Analytics is a powerful predictive analytics tool that enables businesses to gain deep insights into their customer behaviour and optimize their marketing strategies. Part of the Adobe Experience Cloud, the platform provides a comprehensive suite of features designed to track, analyze, and visualize data from multiple sources, including web traffic, social media, and mobile applications. It comes with tools for real-time data analysis, advanced segmentation, predictive modelling, and customizable dashboards, using ML algorithms to forecast customer trends and behaviours and allow businesses to make data-driven decisions that enhance customer experiences and drive growth.
The true advantage of Adobe Analytics lies in its ability to integrate seamlessly with other Adobe products, such as Adobe Experience Manager and Adobe Target, to create a holistic ecosystem for managing customer experiences. This integration allows for richer insights and more targeted marketing campaigns by enabling teams to easily track key performance indicators (KPIs) and visualize data trends. Recognized for this versatility, Adobe Analytics is considered one of the best predictive analytics solutions on the market, helping organizations across various industries to better understand their customers and drive strategic initiatives.
SAS VIYA
SAS Viya is an end-to-end predictive analytics platform that not only fulfils the promise of AI but also brings you the speed and productivity you never imagined possible. Designed on a cloud-native architecture, the platform offers a suite of AI-powered tools that cater to a wide range of analytical needs, from data preparation and visualization to predictive modeling and deployment. You can deploy debut decision flows, automate performance monitoring, tune for peak performance, and retrain predictive models for fast iteration. SAS Viya also scales at the pace of AI. You won’t sacrifice performance or need to provision new hardware to run your models as your projects become more complex.
SAS Viya integrates with open-source languages, such as Python and R to facilitate collaboration between users with different skill sets, making it a versatile choice for teams. The platform also emphasizes governance and security, ensuring that data is handled responsibly and in compliance with regulatory standards, and provides automated machine-learning capabilities that streamline model development, allowing users to focus on interpreting results and making data-driven decisions. These features position SAS Viya as one of the best predictive analytics solutions on the market, trusted by organizations globally to drive strategic initiatives and enhance business outcomes.
Amazon Quicksight
Amazon QuickSight is a business intelligence service from Amazon Web Services (AWS) that enables organizations to visualize their data and derive actionable insights through predictive analytics. Designed for scalability and speed, QuickSight allows users to create interactive dashboards and reports quickly without the need for complex setups. You can connect to a wide range of data sources, including AWS services like S3, Redshift, and RDS, as well as third-party databases. It also advanced visualization options, machine learning insights, and natural language query capabilities, enabling users to explore data intuitively and generate predictions without needing deep technical expertise.
The benefit of Amazon QuickSight lie in its cost-effectiveness and accessibility. Its pay-per-session pricing model allows organizations to control costs while leveraging the full power of the service. QuickSight also supports automatic scaling, meaning it can handle large datasets and a growing number of users seamlessly. Additionally, the service integrates with other AWS offerings, enhancing its functionality and enabling users to build comprehensive analytics solutions within the AWS ecosystem. With its focus on performance, ease of use, and powerful analytics capabilities, Amazon QuickSight is recognized as one of the best predictive analytics solutions available today, empowering businesses to make data-driven decisions and optimize their operations effectively.
SAP Analytics Cloud
SAP Analytics Cloud is a powerful predictive analytics platform that combines business intelligence, augmented analytics, and enterprise planning in a single solution. Designed to enhance data-driven decision-making, SAP Analytics Cloud provides users with an intuitive interface for visualizing data, creating interactive dashboards, and generating insightful reports. Key features include advanced data modeling capabilities, automated machine learning algorithms, and the ability to integrate seamlessly with various data sources, including SAP and non-SAP systems. The platform also offers natural language processing (NLP) capabilities, allowing users to ask questions in plain language and receive meaningful insights in response.
By enabling collaboration across teams, Sap Analytics Cloud helps organizations align their strategies and operational plans effectively. Its cloud-based architecture ensures that users can access data and analytics from anywhere, facilitating remote work and real-time decision-making. It also emphasizes security and compliance, providing robust data governance features that ensure sensitive information is protected. With its focus on delivering actionable insights and fostering collaboration, SAP Analytics Cloud is considered one of the best predictive analytics solutions on the market, empowering organizations to harness the power of data to drive strategic initiatives and enhance performance.
Microsoft Power BI
Microsoft Power BI is a leading business analytics tool that enables organizations to visualize their data and share insights across the enterprise or embed them in an app or website. Power BI combines a user-friendly interface with powerful analytical capabilities, allowing users to create interactive reports and dashboards from a wide array of data sources, including Excel spreadsheets, cloud services, and on-premises databases. It coms with predictive and advanced data modeling, natural language querying, and AI-driven insights, which help users to uncover patterns and trends in their data without requiring extensive technical knowledge.
Microsoft Power BI is accessible for businesses of all sizes, especially those already using the Azure ecosystem. The platform's integration with other Microsoft products, such as Azure and Office 365, enhances its functionality and enables users to leverage existing tools and data seamlessly. Power BI also offers robust collaboration features, allowing teams to share insights and work together in real-time. With its blend of ease of use, powerful analytics capabilities, and integration with the broader Microsoft ecosystem, Power BI is among some of the best predictive analytics tools available today.
Alteryx
Alteryx is an end-to-end cloud analytics platform that transform data into insights with self-service data prep, machine learning, and AI-powered analytics. The platform delivers predictive analytics within a complete analytics workflow, combining data access, preparation, modelling, and sharing of analytic results in one easy-to-use platform. It also allows teams to build predictive models without requiring extensive programming knowledge, providing a range of analytics templates to help you learn how to use the low-code, no-code tools in Alteryx to predict customer spending, make time series forecasts, and optimize your pricing. This makes it easy to build an analytics culture within your organization and uncover valuable insights and trends from your data.
What makes Alteryx so great is its ability to streamline workflows and enhance collaboration among data teams. By automating repetitive data preparation processes, the platform significantly reduces the time needed to generate insights, allowing users to focus on analysis and strategic initiatives. The platform’s huge community and extensive library of pre-built tools and templates also facilitate knowledge sharing and quick implementation of analytics solutions. This focus on user empowerment, paired with the platform’s ease of us and powerful analytical capabilities, make Alteryxone one of the best predictive analytics solutions available today.
Tableau
While Tableau is known for its flexible front end and intuitive visual interface, many data scientists now use Tableau for advanced analytics and predictive modelling. With unique features such as a built-in dashboard and a user-friendly design that is intuitive and requires no scripting knowledge, the platform helps users complete sophisticated analytics projects in a fraction of the time compared to manual methods. It offers rich features that enable users to perform iterative analysis and comparison of data segments, including a predictive modelling feature that allows users to leverage powerful statistical models to build and update predictive models efficiently. It also gives users the flexibility to select their predictors, collaborate on the model results within other table calculations, and comprehend and examine a large volume of data. All this in a drag-and-drop interface that’s easy to use for everyone within the organization – data analyst or not.
Tableau facilitates collaborative decision-making by allowing teams to share dashboards and insights easily across the organization. Its ability to handle large volumes of data efficiently ensures that users can work with real-time data, allowing teams to seamlessly uncover trends in their data and make smarter decisions. With its focus on delivering intuitive visual analytics and fostering collaboration, Tableau is widely regarded as one of the best predictive analytics solutions available, enabling organizations to make data-driven decisions that enhance performance and drive growth.