Exploring the Top Data Science and Machine Learning (DSML) Platforms of 2022  by@priya11

Exploring the Top Data Science and Machine Learning (DSML) Platforms of 2022

This blog discusses the top 20 DSML platforms for 2022, their capabilities, technologies, and organizational adaptability. Read on.
Priya Kumari HackerNoon profile picture

Priya Kumari

Priya has 8 yrs of exp. in Research & works as AM-Content Strategy at Valasys Media, a top B2B Media Publisher company.

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The data science and machine-learning platforms of modern times are popular software products that have been designed to help companies develop and deploy data science and machine learning solutions. 

According to Gartner, data science and machine learning platforms can be defined as, "A cohesive software application that offers a mixture of basic building blocks essential both for creating an array of data science solutions and incorporating those solutions into the business processes, surrounding infrastructure, and products…"

Machine learning can be considered to be a popular subset of data science that guarantees specific attention when evaluating these platforms. Learning about the specific Data Science and Machine Learning (DSML) platforms helps businesses choose the right platforms to address their dynamic business requirements and accelerate product development

As of January 2021, Gartner’s Magic Quadrant for Data Science and Machine Learning Platforms looked as follows: 

Also, according to Gartner, the AI & data science platform market is anticipated to grow over $10 billion by the year 2025 at a phenomenal CAGR of 21.6%.

This growth projects the utility of the DSML platforms for enterprises of all kinds and speaks volumes about the platforms, functionalities that each vendor must prioritize, key trends in the market to be mapped, and more. Also, owing to the ever-increasing utility of the DSML platforms organizations of all shapes, sizes, and forms across the globe are increasing their investment in the DSML platforms.

Top Players in the DSML Market 

The field of DSML platforms is very crowded and competitive, and Gartner recently examined and named the top 20 players in the DSML market to help marketers source data, build models and operationalize machine learning models. 

In 2022, the data science and machine learning market will continue to be driven by new technologies — including generative adversarial deep learning (GADL), artificial intelligence chatbots, and cognitive computing. 

Let's have a look at the top 20 DSML platforms for 2022, their capabilities, technologies, and services used by organizations to transform their business through the use of AI solutions:

1.Matlab by MathWorks 


Matlab by MathWorks - MATLAB offers a lot of communication. It allows for sequences, matrices, and inputs to be easily defined. 

Matlab is a platform for programming, problem-solving, and data analysis. It offers many useful features that make it possible to find the answers to questions in an easy way.

The programs can be used in solving mathematics and science problems. Many arithmetical and logical questions are simple to solve and take only a few seconds. It provides powerful tools in programming and data visualization as well as comprehensive libraries of functions that can be extended with user-written functions, making it suitable for a wide range of applications. MATLAB provides an interface where you can visually interact with your data.

2.Alteryx Designer by Alteryx 


Altertyx Designer is an intuitive platform that makes it easy to get up and running in the cloud. This allows users to easily build and deploy models. The interface displays the performance of the model as it runs and shows how much time each component took to perform. With natural language processing (NLP), you can build models for data integration, text analytics, sentiment analysis, sentiment classification, and text classification.

The platform is a set of tools that allows you to quickly and easily bring your data into an Alteryx platform and start connecting the dots. The result? Data visualization, data cleansing, and predictive analytics.

 Altertyx data integration software is fantastic. If you are not a large company with a high-level IT department, the UX of Altertyx Designer Standard Edition is one of its biggest advantages. The design and visualization interface is clean, and it's incredibly easy to use. On top of that, its rapidity is astounding. Its simplicity of use, along with outstanding rapidity in the creation of complex models, were two of its biggest strengths because the DSML platform takes many hours to learn and master.

3.IBM SPSS Statistics by IBM 


IBM SPSS Statistics is a business process management software that makes it possible to collect data from a variety of sources and transform the data into target variables in order to produce information that is meaningful.

It provides statistical analysis tools for business intelligence which includes the following areas: 

The IBM SPSS Statistics contains PowerPivot which is an Excel add-in that processes data and transforms it into the tabular format with new features for data exploration, analyst calculations, and ad hoc reporting. IBM also provides access to other databases through a direct DB2 interface. 

The IBM SPSS Statistics functions are capable of running any type of statistical analysis needed by the user, regardless of its complexity. By using IBM's SPSS Statistics, the computer scientist has great flexibility in performing complicated calculations without having to learn multiple systems because it runs under several different operating environments. Some examples of the capabilities that IBM SPSS Statistics provides include running descriptive statistics, statistical tests, regression, and even certain predictive analyses.

SPSS Modeler is the author's work, the IBM SPSS Statistics is a well-compiled data analytics solution that allows us to run our new business ideas through it and get predictions of the outcome depending on the parameters that we set for it in a friendly tone.

4. RapidMiner Studio by RapidMiner 


RapidMiner is amongst the most powerful and intuitive data science software that most companies can afford today. With RapidMiner’s Alpha technology, you can access all types of data in business intelligence tools your company already uses, such as Tableau, Qlikview, and Excel.

With RapidMiner Studio you can easily train, validate and deploy your model. The intuitive drag-and-drop interface lets you create a custom data pipeline from scratch or reuse existing models.

5. Dataiku


Dataiku provides you with an analytics platform that enables data scientists to leverage the power of their latest technology by delivering best-in-class, real-time results to help them uncover insights in minutes, not months.  Dataiku is the leading platform for data management and analytics. Fast, agile, reliable, and easy to use, it offers a single integrated, modern solution to all your data management needs.

Dataiku has provided our team with a scalable, performant, and effective analytics platform that allows us to focus on what we do best - building great products. Dataiku helps enterprises streamline their data team and enhance their capabilities around analytics.

6. DataRobot AI Cloud Platform by DataRobot


The DataRobot AI Cloud Platform is a comprehensive data science platform that supports the implementation of real-time machine learning, predictive analytics, and data management to actively improve business processes. This tool is considered among the best to automate all the complicated and mundane data science operations. 

DataRobot AI Cloud Platform is the first branded AI platform that provides personalized AI services to all Healthcare companies, Hospitality businesses, and Finance companies in only one click. DataRobot helps in personalizing user experience by analyzing data from sources like usual data collection and it automatically generates products that help clients to reach their target audience.

This one is a powerful and scalable open platform for enterprises to get started with artificial intelligence as quickly and easily as possible. It provides key components for building AI solutions: The DataRobot AI Cloud Platform gives you the necessary tools to start building AI-powered applications, such as Natural Language Processing, Vision, Deep Learning, and more. One can even create a series of intelligent applications with a broad range of features. It's easy to deploy, configure and scale for local workloads.

7. Base SAS by SAS


This solution is made for Data Scientists who want to utilize SAS for their Machine Learning projects. It speeds up the task of importing and poring data, so there’s no preprocessing or otherwise separating data sets.

Base SAS by SAS is the most common operating system used in research and development. The standard software provides users with many benefits, including easy and fast installation.

All the leading predictive analytics companies are constantly looking for new ways to help our clients bring data to life. If one is passionate about Data Science and machine learning, Base SAS is an easy-to-use product that delivers fast performance with an intuitive interface. It was designed with simplicity in mind — we want to make it easier for you to begin exploring data and performing powerful real-time analytics.

8. SAS Enterprise Guide by SAS


SAS Enterprise Guide is easy to use, a powerful and adaptable application that provides an instant view of your data in the context you need it. You can immediately see trends, diagnose issues and relate performance to other business metrics. It is a technology-centric, state-of-the-art product that offers solutions to meet your data management needs in the cloud. SAS Enterprise Guide includes valuable content related to SAS Enterprise Guide and other products, services, and applications. It also includes technical information that helps you with customer self-service.

SAS Enterprise Guide by SAS is the premier platform for developing, deploying, and managing your web applications. It was designed from the ground up to meet the needs of today's small-to-medium business (SMB) enterprise.  SAS Enterprise Guide by SAS is an easy-to-use platform that you can deploy right away. With a simple, intuitive setup, and a rich set of demo apps, you'll be up and running in minutes.

9. Alteryx APA Platform by Alteryx


Alteryx APA Platform is a widely used data analytics solution by organizations to reach their business objectives. It has helped me build blocks of codes, develop software that takes care of business needs and develop data analytics applications.

The Alteryx AI Platform by Alteryx offers businesses the scalability, speed, and also flexibility that they need to grow and improve their business.

Alteryx's APA Platform is a proven, performance-driven platform that provides developers with integrated capabilities to perform data analysis, visualization, reporting, and transfer of information. The powerful workflow engine allows users to apply numerous integrations to create custom workflows from different sources of data.

 The APA Platform by Alteryx helps you combine web and cloud analytics, ERP, and OLAP tools to drive actionable insights in real-time. It is faster, more accurate, and completes data exploration faster.

10. Anaconda Enterprise by Anaconda


Anaconda is a virtual environment manager which has outgrown its competitors in the field of data science and is currently one of the most widely used platforms for data science modeling. With Anaconda Enterprise, users can work with their data analysis projects more efficiently and quickly. Anaconda Enterprise provides a cloud-based software platform that enables students, researchers, and scientists to work with their data analysis projects more efficiently and quickly.

Anaconda features an intuitive user interface designed to work with interactive R and Python APIs. It enables developers to work with various types of languages, data sources, and tools.

Anaconda Enterprise by Anaconda happens to be the world's favorite data science platform, with a set of extensive features for all types of users. Whatever your skill level, Anaconda can help you create stunning visualizations and analyses, and explore data faster and easier. The platform brings together best-in-class tools and the most powerful libraries to deliver world-class solutions for predictive analytics, machine learning, and data science.

11.Databricks Lakehouse Platform by Databricks 


The Databricks Lakehouse Platform is the best of both worlds. It lets you easily manage your lakehouse so you can focus on your business, while we take care of all of the heavy liftings.

The Databricks Lakehouse Platform is the best of both worlds: enterprise-grade capabilities and modern, open-source development. It includes pre-built enterprise tools that can take you from zero to production within a few clicks, available across all hosting platforms. Built with our partners, it also allows you to use the latest open source technology like Elasticsearch in your pipeline and lets you customize everything if you want. 

The platform offers a seamless way for users to dive deep into their data and make better decisions faster. The first of its kind, it brings the power of Big Data to the enterprise—enabling you to uncover insights with less effort and fewer resources. And do it all within your organization's existing infrastructure.

12. KNIME Analytics Platform by KNIME


KNIME Analytics Platform (KNIME) is a multi-data, logic-based analytics tool that offers a high degree of flexibility and intelligence. One can rely on KNIME as a multi-data REGISTRATION tool because of its high-value predictive analytics and pattern-finding capabilities. Its risk analysis is used in our department to develop new models. 

The platform serves as a software as a service tool that lets you easily analyze large amounts of data through the graphical user interface. It provides a wide range of valuable analytics features, including statistical modeling and data mining, mathematical and physical fundamentals and signal processing, algorithms evaluation, and optimization.

It is a fantastic analysis tool with a graphical user interface. It is written in Java and it quickly runs in the most modern and powerful frameworks. Its features include pre-built libraries for analytics tasks such as clustering. The platform offers powerful models and state-of-the-art implementations of probabilistic and Bayesian data modeling. In addition to supporting standard data science tasks, it also supports advanced analytics tasks such as large-scale machine learning and automatic inference.

13. SAS Enterprise Miner by SAS


The SAS Enterprise Miner by SAS is a machine learning platform that supports analysts and data scientists in a wide range of scenarios. It offers unrivaled data insight, automation, and predictive modeling capabilities that can be deployed to bring a competitive edge to business decision-making. The initial free trial allows end users to go through the product's features and functions. 

It is also an integrated platform that enables data scientists to work with unstructured and structured data easily. This solution provides advanced tools and services for data to machine learning, predictive analytics, and text analytics. A mobile app allows exploratory analysis at any time, anywhere.

Designed specifically to unleash the performance of Hadoop and Spark, SAS Enterprise Miner (SASEM) is a powerful data miner that provides complete control over every aspect of your analytics through a single user interface. SASEM can handle large data sets, run multiple applications at once, analyze on disk and in memory, harness the computational power of both Hadoop and Spark, automatically manage MapReduce jobs across your cluster and perform complex data processing tasks such as modeling with Naive Bayes and logistic regression models.

 SAS Enterprise Miner is the easiest way to unlock the power of your data, with a variety of tools you can use to discover insights that matter.

14. Amazon SageMaker by Amazon Web Services (AWS)


Amazon SageMaker by Amazon Web Services (AWS) is a cloud service that allows you to run machine learning and data science tasks. It provides access to a set of supervised algorithms, pre-trained machine learning models, and computer vision services that help you build fast, production-ready models to train with. You can use Amazon SageMaker as a point solution for deploying trained machine learning models into your own applications or run them in the cloud for workloads without any custom code.

Amazon SageMaker provides a powerful software platform that allows you to create and train ML models using pre-trained machine learning models. All you need to do is specify the appropriate inputs, perform some training then run the trained model on your data to get real-time feedback on how well your model performs.

It can be used to deliver a repeatable real-time machine learning feedback loop, a step towards democratizing advanced fields.

AWS is a Data Science Platform built to empower developers, data scientists, and others to use machine learning to solve problems at scale. The service provides an easy-to-use coding environment, fully managed services and computes resources, flexible workflows, and powerful analytics capabilities that can be run in real-time on EC2. It uses AWS Lambda, Amazon S3, AutoScaling, CloudWatch, Code Deploy, and secure storage like AWS KMS.

15. Microsoft Azure Machine Learning by Microsoft


Microsoft Azure Machine Learning is a cloud service in Microsoft Azure that makes it easy to use machine learning in your applications. It allows you to build, deploy and train distributed models using any data source including web, streaming, and social media. With the cloud, you can easily scale up or down at the click of a button so your model runs the same way day after day.

Microsoft Azure Machine Learning by Microsoft is a great option for setting up and sharing your machine learning experiments.

If you're looking for an easy way to set up and share your machine learning experiments, it has a straightforward interface that is easy to use and well documented. 

The platform can be considered a great asset for machine learning experiments. 

16. Alteryx Server by Alteryx


The Alteryx Server is a suite of cloud-based data management, analytics, and automation solutions that enable businesses to capture, manage, transform and unlock business value by enabling decision makers to make smarter decisions at every stage of their enterprise lifecycle. Their unified platform serves as the foundation for your greenfield or legacy systems as well as for your next-generation digital transformation efforts.

Alteryx Server is a custom-built solution for analyzing, visualizing, and reporting your data. It's not just another point-and-click tool. Alteryx Server is the ultimate mobile solution for one-click analysis, enhanced visualization and reporting, real-time collaboration with others in your company or enterprise, and automated alerts so you never miss an opportunity.

17. RStudio Team by RStudio


For beginners, RStudio is an excellent choice. You can create simple charts and graphs quickly, with no programming knowledge required. From there you can use the very powerful and advanced installation of SAS if you need more power and flexibility (at a high cost). The cost is significantly lower and, because it offers fewer functions, you can create simpler models without spending a lot of money.

RStudio Team by RStudio is a free, open-source software package that makes it easy to create and manage web applications. It supports web development with a variety of frameworks and technologies—including HTML, JavaScript, CSS, and Node. js—and has mobile apps for Android and iOS devices. 

RStudio Team is a collaborative workspace for programming, analysis, and reproducible research that enables you to write code together with other R users on your team, or within your collaborators' groups. Team features include File-sharing. Each participant in the project can see the code and data files of every other user, making it easy to collaborate by checking in contributions or commenting on others' code. Sync. All data is synchronized across users' local machines and the central server so that each person on a project always has all their data from the beginning of the work session in one place. Multi-user editing sessions. Working collaboratively requires making changes to shared documents at the same time, so Team uses an intelligent locking mechanism that prevents multiple people from changing a document at the same time while some other person is working on it.

18. Vertex AI by Google


Vertex AI by Google is a cloud-based AI tool that makes creating custom, intelligent agents as easy as it can be. It combines an AI core powered by TensorFlow, NVIDIA GPUs and has been optimized for energy efficiency, scalability and performance to create a highly performant platform for building intelligent apps. The platform combines artificial intelligence, data science, and machine learning to improve business processes in your company.

It is a simple, intuitive platform to build machine learning models. Its prebuilt libraries of common operations and a huge ecosystem of integrations provide all the tools you need to get started on your next AI project. Vertex AI offers several smart features that help you to quickly design and test your data science models.

It has a number of built-in features for AI, and there are several free options if you want to explore AI further.

19. IBM SPSS Modeler by IBM


IBM SPSS Modeler is the industry's leading statistical software, regularly used to analyze data on all scales. It helps users quickly explore and discover insight from their data and offers in-product analytics capabilities that help identify areas for improvement. IBM SPSS Enterprise Statistics Modeler provides a comprehensive range of analysis capabilities that enable you to access, visualize, and report on new insights found using IBM Cognos Business Intelligence Unwired – offer immediate access to more robust analytics with IBM SPSS Enterprise Statistics Modeler. 

It enables users to create complex analyses quickly, with relative ease, no matter how advanced the variables are.  It is a simple, quick, reliable, and user-friendly software that allows me to get new insights into my data without effort.

20. Domino Enterprise MLOps Platform


Domino Enterprise MLOps Platform is the unified platform for building, managing, and running machine learning and AI models. It enables developers, data scientists, product managers, and business analysts to create cognitive applications that learn in real time, learn new tasks on the fly, and can be deployed across any cloud or operating system. Domino gives them the freedom to work more fluidly with machine learning, by processing data directly on their phones wherever they are - whether unstructured or structured data (such as text), open APIs, or external callbacks.

Domino Enterprise MLOps Platform is the only holistic data science and MLOps solution on the market. It combines real-time data streaming from all your cloud sources, and an easy-to-use analytics interface to step through all ML models and visualize your results in real time. This is the first of its kind product that stands out for its exceptional user experience combined with a unique combination of capabilities, making it ideal for large-scale enterprises who need to move rapidly up that curve from inside the "black box" of their data scientists.

Final Words

The top DSML platforms are platforms that provide users with tools to build, deploy, monitor and manage decision-making algorithms. These platforms combine intelligent algorithms with data in order to create a business solution. Some of these platforms allow for third-party integration of prebuilt algorithms and workflows that require little coding knowledge. Others require developers to code a machine learning solution from scratch. Arguably the most popular algorithm used in ML development today is called decision tree analysis or deep learning. In this post, we have tried to cover the top 20 best data science and machine learning platforms as depicted by Gartner for the year 2022. 

These platforms can be built using both open source software and proprietary code. Some platforms offer a drag-and-drop interface with visual design options that can be customized to meet specific needs without requiring too much technical knowledge, while others require designers to familiarize themselves with coding before building their own algorithms. 

The Data Science and Machine Learning Platforms category is for products with features that enable users without intensive data science skills to benefit from the platforms’ features. AI platforms are very similar to platforms as a service (PaaS), which allow for basic application development, but these products differ by offering machine learning options.

The platforms described in this post are designed to provide end users with the right tools and advanced machine learning capabilities to help take advantage of data. We have also highlighted the different types of AI applications and emphasized how some platforms do not require any particular programming language or code.

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