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Dataiku vs Alteryx — the Best Software for Analytics Automation in 2023

Monica Salib

12 minutes
Last Updated:
November 23, 2023

Table of Contents

According to a survey conducted by the Harvard Business Review, analytics automation increased manufacturing productivity by 90%, increased collaboration by 85%, and reduced errors by 90%.

As organizations increasingly rely on data-driven insights to make informed decisions, the demand for efficient and comprehensive analytics software has reached new heights.

In 2026, the automation market is projected to surge to $9.36 billion, driven by a robust compound annual growth rate of 12.5%. Dataiku and Alteryx have emerged as leading solutions in this market, offering a wide array of capabilities and features to cater to diverse analytics needs.

However, amidst this competition, it becomes imperative to explore whether an alternative exists that outshines both contenders and revolutionizes the way we approach analytics automation.

In this article, we’ll delve into the strengths and weaknesses of Dataiku and Alteryx, all while introducing an alternative solution that not only bridges the divide but also provides a more efficient solution for manufacturers.

Figure 1: Analytics automation, the paradigm for excellence

Dataiku review

 Dataiku DSS homepage
Figure 2: Dataiku DSS homepage


Dataiku DSS is an analytics automation platform with many features and a user-friendly design, making it accessible to a diverse audience with varying skill levels. Its extensive capabilities, collaborative environment, and versatility make it a compelling choice for businesses seeking a comprehensive analytics solution.

With its user-friendly interface and rich features, Dataiku has gained popularity among various industries seeking advanced analytics automation.


Dataiku boasts an intuitive and visually appealing interface, making it accessible to beginners and advanced users. Its drag-and-drop functionality simplifies data processing and model building, allowing users to analyze and interact with data effortlessly.

Figure 3: Dataiku DSS interface


Dataiku caters to diverse users, including data scientists, analysts, business professionals, and engineers. The customer base for Dataiku includes:

  • General Electric (GE)
  • Sephora
  • Unilever
  • Schlumberger (SLB)
  • BNP Paribas
  • Ubisoft
  • Paloalto
  • Cisco


  • Data wrangling and preparation: Dataiku offers tools for data cleaning, transformation, manipulation, and structuring, aiding in data preparation for analysis.
  • Data visualization: The platform provides data visualization capabilities, enabling users to create charts, graphs, and dashboards to gain valuable insights from their data.
  • Machine learning and autoML: Dataiku supports the development and deployment of machine learning models, allowing users to build, train, and validate algorithms on their data. Along with its AutoML functionality, the process is fully automated, making it more accessible.
  • Multiple data sources: With Dataiku, users can upload several data sources, making it a versatile platform suitable for organizations with diverse data types that need a smooth import and export of data.
  • Model deployment: Users can deploy machine learning models built in Dataiku to make predictions and drive real-world applications.
  • Model evaluation: Dataiku provides tools to evaluate the performance of machine learning models, enabling users to optimize their models effectively.
  • Data insights and reporting: Users can generate interactive reports and share data insights with relevant stakeholders.

Use cases

Dataiku finds applications in fintech, logistics, supply chain, and transportation spaces but has limited use in manufacturing and process engineering. Dataiku’s use cases vary from financial institutions optimizing risk management strategies to e-commerce businesses personalizing customer experiences.


  • User-friendly interface – Dataiku provides an intuitive interface that fosters ease of use. While new users may have an initial learning curve, this can be quickly overcome with their support services.
  • End-to-end solution – The platform offers a comprehensive suite of tools, eliminating the need for multiple disparate tools and integrations.
  • Scalability – Dataiku can handle large and complex datasets, making it suitable for organizations of all sizes.
  • Extensive support – The platform provides excellent documentation and customer support to assist users throughout their data analytics journey.
  • The flexibility of work – Dataiku’s strength lies in its work flexibility, allowing users the freedom to choose between visual or code-based approaches based on their preferences. The platform also offers real-time model deployment for production scenarios.


  • Pricing – Dataiku's pricing may be higher for small businesses or startups, limiting accessibility to budget-constrained organizations.
  • Resource-intensive – Running Dataiku on less powerful hardware might result in performance issues and longer processing times.
  • Training requirements – Training and support are imperative for beginners to overcome the learning curve. Incredibly advanced features require extensive training, which Dataiku provides for an additional fee.
  • Performance issues – Larger projects with complex workflows might experience performance issues and require comprehensive hardware upgrades to manage.
  • Limited industrial connectivity – Dataiku, a traditional MLops platform, offers limited industrial connectivity as it focuses on integrating with other cloud-based services using API integration and does not offer compatibility with OSI-PI or the data historian of industries.

Alteryx review

Alteryx designer homepage
Figure 5: Alteryx designer homepage


Alteryx is a top-tier data analytics platform with a user-friendly interface, robust data quality features, and comprehensive data preparation tools. Its versatility and ability to handle complex analytics make it an invaluable asset for organizations leveraging data-driven insights for better decision-making.

Nonetheless, when assessing Alteryx, potential users should consider factors such as the learning curve, technical support, and cost.


Alteryx has a user-friendly and intuitive interface, enabling users with varying technical expertise to navigate the platform easily.

The drag-and-drop workflow builder simplifies the process of data preparation, blending, and analysis, fostering a smooth and efficient user experience.

Alteryx designer interface
Figure 6: Alteryx designer interface


Its accessibility and ease of use make Alteryx a valuable asset for empowering various organizational teams to perform tasks efficiently. The following are the prominent customers of Alteryx:

  • Walmart
  • Cardinal health incorporated
  • Fords motor company
  • Johnson & Johnson
  • Phillips 66
  • Abbot UK
  • AGL Energy Ltd.


  • Data preparation – Alteryx offers robust data preparation and blending capabilities, allowing users to clean, transform, and manipulate data from various sources.
  • Seamless integration – Alteryx supports easy integration with various data sources, including spreadsheets, databases, and cloud-based services, facilitating a smooth import and export process.
  • Geospatial analytics – The platform allows users to analyze location-based data and gain deeper insights from spatial information.
  • Predictive analytics – Alteryx supports predictive analytics, empowering users to build sophisticated predictive models based on their data.
  • Data mining – With Alteryx, users can mine data from different sources, making extracting valuable information and patterns from diverse datasets easier.
  • Visual workflow – Alteryx offers a graphical, drag-and-drop workflow interface, eliminating the need for coding and simplifying the data analytics process.
  • Model building – Users can build and deploy sophisticated models for predictive analytics and data analysis within the platform.
Alteryx designer workflow
Figure 7: Alteryx designer workflow

Use cases

Alteryx finds applications across diverse industries and use cases. It is commonly used for data cleaning and transformation, customer segmentation, sales forecasting, churn analysis, and sentiment analysis.

Moreover, it aids in automating repetitive database tasks, saving time and effort for data professionals and engineers.


  • Seamless interface – Alteryx offers an intuitive and user-friendly interface, which is the bread and butter of the company.
  • Various data sources – Alteryx offers comprehensive data preparation and blending tools; it provides exceptional data management by integrating various data sources.
  • Versatility – Alteryx caters to a broad user base due to its diverse functionality, offering versatile applications across different industries and end-user scenarios.
  • Automation for productivity – The platform offers seamless workflow automation, dramatically reducing the need for additional resources while enhancing productivity.


  • Complex functionality – Alteryx’s user interface is intuitive. However, there is a learning curve for advanced features such as spatial predictive modeling, time series, perspective analysis, and custom macro integration, especially for new users.
  • Price – Alteryx, compared to other platforms, has one of the highest costs in the market, making it less viable for small-scale organizations with limited budgets.
  • Limited scalability – Compared with other data science studios, Alteryx’s scalability is limited; handling large datasets may cause performance issues.
  • Real-time collaboration – Alteryx's most significant flaw lies in its limited collaborative features, which impede team collaboration, hinder the ability of multiple users to work on a single workflow, and delay real-time decision-making.

Why look for Dataiku and Alteryx alternatives?

While Dataiku and Alteryx have earned their reputation as robust data analytics platforms, there remains room for improvement in terms of enhancing ease of use, refining data quality management, and offering more flexible pricing.

For instance, Dataiku and Alteryx can be complex and challenging to navigate for non-technical users, limiting collaboration across teams. Additionally, their pricing structures can be prohibitive for smaller organizations, hindering access to advanced analytics for budget-conscious businesses.

Basetwo emerges as a superior alternative that addresses these shortcomings. Basetwo offers a user-friendly interface, making it accessible to data science professionals and business users with varying expertise.


 Basetwo’s workflow
Figure 8: Basetwo’s workflow


Basetwo's low-code AI platform focuses on industrial simulation and optimization, providing process engineers with the tools to automate and optimize production processes in real-time.

One significant advantage is that Basetwo combines a wide range of first-principle models with ML to fit user needs. These models can be readily shared as templates throughout the organization, promoting seamless cross-functional collaboration.

The drag-and-drop functionality and visual workflow builder simplify the data analytics process, promoting seamless collaboration between teams and ensuring data-driven decision-making across the organization. Its capability of advanced process control offers business intelligence beyond other platforms.

Regarding features, Basetwo differentiates itself from Dataiku and Alteryx as it focuses on process engineering and manufacturing applications while offering comprehensive data blending, advanced analytics, and machine learning capabilities.

The wide range of algorithms and hybrid models enable users to mine data products, gain deeper insights, and easily make data-driven predictions.

Basetwo’s hybrid modeling technology
Figure 9: Basetwo’s hybrid modeling technology


Basetwo is a user-friendly platform with a low-code, drag-and-drop interface, allowing process engineers to build and modify simulation models without programming knowledge.

Manufacturers can enhance their operational visibility, make data-driven decisions, and ultimately optimize operational efficiency by adopting a hybrid modeling platform. This platform seamlessly integrates data science with process engineering and incorporates real-time data monitoring capabilities, all through the utilization of digital twin-life cycle technology.

Its visually interactive design simplifies modeling, promotes productivity, and optimizes production outcomes.

Basetwo’s low-code interface
Figure 10: Basetwo’s low-code interface


Designed with process engineers in mind, Basetwo caters to the specific needs of the manufacturing space. The platform bridges the gap between data science and engineering, promoting a collaborative atmosphere where experts merge seamlessly.

Basetwo emerges as the alternative, offering a user-friendly interface, robust data quality features, and competitive pricing. Its reputation with engineers, particularly in the oil and gas, pharmaceutical, and aerospace industries, has grown exponentially over the years, making it a viable alternative.


  • Real-time data access – Basetwo connects to multiple data sources, providing manufacturers with real-time access to critical data and offering traditional data cleaning and preparation tools. It enables informed decision-making and streamlines workflows to enhance overall productivity.
  • Advanced simulations – The platform offers advanced simulation capabilities, allowing manufacturers to run virtual simulations to model and analyze various scenarios. It helps in the continuous fine-tuning of processes and identifying inefficiencies.
  • Optimization capabilities – Basetwo's optimization features enable manufacturers to identify opportunities for improvement, reduce downtime, and enhance overall productivity in their operations.
  • Data integration – Basetwo integrates with multiple data sources, ensuring manufacturers have a comprehensive view of their operations and can extract valuable insights from their data.
  • Decision support – The platform provides decision support tools that aid manufacturers in understanding complex processes and optimizing their strategies for better outcomes.
  • Predictive analytics – Basetwo leverages predictive analytics to anticipate potential issues, enabling proactive decision-making and minimizing disruptions in manufacturing processes.
  • Industrial connectivity – Basetwo offers API integration compatibility and gives full-scale industrial connectivity using OPC-UA features, allowing Basetwo to connect with industrial databases and plant operational data in real-time.
Basetwo workflow
Figure 11: Basetwo workflow

Use cases

Basetwo's versatile features enable manufacturers to monitor production processes, equipment performance, and quality metrics in real-time, minimizing downtime and ensuring optimal efficiency.

It also supports advanced simulations, optimization, predictive analytics, and process improvement initiatives, enabling data-driven decisions and enhancing overall operational performance.

Comparison Table

dataiky vs alteryx comparison table


Dataiku and Alteryx are popular choices for analytics automation software in 2023. However, Basetwo's features make it one of the best alternatives for the manufacturing industry.

Its low-code interface, specialized focus, and data-driven features empower process engineers to achieve optimal production outcomes and drive manufacturing excellence.

Basetwo sets a new standard in analytics automation, demonstrating how advanced technology and domain expertise can work together to shape the future of manufacturing.

Take advantage of your opportunity and explore today's next gold standard in the automation industry; book your demo today!

Is Dataiku the same as Alteryx?

No, Dataiku and Alteryx are not the same. They are both data analytics platforms, but different companies develop them and have their own distinct features and capabilities. Dataiku focuses on collaborative data science and machine learning, while Alteryx emphasizes data preparation, blending, and advanced analytics.

What is the difference between Dataiku and Alteryx Cloud?

Dataiku and Alteryx Cloud are cloud-based platforms, with Dataiku focusing on collaborative data science projects and Alteryx Cloud on advanced analytics. Dataiku enables teams to work together on projects, while Alteryx Cloud focuses on self-service data preparation and analytics for business users.

Is Dataiku worth it?

Dataiku is a powerful tool with features for collaborative data science, machine learning, and data prep. It streamlines workflows, builds predictive models, and provides insights for data scientists and analysts. However, the decision should consider budget, time constraints, organization size, and data complexity. To evaluate Dataiku's value, evaluate through demos, trials, and comparisons with similar tools to ensure alignment with your needs and a satisfactory return on investment.

Who are Dataiku's competitors?

As per the current market scenario, Dataiku's key competitors include Basetwo, Alteryx, Databricks, KNIME, RapidMiner, DataRobot, IBM Watson Studio, Microsoft Azure Machine Learning, and Google Cloud AI Platform.

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