Home > Big Data Analytics Tools > Dataiku > Dataiku vs QlikView

Dataiku vs QlikView

Last Updated: November 18th, 2024

Our analysts compared Dataiku vs QlikView based on data from our 400+ point analysis of Big Data Analytics Tools, user reviews and our own crowdsourced data from our free software selection platform.

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Product Basics

Dataiku is a powerful data analytics platform designed to empower organizations with data-driven insights and machine learning capabilities. It offers a comprehensive suite of features, including data integration, preparation, and advanced machine learning, all within a user-friendly interface. Dataiku facilitates collaboration among data professionals and business users, streamlining the data analytics process. Its AutoML capabilities simplify machine learning model development, making it accessible to users with varying levels of expertise. Real-time insights and scalability are key benefits, allowing organizations to make timely decisions and adapt to changing data requirements. Despite some learning curve challenges, Dataiku remains a favored choice for medium and large businesses seeking robust data analytics solutions.

QlikView is a data discovery and customer insight platform from Qlik, a leader in the insight and intelligence space. However, it is not available for purchase any longer. Qlik Sense, Qlik’s next-generation offering, is available for new customers. It offers self-service data that can help drive decisions and generate significant ROI for technical skill level users.

It’s built from the ground up to be affordable, scalable and adaptable. It can ingest data from diverse sources like big data streams, file-based data, and on-premise or cloud data. It is well-known for its data associations and relationship functionality, keeping data in context automatically. It delivers results quickly via its patented in-memory data processing module, processing data down to as little as 10% of its original size.

Pros

Intuitive interface
Fast data visualization
Easy data exploration
User-friendly for non-technical users
Strong community and support

Cons

Limited data modeling capabilities
Licensing costs can be high
Customization can be challenging
Version control can be a concern
Performance can slow with large datasets

$4,000 Monthly

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$2,500/User, Annual

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Tailored to your specific needs

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Product Insights

Advanced Data Preparation: Dataiku offers powerful data preparation tools, allowing users to clean, transform, and enrich data easily. This ensures that data is ready for analysis and modeling.
Collaborative Environment: Dataiku provides a collaborative workspace where data scientists, analysts, and business users can work together seamlessly, fostering cross-functional teamwork.
Scalable Machine Learning: With Dataiku, organizations can build, deploy, and monitor machine learning models at scale. This empowers data-driven decision-making across the enterprise.
AutoML Capabilities: Dataiku's AutoML functionality automates the model selection and hyperparameter tuning process, making it easier for users to create accurate machine learning models.
Visual Data Exploration: Users can visually explore data, gaining valuable insights through interactive charts and graphs, simplifying the process of uncovering trends and patterns.
Model Deployment: Dataiku streamlines the deployment of machine learning models into production, ensuring that insights generated from data are put into action efficiently.
Data Governance: Dataiku offers robust data governance features, including data lineage, access controls, and auditing, to maintain data quality and compliance.
Automated Reporting: Users can create automated reports and dashboards to share insights with stakeholders, saving time and ensuring data-driven decisions are accessible to all.
Flexible Integration: Dataiku seamlessly integrates with a variety of data sources and tools, making it adaptable to existing data ecosystems and technologies.
Interpretable AI: Dataiku places a strong emphasis on model explainability, helping users understand why AI models make specific predictions, enhancing trust and transparency.

Optimize Connections: Spot connections in data even when working with large data sets. Take a granular look at data through drill-down and view high-level trends in customer/employee behavior.
Increase Data Security and Control: Ensure total control over sensitive data. Prevent unauthorized access to crucial data sets through user-control, filtered views and permissions. AES-256 GCM provides data integrity and keeps information secured. Grant access to view data using user-specific access.
Enhance Functionality: Build the product in alignment with user needs and specifications. Extend functionality with QlikView Workbench to customize the app with custom scripting.
Increase Insight: Gain unparalleled insights into business operations, as well as the market at large. Track KPIs like sales, budgets, employee performance, and hundreds of other pre-built or custom data points.
Flexible Deployment: Choose from a cloud analytics solution, an on-premise installation, or a combined solution to get desired scalability and flexibility.
Intuitive Interface: Obtain data results via the self-service and code-free visual tool. Its accessible interface provides updated information instantly.
Empower Company Culture: Foster a data-driven culture by empowering employees to share data and insights directly or outside the platform.
Increase Competition: Monitor and track employee performance using KPI dashboards across organizations. Analyze changes in empirical data and make decisions to capitalize the profits.
Automated Recommendation: Receive and recommend automated context-aware suggestions using machine learning (ML). Prioritize recommendations on visualization type for easy access.
Accelerate Business Growth: Scale the businesses by deploying self-service and predictable BI. Test business performance using free tools available on the webpage.
Enhance Accessibility: Access all features from anywhere and on any device using an HTML5 client. Provides mobile push notifications to ensure unrestricted and consistent access.
Worldwide Support: Support fifteen languages and native currency conversions while detecting which language to use according to the browser or operating system.
Optimize Deployment and Configuration: Deploy quickly and allow for even quicker configuration because data is not required to be stored in any silos or cubes.

Data Integration: Dataiku offers seamless data integration capabilities, allowing users to connect to various data sources, import data, and prepare it for analysis.
Machine Learning Studio: Users can build, train, and deploy machine learning models in a user-friendly visual interface, streamlining the data science workflow.
Data Preparation: Dataiku provides robust data preparation tools, enabling users to clean, transform, and enrich data efficiently for analysis.
AutoML: The AutoML functionality automates model selection and hyperparameter tuning, simplifying the process of creating accurate machine learning models.
Collaboration Hub: Dataiku offers a collaborative environment where data scientists, analysts, and business users can work together on data projects.
Model Deployment: Users can easily deploy machine learning models into production, ensuring that insights generated from data are put into action.
Visual Data Exploration: Dataiku enables users to visually explore data through interactive charts and graphs, facilitating data discovery and insights.
Data Governance: The platform includes robust data governance features, such as data lineage, access controls, and auditing, ensuring data quality and compliance.
Automated Reporting: Users can create automated reports and dashboards to share insights with stakeholders, streamlining communication.
Scalability: Dataiku is designed to scale with an organization's data needs, making it suitable for both small teams and large enterprises.

Direct Data Source Connection: Connect to almost any data source, including cloud, big data, file-based and on-premise data. Pull information from many services (Salesforce, Hive, Teradata) and combine intel seamlessly into unique and intuitive dashboards.
Intelligent Visualization: Offer interactive displays and represent data in multiple ways for better data analysis. Flexible visualizations allow users to change and adjust graphics according to screen size.
Enterprise Collaboration: Facilitate collaboration for users to share the same dashboard, look at the same view or track one another as they navigate the application.
Strong Associations: Leverage the strength of the platform’s built-in association engine to conduct direct and indirect searches across data or within a single field. Identify data that is related and not associated.
Self-Service App Building: Build apps and files via the drag-and-drop function. Create individual lists with their visualization while managing and sharing across organizations.
Associative Indexing: Combine, transform and ingest data from multiple sources. Gathers data and indexes it to find logical associations. Explore and search big data repositories freely while keeping data intact.
Interactive Dashboards: Provide visualization capabilities and improve interaction using tooltip, lasso selection, filtering and drill-down functions. Encourage viewers to explore data by creating smart dashboards and distributing them using interactive elements.
In-Memory Application: House the software in memory, so conversions, queries and searches happen quicker and more efficiently. Eliminate problems that traditionally plague slow, on-disk applications. Locate all data in RAM.
Web Connectors: Extract data from multiple social networking sites and web-based sources using web APIs. Built-in connectors easily connect to any URL and fetch data.
Robust Data Controls: Enable meaningful data manipulation within the application by leveraging unique dashboards, reports and filter views.
Data Alerts: Spot anomalies and outliers by requesting context-aware alerts. Monitor and manage data without limitations.

Product Ranking

#26

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#32

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Analyst Rating Summary

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User Sentiment Summary

91%

of users recommend this product

Dataiku has a 'excellent' User Satisfaction Rating of 91% when considering 7 user reviews from 1 recognized software review sites.

82%

of users recommend this product

QlikView has a 'great' User Satisfaction Rating of 82% when considering 1859 user reviews from 4 recognized software review sites.

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4.3 (163)

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3.9 (732)

Awards

Synopsis of User Ratings and Reviews

Comprehensive Feature Set: Users appreciate Dataiku's wide range of features, from data preparation to advanced machine learning, enabling end-to-end data analytics.

Intuitive Interface: Dataiku's user-friendly interface receives praise for its ease of use, making it accessible to both data professionals and business users.

Effective Collaboration: Many users find Dataiku's collaborative environment conducive to teamwork, facilitating cross-functional collaboration on data projects.

Scalability: Dataiku's scalability is highly regarded, making it suitable for small teams and large enterprises, adapting to evolving data requirements.

AutoML Capabilities: Users value Dataiku's AutoML functionality, which simplifies machine learning, making it accessible to users with varying levels of expertise.

Real-Time Insights: Dataiku's ability to provide real-time insights is a significant benefit, enabling timely decision-making based on up-to-date data.

Data Governance: Dataiku's robust data governance features are highly regarded, helping maintain data quality and ensuring compliance with regulations.

Community and Support: Users appreciate the Dataiku community and support resources, which provide valuable assistance and guidance.

Integration Capabilities: Many users highlight Dataiku's seamless integration with other tools and systems, enhancing their data workflows.

Transparency and Explainability: Dataiku's focus on model transparency and explainability is praised, enhancing trust in machine learning models.

Data Visualization: Approximately 80% of users who review its data visualization capabilities are satisfied with its intuitive drag-and-drop feature, rich libraries and its range of aesthetically appealing data representation options.

Data Preparation: Of users who mention data processing, 83% appreciate the platform’s seemingly limitless data transformation capabilities that help them deep-dive into all possible data relationships to glean actionable insights.

Functionality: Among users who share their views on this platform, around 68% say that they are satisfied with the power of its associative query engine that enables faster on-the-fly calculations and analytics aggregation at the speed of thought.

Sharing and Collaboration: About 83% of users who comment on sharing capabilities appreciate its multi-tier permissions capabilities and easy sharing of reports with clients via external sharing options.

Setup: Around 66% of users who mention ease of setup say that QlikView has a fast implementation cycle.

Steep Learning Curve: Some users find Dataiku's learning curve to be relatively steep, particularly for those new to data science and machine learning.

Resource Intensive: Running complex operations and large-scale data processing in Dataiku can be resource-intensive, potentially requiring substantial computing power.

Costly Licensing: The cost of Dataiku's licensing can be a concern for small organizations or startups with limited budgets.

Limited Free Version: The free community edition of Dataiku has limitations in terms of features and scalability, which may not meet the needs of larger enterprises.

Integration Challenges: Some users encounter challenges when integrating Dataiku with certain legacy systems or non-standard data sources, requiring additional effort and customization.

Dependency on Data Quality: The effectiveness of Dataiku's analysis and modeling heavily relies on the quality of input data, which can be a challenge if data is not well-maintained.

Customization Complexity: Highly customized data workflows may require a deeper understanding of the platform, potentially making customization more complex.

Real-Time Processing: Dataiku may not be the ideal choice for applications requiring real-time data processing, as it primarily focuses on batch processing.

Competitive Market: Dataiku operates in a competitive market with various alternatives, making it essential for users to evaluate if it aligns with their specific needs and budget.

Security Concerns: While Dataiku offers security features, organizations handling highly sensitive data may need additional security measures to meet compliance standards.

Cost: Pricing plans are inflexible and can be cost-prohibitive for small organizations and startups, though large organizations may find that it offers high value, as stated by 93% of users who mention its cost.

Performance: Approximately 42% of users say that performance-wise, this platform is resource-hungry and liable to slow down when crunching large amounts of data on local machines.

User Interface and Graphics: Of users who mention user interface, around 44% say that it needs improvement in deep-dive capabilities, as well as its quality of graphics.

Reporting: Of users who mention reporting, approximately 46% say that it lacks ad-hoc reporting and built-in reporting capabilities, requiring paid plugins to enhance the graphics quality of reports.

User reviews for Dataiku reveal a mixed sentiment, with notable strengths and weaknesses. Users appreciate Dataiku's comprehensive feature set, user-friendly interface, and its effectiveness in facilitating collaboration among diverse teams. Scalability is another advantage, making it suitable for various organizational sizes. AutoML capabilities and real-time insights are well-received for their accessibility and timeliness. However, several users express concerns about a steep learning curve, especially for newcomers to data science. The platform's resource-intensive nature can be challenging, and the cost of licensing may be a barrier for smaller organizations. Some users find limitations in the free community edition and face integration challenges with legacy systems or non-standard data sources. Data quality dependency and customization complexity are other reported cons. Dataiku is often compared to similar products in a competitive market, and users stress the importance of evaluating it against specific needs and budgets. Security-conscious organizations may need additional measures when handling sensitive data. Despite its limitations, Dataiku maintains a strong user base due to its robust feature set and collaborative capabilities, enabling data-driven decision-making in various industries.

QlikView is one of the foremost BI solutions in the market today, mainly due to the power of its associative query engine to link data from multiple sources that drives its visually impressive dashboards. With its strong data visualization capabilities, users can perform search and filter through data on-the-fly and conduct deep-dives to glean insights that matter to them. With a fast setup, users can have their first data model up and running in very little time. The software resides in-memory and houses data in RAM for quicker retrieval. With multi-tier access permissions for in-organization users, it enables users to view executive summaries at a glance, while allowing them to drill-down into data to find out more. Sadly, Qlik is now scaling back on improvements and updates for QlikView and focusing on promoting QlikSense instead, a possible reason why its filter and search functions, ad-hoc reporting and graphics are lagging in terms of quality, as mentioned in many user reviews. Also, this platform can prove to be resource-heavy for databases housed on local machines, especially when performing batch update jobs. In addition to inflexible pricing plans and the cost of licensing, quite a few necessary add-ons are paid. In summary, QlikView is one of the leading in-memory BI tools available in the market today and rates excellently with users in terms of data aggregation and visualization capabilities; however, buyers should factor in its pricing plans and other limitations when searching for the perfect BI solution for their enterprise.

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