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Dataiku vs 1010data

Last Updated: November 18th, 2024

Our analysts compared Dataiku vs 1010data 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.

1010data is a market intelligence and enterprise analytics solution that helps track consumer insights and market trends. In addition to vendor-critical insights, it provides brand performance metrics to buy-side entities. Seamlessly embeddable, it can also function as a standalone private-label option. Data scientists and statisticians leverage its integration with R to view and query data tables.

It enables analytics development through its QuickApps framework. By tracking consumer spending trends and brand performance, it enables businesses to better position their products in the marketplace.

$4,000 Monthly

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$12,000/User, Annually

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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.

Track Consumer Trends: Discover how consumers search for and assess products before buying. Identify product affinities by segments and add value through basket analysis to expand the category assortment. Analyze customers based on geography and spending tiers to create targeted marketing strategies.
Analyze Buyer Behavior: Drive customer retention and higher loyalty by analyzing shopper lifecycles by retailer with geographical drill-down capabilities. Track the path-to-purchase customer experience and the buyer acquisition process. Monitor points of purchase — whether in-store or online, which stores were visited pre-purchase and the items considered before buying.
Maximize ROI: Assess shopping behavior at the category, brand, merchant and product levels. Analyze conversion rates and key metrics’ progression over time by new, lost and retained customers. Uncover churn rate figures by segment and spending capacity to drive remedial strategies.
Track the Competition: Track the product’s market position across hundreds of consumer goods categories. Identify disruptors from other brands on the market. Justify specific product category positioning with data on emerging competitors. Analyze merchandising strategies and promotional spend across merchants.
Application Development: Create end-to-end analytic applications directly atop proprietary granular data through its QuickApps framework and iterate when needed. Deploy them via desktop web, mobile devices or external applications with legacy governance parameters.
Buy-Side Insights: Inform buy-side investment decisions by tracking consumer spending, transactions and basket size of multiple brands. Analyze company performance by quarter, month, week and day. Get granular insights on sector trends, customer segments or geospatial consumer data, refreshed daily.
Data Security: Secure by design, it has a stateful architecture for privately allocated, separate user sessions. It is HIPAA compliant and SOC 2 Type II certified, with support for single sign-on via SAML 2.0 authentication.

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.

Cloud-Native: Built from the ground up to enable large-scale, multi-party data sharing and analytics in the cloud.
Advanced Analytics: Derive meaningful data insights by creating advanced data models against complex data sets. Perform time-series analysis, statistical functions and machine learning through its functions library.
Visualizations: Create charts, graphs, heat maps and more through its rich functions library and a visual expression builder. Leverage the power of analytics through integration with visualization tools like Tableau, Logi Analytics, Information Builders and Metric Insights.
Reporting: Acquire business-critical insights through standardized reporting, consistent KPI monitoring and guided ad-hoc reporting. Gain confidence in data with full visibility into proprietary information and calculation lineage. Save data results locally or to a file system via FTP, or in a data table. Or, export it in CSV, PDF or Excel format.
Data Management: Pull and blend disparate, complex data sets on-the-fly into an analysis-ready format. Assign role-based permissions for access to tables, rows and columns. Tracks usage activity through audit trails and logs that include the account information, IP address and tables accessed.
Integrations: Run advanced data analytics via the R console through R1010. Easily access data tables and view them in Tableau with real-time integration, data discovery and SQL support. Create spreadsheets that access the 1010 data platform via its Excel add-in.
Universal Calculation Library: Quickly answer data-based queries by analyzing complex datasets through centralized and standardized calculations.

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#44

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Analyst Rating Summary

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Dataiku

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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.

78%

of users recommend this product

1010data has a 'good' User Satisfaction Rating of 78% when considering 25 user reviews from 2 recognized software review sites.

4.57 (7)

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3.7 (7)

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.

Robust Data Processing: Handles large volumes of structured and unstructured data efficiently, enabling comprehensive data analysis.

Scalable Architecture: Supports growing data volumes and user demands, ensuring seamless performance as your business expands.

Advanced Analytics Capabilities: Provides sophisticated machine learning algorithms and statistical techniques for in-depth data exploration and predictive modeling.

User-Friendly Interface: Intuitive dashboards and visualization tools simplify data analysis, making it accessible to users of all technical levels.

Data Security and Compliance: Adheres to industry standards and regulations, ensuring the protection and privacy of sensitive data.

Cost-Effective Solution: Offers flexible pricing models and cloud-based deployment options, reducing upfront investment and ongoing maintenance costs.

Excellent Customer Support: Provides dedicated technical support and documentation, ensuring smooth implementation and ongoing assistance.

Community and Resources: Fosters a vibrant user community and offers extensive resources, including tutorials, webinars, and case studies.

Integrations with Other Tools: Seamlessly connects with popular business intelligence and data visualization tools, enhancing data analysis capabilities.

Proven Track Record: Trusted by numerous businesses and organizations, delivering successful data-driven initiatives.

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.

Complexity: Challenging to use for non-technical users, requiring specialized knowledge and skills.

Limited Customization: Pre-defined templates and limited flexibility, hindering the adaptation to specific business needs.

Data Quality Issues: Inconsistent data quality and lack of data validation tools, leading to unreliable insights.

Scalability Challenges: Struggles to handle large and complex datasets, resulting in performance issues and delayed analysis.

Vendor Lock-in: Proprietary technologies and limited data portability, restricting users from switching to alternative solutions.

Costly Licensing: Expensive licensing fees and hidden costs, making it unaffordable for some organizations.

Lack of Real-time Analysis: Inability to process and analyze data in real-time, hindering timely decision-making.

Insufficient Support: Limited technical support and documentation, leaving users struggling with implementation and troubleshooting.

Privacy Concerns: Concerns about data privacy and security, as tools often require access to sensitive information.

Steep Learning Curve: Extensive training and time investment required to master the tools, hindering adoption.

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.

1010data's user reviews over the past year paint a picture of a robust big data analytics tool with strengths in data visualization, ease of use, and customer support. Users have praised its intuitive interface, which allows even non-technical users to quickly create and share insights. Additionally, the tool's advanced visualization capabilities, such as interactive dashboards and customizable charts, have been highlighted as key differentiators, enabling users to explore and present data in a visually appealing and impactful manner. However, some users have expressed concerns regarding the tool's scalability and performance when handling extremely large datasets. Additionally, the lack of certain advanced features, such as real-time analytics and predictive modeling, has been noted as a weakness compared to more comprehensive analytics platforms. Nonetheless, 1010data remains a popular choice for businesses seeking a user-friendly and visually oriented tool for their data analytics needs, particularly for those with smaller to mid-sized datasets.

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