Azure Synapse Analytics vs 1010data

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Our analysts compared Azure Synapse Analytics 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.

Azure Synapse Analytics Software Tool
1010data Software Tool

Product Basics

Microsoft Azure Synapse Analytics is a comprehensive cloud-based analytics service designed to empower organizations with robust data warehousing and data analytics capabilities. It seamlessly integrates data warehousing and big data analytics, enabling users to ingest, prepare, manage, and serve data for immediate business insights. Key features include scalable resources, real-time analytics, machine learning integration, and a collaborative workspace for data professionals. Azure Synapse Analytics offers benefits such as improved scalability, enhanced data security, and simplified data integration. It's particularly valuable for organizations looking to harness the power of data to make informed decisions and gain a competitive edge in today's data-driven landscape.
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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.
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$1.25/Hour, Usage-Based
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$12,000/User, Annually
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Product Insights

  • Scalability: Azure Synapse Analytics offers scalable data warehousing, allowing organizations to easily adjust resources to meet their specific needs. This scalability ensures optimal performance and cost-efficiency.
  • Unified Analytics: With Azure Synapse Analytics, users can seamlessly integrate data analytics and data warehousing. This unified approach simplifies data management, analytics, and reporting, leading to faster insights and smarter decision-making.
  • Advanced Security: Security is a top priority in Azure Synapse Analytics. It provides robust security features, including data encryption, authentication, and role-based access control, ensuring that sensitive data remains protected.
  • Data Integration: This platform offers powerful data integration capabilities, allowing users to easily ingest, transform, and load data from various sources. It supports a wide range of data formats and connectors, facilitating seamless data integration workflows.
  • Optimized Performance: Azure Synapse Analytics leverages intelligent caching and query optimization to deliver exceptional query performance. Users can run complex queries on large datasets quickly and efficiently.
  • Real-time Analytics: Organizations can harness real-time data analytics with Azure Synapse Analytics. It supports streaming data, enabling businesses to gain insights from live data streams and make timely decisions.
  • Cost Management: With cost controls and optimization features, Azure Synapse Analytics helps organizations manage their data warehouse expenses effectively. Users can pause and resume resources as needed to control costs.
  • Integration with Azure Ecosystem: Azure Synapse Analytics seamlessly integrates with other Azure services, such as Azure Data Lake Storage and Azure Machine Learning. This integration enables organizations to build end-to-end data solutions within the Azure ecosystem.
  • AI and Machine Learning: Leveraging Azure's AI and machine learning capabilities, Synapse Analytics allows users to build and deploy advanced analytics models, unlocking valuable insights from their data.
  • Global Reach: Azure Synapse Analytics is available in multiple Azure regions worldwide, providing global accessibility and low-latency data processing for organizations with international operations.
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  • 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. 
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  • Data Warehousing: Azure Synapse Analytics offers a robust data warehousing solution, allowing organizations to store and manage large volumes of structured and unstructured data efficiently.
  • Analytics Workspace: It provides an integrated analytics workspace for data engineers, data scientists, and analysts to collaborate, explore data, and build advanced analytics models.
  • On-Demand Query Processing: Users can run on-demand queries to extract insights from their data in real-time, without the need for predefined structures or complex ETL processes.
  • Data Integration: Synapse Analytics supports data integration from a variety of sources, enabling users to ingest, transform, and load data with ease.
  • Auto-scaling: The platform offers auto-scaling capabilities, automatically adjusting resources to handle varying workloads, ensuring optimal performance and cost-effectiveness.
  • Security and Compliance: Azure Synapse Analytics includes robust security features, such as encryption, authentication, and access control, to protect sensitive data and maintain compliance with industry regulations.
  • Intelligent Caching: It employs intelligent caching to speed up query performance, reducing latency and enhancing overall data processing efficiency.
  • Real-time Analytics: Users can analyze streaming data in real-time, enabling timely insights and the ability to respond to changing conditions swiftly.
  • Machine Learning Integration: Synapse Analytics seamlessly integrates with Azure Machine Learning, allowing organizations to build, train, and deploy machine learning models for advanced predictive analytics.
  • Collaborative Workspace: It provides a collaborative workspace for teams to collaborate on data projects, facilitating efficient data exploration and analysis.
  • Serverless SQL Pools: Azure Synapse Analytics offers serverless SQL pools, enabling users to query data stored in data lakes without the need for provisioning dedicated resources.
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  • 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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Product Ranking

#40

among all
Big Data Analytics Tools

#44

among all
Big Data Analytics Tools

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Analyst Rating Summary

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Analyst Ratings for Functional Requirements Customize This Data Customize This Data

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Augmented Analytics Computer Vision And Internet Of Things (IoT) Dashboarding And Data Visualization Data Management Data Preparation Geospatial Visualizations And Analysis Machine Learning Mobile Capabilities Platform Capabilities Reporting 54 63 93 93 78 75 0 57 0 25 50 75 100
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Analyst Ratings for Technical Requirements Customize This Data Customize This Data

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User Sentiment Summary

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Good User Sentiment 25 reviews
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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.

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4.0 (18)
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3.7 (7)

Synopsis of User Ratings and Reviews

Scalability: Azure Synapse Analytics is praised for its ability to seamlessly scale resources to handle growing data volumes and complex workloads.
Integration: Users appreciate the tight integration with other Azure services, making it easy to build end-to-end data solutions within the Azure ecosystem.
Real-time Insights: The platform's support for real-time data analytics enables users to gain timely insights from streaming data sources, improving decision-making.
Data Security: Azure Synapse Analytics is lauded for its robust security features, including encryption and access controls, ensuring data privacy and compliance.
Data Integration: Users find it user-friendly for integrating data from various sources, simplifying data preparation and analysis.
Performance Optimization: The platform's query optimization and caching mechanisms enhance query performance, even with complex analytical workloads.
Collaboration: Its collaborative workspace fosters teamwork among data professionals, improving productivity and knowledge sharing.
Machine Learning Capabilities: Users appreciate the integration with Azure Machine Learning, allowing them to leverage AI and machine learning for advanced analytics.
Cost Management: Azure Synapse Analytics offers cost-control features that help users manage their data analytics expenses effectively, ensuring cost-efficiency.
Global Reach: Its availability in multiple Azure regions ensures global accessibility and low-latency data processing for organizations with international operations.
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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.
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Cost Complexity: Some users find managing costs in Azure Synapse Analytics complex, as resource scaling and query optimization may require careful monitoring to avoid unexpected expenses.
Learning Curve: There's a learning curve associated with the platform, especially for users new to Azure services, which can slow down initial adoption and implementation.
Data Volume Challenges: Handling extremely large data volumes can be challenging and may require additional resources, impacting overall cost-effectiveness.
Integration Complexity: While Azure Synapse Analytics integrates well with Azure services, some users have reported challenges when integrating with external systems, which may require custom solutions.
Resource Scaling Time: Scaling resources up or down can take time, affecting immediate query performance during resource adjustments.
Storage Costs: Users have noted that storing data in Azure Data Lake Storage, a common practice, can add to overall costs that need to be carefully managed.
Complex Queries: Executing complex queries may lead to longer processing times and higher resource consumption, impacting query performance and costs.
Resource Provisioning: Some users have experienced challenges when provisioning resources, requiring careful planning and allocation.
Offline Work Limitations: Certain features may require an active internet connection, limiting offline work capabilities, which could be a drawback in specific scenarios.
Support: A few users have reported concerns about the level of support provided, particularly for resolving complex technical issues.
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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.
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User reviews for Microsoft Azure Synapse Analytics generally highlight its strengths in scalability, integration, and real-time analytics. Many users appreciate its ability to seamlessly scale resources and integrate with other Azure services, simplifying end-to-end data solutions. The support for real-time data analytics also receives positive feedback for enabling timely decision-making. However, some users note challenges associated with cost management, citing complexity in monitoring and controlling expenses. There's a learning curve for newcomers, which can slow down initial implementation. Handling large data volumes and complex queries may require extra resources and careful optimization. Integration with external systems can be complex, and resource scaling may impact query performance temporarily. In comparison to similar products, users find Azure Synapse Analytics competitive due to its tight integration within the Azure ecosystem and its machine learning capabilities. Despite some limitations, it is viewed favorably for its potential to deliver scalable, real-time insights and drive data-driven decision-making within organizations.

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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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