Azure Data Share Description
Easily distribute data of any format and size from various sources to other organizations while maintaining full control over what you share, who receives it, and the associated terms of use. The Data Share platform offers complete transparency regarding your data-sharing connections through a user-friendly interface, allowing you to share information with just a few clicks or create a custom application via the REST API. This serverless, code-free data-sharing solution eliminates the need for infrastructure setup or management, providing an intuitive interface to oversee all your data-sharing interactions. With automated processes in place, you can achieve greater productivity and predictability in your operations. The service ensures data security by leveraging Azure's robust security measures, enabling the sharing of both structured and unstructured data from a variety of Azure data stores effortlessly. Furthermore, there’s no need for SAS keys, and sharing is entirely code-free, allowing you to dictate data access and define terms of use that comply with your enterprise policies seamlessly. With this tool, organizations can foster collaboration while safeguarding their data integrity and compliance.
Azure Data Share Alternatives
MongoDB Atlas
MongoDB Atlas stands out as the leading cloud database service available, offering unparalleled data distribution and seamless mobility across all major platforms, including AWS, Azure, and Google Cloud. Its built-in automation tools enhance resource management and workload optimization, making it the go-to choice for modern application deployment. As a fully managed service, it ensures best-in-class automation and adheres to established practices that support high availability, scalability, and compliance with stringent data security and privacy regulations. Furthermore, MongoDB Atlas provides robust security controls tailored for your data needs, allowing for the integration of enterprise-grade features that align with existing security protocols and compliance measures. With preconfigured elements for authentication, authorization, and encryption, you can rest assured that your data remains secure and protected at all times. Ultimately, MongoDB Atlas not only simplifies deployment and scaling in the cloud but also fortifies your data with comprehensive security features that adapt to evolving requirements.
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Google Cloud BigQuery
BigQuery is a serverless, multicloud data warehouse that makes working with all types of data effortless, allowing you to focus on extracting valuable business insights quickly. As a central component of Google’s data cloud, it streamlines data integration, enables cost-effective and secure scaling of analytics, and offers built-in business intelligence for sharing detailed data insights. With a simple SQL interface, it also supports training and deploying machine learning models, helping to foster data-driven decision-making across your organization. Its robust performance ensures that businesses can handle increasing data volumes with minimal effort, scaling to meet the needs of growing enterprises.
Gemini within BigQuery brings AI-powered tools that enhance collaboration and productivity, such as code recommendations, visual data preparation, and intelligent suggestions aimed at improving efficiency and lowering costs. The platform offers an all-in-one environment with SQL, a notebook, and a natural language-based canvas interface, catering to data professionals of all skill levels. This cohesive workspace simplifies the entire analytics journey, enabling teams to work faster and more efficiently.
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InfoSum
InfoSum unlocks data’s unlimited potential. InfoSum uses patented privacy-first technology to connect customer records between companies without sharing data. InfoSum is trusted by customers in financial services, content distribution and connected television as well as gaming, entertainment, and gaming. It seamlessly and compliantly connects customer data to other partners via privacy-safe, permission-controlled data networks.
InfoSum's technology has many uses, from the standard 'data-onboarding" to more complex use cases that allow the creation of own identity platforms, the development and sale of new products and data, and the creation of completely new markets.
InfoSum was established in 2015. InfoSum was founded in 2015. The company is poised to experience exponential growth.
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Databricks Data Intelligence Platform
The Databricks Data Intelligence Platform empowers every member of your organization to leverage data and artificial intelligence effectively. Constructed on a lakehouse architecture, it establishes a cohesive and transparent foundation for all aspects of data management and governance, enhanced by a Data Intelligence Engine that recognizes the distinct characteristics of your data. Companies that excel across various sectors will be those that harness the power of data and AI. Covering everything from ETL processes to data warehousing and generative AI, Databricks facilitates the streamlining and acceleration of your data and AI objectives. By merging generative AI with the integrative advantages of a lakehouse, Databricks fuels a Data Intelligence Engine that comprehends the specific semantics of your data. This functionality enables the platform to optimize performance automatically and manage infrastructure in a manner tailored to your organization's needs. Additionally, the Data Intelligence Engine is designed to grasp the unique language of your enterprise, making the search and exploration of new data as straightforward as posing a question to a colleague, thus fostering collaboration and efficiency. Ultimately, this innovative approach transforms the way organizations interact with their data, driving better decision-making and insights.
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Pricing
Pricing Starts At:
$0.05 per dataset-snapshot
Free Trial:
Yes
Company Details
Company:
Microsoft
Year Founded:
1975
Headquarters:
United States
Website:
azure.microsoft.com/en-us/products/data-share
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Cloud data warehouse to power your data-driven innovation
BigQuery Studio provides a single, unified interface for all data practitioners of various coding skills to simplify analytics workflows from data ingestion and preparation to data exploration and visualization to ML model creation and use. It also allows you to use simple SQL to access Vertex AI foundational models directly inside BigQuery for text processing tasks, such as sentiment analysis, entity extraction, and many more without having to deal with specialized models.
Product Details
Platforms
Web-Based
Types of Training
Training Docs
Live Training (Online)
Webinars
In Person
Training Videos
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Azure Data Share Features and Options
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