Microsoft Intelligent Data Platform Description
The Microsoft Intelligent Data Platform serves as a cohesive data and AI solution that empowers organizations to quickly adapt, infuse intelligence into their applications, and derive predictive insights. By harmonizing databases, analytics, and governance, this platform allows businesses to focus more on creating value instead of managing their data infrastructure. It ensures smooth data integration and offers real-time business intelligence, which supports effective decision-making and drives innovation. By dismantling data silos, organizations can gain immediate insights while maintaining the essential data governance needed for secure operations. Additionally, the platform enhances innovation, boosts productivity through automation and AI, and increases agility by forecasting changes and refining decision-making processes. Security is also a top priority, as the platform provides robust protection throughout the data lifecycle, safeguarding both hybrid and multi-cloud environments. Ultimately, this comprehensive approach not only streamlines data management but also cultivates a more informed and responsive organizational culture.
Microsoft Intelligent Data Platform Alternatives
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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DataBuck
Big Data Quality must always be verified to ensure that data is safe, accurate, and complete. Data is moved through multiple IT platforms or stored in Data Lakes. The Big Data Challenge: Data often loses its trustworthiness because of (i) Undiscovered errors in incoming data (iii). Multiple data sources that get out-of-synchrony over time (iii). Structural changes to data in downstream processes not expected downstream and (iv) multiple IT platforms (Hadoop DW, Cloud). Unexpected errors can occur when data moves between systems, such as from a Data Warehouse to a Hadoop environment, NoSQL database, or the Cloud. Data can change unexpectedly due to poor processes, ad-hoc data policies, poor data storage and control, and lack of control over certain data sources (e.g., external providers). DataBuck is an autonomous, self-learning, Big Data Quality validation tool and Data Matching tool.
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Connecty AI
Equip your data professionals with advanced contextual learning agents that enable immediate insights from intricate structured data. Your data transcends mere numbers; it tells a story. Our advanced contextual learning system processes, enriches, and integrates your diverse, multi-source data, converting disjointed facts into a unified graph. From multi-cloud data warehouses to sophisticated data lineage tracking, observe the comprehensive narrative unfold in real-time. Acquire insights that adapt alongside your data, facilitating informed decisions free from distractions. Synchronize every data role into a cohesive workflow through agent-assisted collaboration. Analysts, engineers, managers, and artificial intelligence collaborate seamlessly, dismantling barriers with agent-driven processes that clarify even the most intricate analytics challenges. Our agents promote an effortless information exchange among teams, significantly reducing the time needed for insights and enhancing team effectiveness. Together, unleash the complete potential of your data. By fostering collaboration and streamlining processes, your organization can thrive in an increasingly data-driven landscape.
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Praxi
Praxi is an innovative data classification platform that leverages artificial intelligence to convert unstructured data into meaningful and actionable insights specifically for highly regulated sectors like healthcare, finance, and defense. By providing pre-trained AI models, it streamlines the processes of data discovery, curation, and classification, significantly reducing the need for manual intervention and saving both time and resources. The platform effectively scans various data sources and silos, establishing a cohesive interface that clarifies data relationships while ensuring compliance with GDPR regulations and facilitating automated data curation. Offering real-time insights and improved data governance, Praxi seamlessly integrates with existing systems, empowering organizations to fully harness their data, enhance decision-making capabilities, and maintain regulatory compliance. Furthermore, its user-friendly design enables teams to focus on strategic initiatives while the platform manages the complexities of data management.
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Company Details
Company:
Microsoft
Year Founded:
1975
Headquarters:
United States
Website:
www.microsoft.com/en-us/microsoft-cloud/solutions/intelligent-data-platform
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