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Assess your organization’s data maturity and see how to accelerate digital transformation with Azure data services.
Get key insights on your organization's data maturity
Answer these questions to get insights on your organization's data maturity, as defined in the Rethinking the Enterprise white paper. See recommended next steps for your organization and explore curated resources to accelerate your digital transformation.
Your result: Platform
Your organization has successfully digitally transformed and is now a leader when it comes to tech intensity. Your organization most likely has an integrated foundation of data, software, and artificial intelligence that supports a mature innovation process, as well as a strong culture of growth and measurement that empowers employees to collaborate extensively and make individual decisions that are aligned to organizational strategy. Get more information and insights for platform organizations.
Your result: Hub
Your organization has already taken significant steps towards digital transformation and is now poised to successfully make use of all your organizational assets. At this point, your organization is most likely looking to improve your processes rather than your technical foundations, and you’re also able to focus on developing and improving the use of analytics and machine learning to drive business performance and transforming your business culture so that your employees can effectively use the new data and analytics tools at their disposal. Get more information and insights for hub organizations.
Your result: Bridge
Your organization has already made some first steps towards digital transformation. As you continue to establish your data platform, your organization may face challenges in finding ways to keep building on your initial successes and in determining and prioritizing next steps for your data platform. Get more information and insights for bridge organizations.
Your result: Traditional
Your organization is still in the early stages its digital transformation and may face challenges in fostering collaboration across organizational boundaries, sharing data, and making effective use of your data. Get more information and insights for traditional organizations.
Get key insights for enabling successful data-driven transformations
Analytics Lessons Learned: How Four Companies Drove Business Agility with Analytics
See real-world examples of companies using data analysis to make responsive, informed, and timely decisions.Read the white paper
GigaOm - Forrester Total Economic Impact™ of Azure Machine Learning
Read about the real impact and benefits businesses are experiencing by building AI solutions using Azure Machine Learning.Read the white paper
Take advantage of limitless scale, limitless performance, and limitless possibilities for your digital transformation—all with Azure data services.
Scale a single database to hundreds of terabytes, and enable tens of thousands of users to gain real-time insights at petabyte scale.
Build cloud-native apps with real-time personalization and ultra-low latency. Enjoy higher performance analytics at a lower cost compared with competitors.1
Improve customer experiences, transform products, optimize operations, and enable employees of all skill levels to apply AI to their data responsibly with Azure data and AI services.
Get more value from your data at a lower cost
Analytics in Azure is up to 380% faster than other cloud providers1
Analytics in Azure is up to 59% less expensive than other cloud providers1
Azure Machine Learning is up to 64% less expensive than Google Vertex AI2
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1Performance, TCO, and price-performance claims based on data from a study commissioned by Microsoft and conducted by GigaOm in March 2021 for the Cloud Analytics Platform Total Cost of Ownership report. Analytics in Azure costs up to 59 percent less than other cloud providers according to the Cloud Analytics Platform Total Cost of Ownership report. Data is taken from Test-DS derived queries, and is based on query execution performance testing of 103 queries per vendor, conducted by GigaOm in March 2021; testing commissioned by Microsoft. The primary metric used was the aggregate total of the best execution times for each query. Three power runs were completed. Each of the 103 queries (99 plus part 2 for 4 queries) was executed three times in order (1, 2, 3, … 98, 99) against each vendor cloud platform, and the overall fastest of the three times was used as the performance metric. These best times were then added together to obtain the total aggregate execution time for the entire workload. Prices are based on publicly available US pricing as of March 2021. Actual performance and prices may vary. Learn more about the GigaOm TCO study.
2Total Cost of Ownership, time-to-value and enterprise capability readiness claims based on data from a study commissioned by Microsoft and conducted by GigaOm in July 2021 for the Enterprise Readiness of Cloud MLOps report. Prices are based on publicly available US pricing as of July 2021. Actual performance and prices may vary. Learn more about the GigaOm study.
Gartner, Magic Quadrant for Cloud Database Management Systems, 23 November 2020, Donald Feinberg | Merv Adrian | Rick Greenwald | Adam Ronthal | Henry Cook
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