Building a data-driven organization: Modernizing data architecture
with Snowflake on Azure
From sensor data to financial transactions or employee performance data – structured, semi-structured, and unstructured data is being processed, stores, and analyzed with the end goal being to use it as a competitive advantage. Yet these huge volumes and variety of data are putting to test the capacity of legacy data platforms. Organizational data is often siloed in departments or individual business systems. Business users rely heavily on IT to support dashboarding or reporting activities.
Business intelligence (BI) modernization is a critical step forward to addressing these limitations and building the environment needed for a data-driven culture. To prepare this environment, you need to prepare data by cleansing, transforming, and consolidating it (through ETL or ELT processes). This merges all of your data (including legacy data assets) into a unified structure to make it ready for consumption in the process of analysis.
Take a look at how to modernize your data architecture to support data variety and self-service BI with the power of the Snowflake data warehouse run on the Microsoft Azure platform. You’ll find out why Snowflake on Azure is a better option, including:
• You can enjoy a 72% reduction in IT support requirements
• Get a unified cloud platform and a single source of truth for enterprise data
• Support most data formats with a flexible architecture
• Enjoy high-scalable data handling and sustainable data integration capabilities
• Accelerate business processes and lower infrastructure, maintenance, and administration costs
Snowflake architecture on the Azure platform is a unique and effective solution to tap into the benefits of both platforms.
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