Azure Synapse Analytics is the next incarnation of Azure SQL Data Warehouse from Microsoft. Like SQL Data Warehouse, Azure Synapse Analytics is a cloud-based, relational data warehouse system with MPP (massively parallel processing), virtually unlimited scaling capacity, and the power to process and store petabytes of data. The difference is that Azure Synapse Analytics has added business intelligence, machine learning, and other advanced features to its data warehousing profile. Microsoft has also boosted the platform's capacity to ingest, transform, manage, and process larger volumes of relational and non-relational data faster and more efficiently.
Mixpanel gathers product usage data, including metrics like what features are being used most frequently, the number of active users, and when user engagement rises or drops. It also automatically collects data on all user actions and uses that data to provide a variety of useful insights, such as automatic suggestions for how to improve customer retention and lead acquisition. Since usage data is collected from the start, Mixpanel can also track newly defined metrics using historical data.
Bring all your Mixpanel data to Amazon Redshift
Load your Mixpanel data to Google BigQuery
ETL all your Mixpanel data to Snowflake
Move your Mixpanel data to MySQL
In addition to serving as a powerful, scalable, cloud-based data warehouse, Azure Synapse adds advanced business intelligence and machine learning data analytics to its list of services.
Whether you need a non-relational data lake, relational data warehouse, or a combination of both, Azure Synapse integrates the two and lets you query the data in SQL while serving as a unified, end-to-end analytics solution. Within a single workspace, Azure Synapse allows you to achieve your data warehousing, data preparation, data management, AI, machine learning, and business intelligence goals. Access all of your data and create stunning dashboards with Power BI via a single interface.
With Azure Synapse Link, cloud-native HTAP implementation allows you to integrate Azure Synapse with Azure databases to extract near real-time insights from operational databases. This allows Azure Synapse to extract machine learning and business intelligence analyses from live data without disrupting the transactional performance of operational systems.
Azure Synapse allows your team to work with their preferred language. Whether it's T-SQL, Scala, Spark SQL, Python, or .Net, Azure Synapse is compatible with your language of choice while using either provisioned or serverless processing resources.
Azure Synapse lets you query data with provisioned or serverless on-demand computational resources.
Azure Synapse natively connects with a wide range of Azure and Microsoft services. The platform includes native connectors for Azure Machine Learning, Azure Data Lake, Azure Blob Storage, Azure Active Directory for authentication, and Microsoft Power BI for visualizing data. Azure Synapse also integrates its machine learning and business intelligence tools with Open Data Initiative tools and services. Led by Microsoft, Adobe, and SAP Software solutions, the Open Data Initiative seeks to boost the connectivity and interoperability of cloud-based SaaS services. Open Data Initiative compatible services include the Microsoft Office 365 suite, the Microsoft Dynamics 365 suite, and more.
Microsoft Azure Synapse makes it easy to optimize your query performance through limitless concurrency, workload isolation, workload management.
Azure Synapse offers cutting-edge security and privacy that includes dynamic, real-time data masking, always-on data encryption, automated threat detection, authentication through single-sign-on and Azure Active Directory. The platform also includes access control features like column-level security and native row-level security for additional security and privacy within your team.
In terms of compliance, Azure offers more certifications than any cloud provider to ensure that your data collection and data use practices comply with industry-specific, regional, state, and national compliance standards.
Get any or all raw event data that has been collected by Mixpanel, including what events have occurred, when they happened, and any relevant properties about those events. Then, integrate this raw data with other data sources to get new or deeper usage analytics.
Retrieve data about a customer’s journeys through your funnel. This data contains the customer’s timeline from start to finish - including how many steps in the funnel the customer completed during that time - which can be used to identify which steps during a funnel most commonly include specific events, such as losing a customer.
Gather event data that is filtered into segments by an array of properties, such as date range, country, and specific search terms. Then, use that filtered Mixpanel data to get deeper, more detailed analytics into your product performance.
Track customer engagement data, including a customer’s name and email address, as well as the date and time they last accessed your product. This allows you to run predictive analytics, which can show when engagement will likely drop or increase based on historical engagement data.
Get retention data for a specific cohort of customers by tracking signups and other relevant events during a specified date range. Then, you can feed that Mixpanel data into your analytics to provide a more comprehensive view of your retention trends over time.