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.
ChartMogul can turn new and existing business intelligence data into valuable analytics that companies can use to improve their market performance. ChartMogul can take subscriber data - both created within ChartMogul and imported from other data sources - and generate visualized analytics for a variety of metrics that SaaS companies care about.
Bring all your ChartMogul data to Amazon Redshift
Load your ChartMogul data to Google BigQuery
ETL all your ChartMogul data to Snowflake
Move your ChartMogul 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.
Gather data about your subscription plans - like the subscription IDs, names, billing intervals, and the number of intervals that are charged at once - to evaluate the performance of each plan. This will help you better understand the effectiveness of your plans so that you can determine which ones are more or less successful as a whole.
Create, retrieve, or update data for new or imported customers in ChartMogul. This allows you to see important customer contact details, customer IDs, and valuable performance data including a customer’s MRR, ARR, and industry sector. You can then use that data to better segment your customers, which can provide more accurate and specific information about your business performance.
Import invoice data for customers that you are tracking through ChartMogul, including customer IDs, dates of purchase, transactions, and any relevant line items. Then, use ChartMogul to create subscription data for those customers and use that data to track more specific revenue data, both in ChartMogul and in your other data sources.
Track payments or refunds made on an invoice to see the transaction ID, type of transaction, transaction date, and whether or not the transaction was successful. This can help you get more accurate analytics from your invoice data. It can also indicate when there is an unusually high number of refunds, which could signal a problem worth addressing.
Get a list of subscriptions that ChartMogul has automatically generated from invoice data. This endpoint returns several IDs - including subscription IDs, customer IDs, plan IDs, and data source IDs - that will help you to more easily track and integrate data between any of those parameters to create deeper, more accurate business analytics.
Use tags to track terms that are associated with a customer so that you can segment or monitor them more specifically. For example, you could tag a particular customer as “high priority,” “returning” or anything else that is relevant to your business, and then retrieve a list of customers who have been tagged with those attributes in order to analyze them as a segment.
Update customer data with ChartMogul custom attributes that are more specific to the needs of your company. This can include both tags as well as more complex custom attributes. Then, track those attributes in ChartMogul to get analytics that are focused on your particular business concerns.