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.
Intercom is a powerful set of tools for better managing your company’s customer support system. It includes a help center with a feedback system, which you can use to focus future articles on the growing needs of your customers, and it also provides a robust conversation system that allows you to assign support teams to customers based on specific criteria (about the customer or discussion topic), rather than just based on availability. Intercom is designed to create a more effective customer support network by specifically tracking and targeting your customers’ needs.
Bring all your Intercom data to Amazon Redshift
Load your Intercom data to Google BigQuery
ETL all your Intercom data to Snowflake
Move your Intercom 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.
Track the content of conversations and who is involved in them. This can be used to generate data about which topics customers are most concerned with so that you can further focus your support efforts accordingly.
Sort specific groups of users and companies that you are communicating with by creating an easily searchable tag that permeates all of your intercom databases, and you can use that tag to integrate other data about those groups throughout intercom.
Collect valuable customer data for your CRM, including basic contact info such as name, email address, and phone number but also more specific data, such as when they signed up, last signed in, and the tags associated with them.
Track the progress of your business relationship with companies (including a list of their users). Use that data to monitor how well your support network is meeting a company’s needs and how much of your overall revenue comes from each of the companies that are interacting with your business via intercom.
Automatically categorize users based on set criteria. Then Intercom can assign support teams based on that criteria, which allows you to more easily match customers with the support team members that can best assist them.