Azure Synapse Analytics Features

Database (3)

Integrations (2)

Platform (3)

Processing (2)

Data Transformation (5)

Real-Time Analytics: Facilitates analysis of high-volume, real-time data.
Data Querying: Allows user to query data through query languages like SQL.
Reporting/Analytics: View and track pertinent metrics to find patterns and gain insights from data
Predictive Analytics: Predict future data based on historical data sets
Visual Analytics: Interact with data visualization elements, such as charts and graphs, to drill down into data

Connectivity (12)

Hadoop Integration: Aligns processing and distribution workflows on top of Apache Hadoop
Spark Integration: Aligns processing and distribution workflows on top of Apache Spark
Multi-Source Analysis: Integrates data from multiple external databases.
Data Lake: Facilitates the dissemination of collected big data throughout parallel computing clusters.
Real-Time Data: Receive data and information in real time
Data Capture and Transfer: Import, collect, and capture data from multiple sources
Trend Analysis: Review data from past periods to reveal recurring tendencies and predict future performance
What-if Analysis: Provides varying estimates based on different scenarios
Statistical Analysis: Apply statistical/mathematical models to sets of data
Data Blending: Merge data from multiple sources to a single data set
Ad hoc Analysis
Third-Party Integrations: Set up connections to third-party platforms to improve business processes

Operations (6)

Data Visualization: Processes data and represents interpretations in a variety of graphic formats.
Data Workflow: Strings together specific functions and datasets to automate analytics iterations.
Governed Discovery: Isolates certain datasets and facilitates management of data access.
Embedded Analytics: Allows big data tool to run and record data within external applications.
Notebooks: Use notebooks for tasks such as creating dashboards with predefined, scheduled queries and visualizations
Data Discovery: Discover and connect variety of data sources to the application for analysis

Additional Functionality (26)

Data Warehousing: Central repositories of integrated data from various sources
Drag & Drop: Assemble applications and processes by dragging over and arranging pre-built components
Activity Dashboard: Dashboard to view the status of ongoing processes, identify current incidents and track past activities
Data Connectors: Connect to big data sources
Ad hoc Reporting: Generate one-off reports that meet information requirements
Customizable Reports: Alter the layout and content of reports
Alerts/Escalation: System alerts about the need to escalate an issue or request
Templates: Sample files or documents that could be customized as needed or used as is
Forecasting: Form predictions based on past and present data/trends
Data Migration: Move from one database to another, or upgrade the version of database software being used
Data Transformation: Translate EDI formats into data suitable for use with company applications.
Access Controls/Permissions: Define levels of authorization for access to specific files or systems
API: Application programming interface that allows for integration with other systems/databases
Data Cleansing: Removes data that is incomplete, inaccurate, or irrelevant from a dataset
Data Synchronization: Synchronizing data between two or more devices/systems and automatically updating changes to maintain consistency
AI Copilot: A virtual assistant that uses AI to pursue goals and complete tasks on behalf of users
Dashboard Creation: Creation and customization of dashboards
Data Extraction: Automatically retrieve and pull information from documents, websites, images, data sets, and other sources
Data Security: Protect sensitive data for digital privacy
SSL Security: Security protocol that ensures secure, encrypted communication over the internet, safeguarding sensitive data from unauthorized access
Collaboration Tools: Provides a channel for team members to share media files, communicate, and work together
No-Code: Drag and drop/visual interfaces that allow non-tech users to build without writing code
High Volume Processing: Process and analyze large volume of data
Database Support: Supports common databases such as MySQL and Oracle
Search/Filter: Search and filter data across systems to locate required information by entering keywords or certain criteria
Generative AI: Use AI to generate content in the form of text, images, videos, etc.