The democratization of data access has changed data management platforms. Cloud-based services, led by the likes of Google, Amazon and Microsoft, have broadened data access for many kinds of data users, creating a need to refine solutions to better suit collaboration needs. Microsoft's refinements to its Azure Synapse platform should prove handy for professionals with on-demand analysis needs.
What Is Azure Synapse?
First some basics on what Azure Synapse is. Azure Synapse is an analytics service that brings enterprise data into analytics and machine learning. Formerly known as Azure SQL Data Warehouse, its capabilities serve as a bridge across enterprise data sources to enhance data management. As a result, Azure Synapse can ingest, explore and analyze data at a petabyte scale. It allows users to pick data from a file, database or from the cloud, handling workloads from varied relational and non-relational databases.
Azure Synapse integrates with Power BI and Azure Machine Learning. Both platforms are still available individually, but Synapse provides the option to integrate these services seamlessly through the Synapse user interface. Another integration option is aimed at Apache Spark and SQL users. Azure Synapse includes Spark and SQL engines which makes it easier for SQL and Spark users to collaborate on the same data.
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New Features Ease Analytics Collaboration
Azure Synapse represents an analytics trend of data movement services within software or cloud solutions. Data movement is a kind of batch ETL (extract, transform and load). The details will vary by data sources and type, but data movement is a series of programmed tasks that usually occur among data sources to respond to a large of amount of queried data. When fetching data from different sources, it is possible that not all queries gather rows and columns the same way. The result is increased run time in matching rows and columns, establishing keys for user-made tables, or conducting data transformations. Thus the need for data movement platforms like Azure Synapse.
Microsoft has worked to make it easier for analysts to work with data in Azure Synapse. The company announced broader access with public preview of its Azure Synapse platform during its Build conference in May. It has added data management features since then. All the changes enhance Synapse to consolidate the view of data tables.
One example feature is a MERGE function which makes it possible to set inserts, deletes and updates in the user tables according to the row and column conditions in a separate table. The function eases making changes across multiple tables and helps save some time duplicating efforts.
Another example is column-level encryption, which allows users to set column-specific keys for privacy concerns. With column-level encryption, multiple users have access to the same dataset table yet may be limited in what data they have access to depending on their permissions.
These features ease collaboration between professionals with different querying knowledge and needs. The team can create a shared environment yet have a few tailored features for specific users. The end result is a better unified workflow across a team.
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Marketers Look to Analytic Solutions to Innovate
Marketers should work alongside IT and analysis professionals with tools like Azure Synapse. The heightened demand in online retail and services has raised the need to quickly mesh data from different sources. This is an essential step in developing deeper analysis, such as a cohort of customer lifetime value. As more and more business is conducted online, the pressure for analytic solutions to innovate their data management features only increases.
Azure Synapse should prove a good aid for marketers and analysts to explore advanced analysis options with data.