Maximize your Business Capabilities by Combining Azure Synapse and Power BI

Marketing Team
Published on December 19, 2021

Data storage and analytics are becoming increasingly important to any industry's growth as the digital transformation of business proceeds. Consider how to liberate data stuck in divisional and system data silos, how to protect data privacy and security, and how to offer insights cost-effectively and easily to create a data-driven culture. Microsoft's new Azure Synapse Analytics platform integrates data warehousing, data storage, data engineering, data transformation, Machine Learning modeling, and business intelligence tools to provide boundless analytics. A serverless SQL pool is included in A synapse analytics, and you can connect to a current data lake or establish a new one linked to the workspace. There's just too much in Azure Synapse to cover in a single blog article, so today we'll concentrate on the powerful combination of Data Warehousing and Power BI. Users can offer insights with Power BI by building interactive visualizations from data that has been acquired, organized, and stored in a data warehouse. The combination of these two features in Azure Synapse allows you to revolutionize your business using data.

What are the Advantages of Combining Azure Synapse and Power BI?

When combined, Azure Synapse and Power BI offer a best-in-class platform for all facets of the Modern Data Warehouse:

  • Azure data warehousing's security and flexibility automatically scale up and down to fit your needs, with the best cost/performance measurement available.
  • Spark and SQL engines built for the enterprise provide powerful processing solutions for a wide range of use cases.
  • The graphically rich business analytics capabilities of Power BI securely provide tailored insights to the right audience, in the right format, on any data.

Improved Analytics Delivers Tangible Business Benefits

Choose Azure Synapse to get more timely analysis which would allow you to make better and stronger decisions to reach improved outcomes. Data warehousing and Power BI enable data analysis, which leads to higher revenues, lower operational and supply chain expenses, and quicker entry into new markets. These solutions can also help the IT and business users be more productive by allowing them to spend less time wrangling data and more time evaluating and planning.

Cost-Effective Solutions

In terms of both money and effort, on-premise infrastructure is expensive. In the past, firms have paid more for data analytics solutions than they were ready to invest in terms of installation and upkeep. Implementation, deployment, and maintenance of Azure Synapse Analytics with Power BI are both less risky and less expensive. An applications manager in the retail pharmacy industry noted that by migrating to Azure for warehousing, storage, and computing, the company was able to save money "Our TCO (total cost of ownership) has been halved, and our performance has increased by three times. This equates to a six-fold increase in performance per dollar invested.”

Empower Users

With its BI and data warehousing capabilities, Azure Synapse Analytics delivers data in the hands of more users, allowing them to build their own analyses and valuable reports, speeding up change and improving business outcomes. Users can share data that they have secure, structured access to in a rich and meaningful way with Power BI's dynamic features.

Increased Flexibility

The extensive capabilities of Azure Synapse Analytics frequently result in additional business benefits beyond those that initially prompted adoption. Organizations find it simple to add new data sources or start new analytics projects once these solutions are in place. New Azure features can be included in the ever-evolving toolset as they become available, expanding capabilities as technology advances. Using Azure for analytics also opens up possibilities for artificial intelligence and machine learning!

Security and Privacy

Azure is well-known for being the most secure analytics cloud. The Azure platform, according to Donald Farmer, a well-known data industry thought leader, "has by far the most comprehensive set of compliance and security features of any cloud data warehouse provider." Microsoft has also recently added Dynamic Data Masking, which limits sensitive data exposure by masking it to non-privileged users, and Data Discovery and Classification, which classifies, labels, and further protects data, to help automatically protect sensitive data, enhancing data security and privacy.

What are the options available in Power BI?

Import: The tables and columns chosen from the Azure Synapse data source are imported into Power BI Desktop and stored in the computer's memory. Power BI Desktop uses the imported data and never touches the data source when you create or interact with a visualization (underneath the covers Power BI stores the data in an analysis services engine in-memory cache). To observe any changes to the underlying data since the first import or the most recent refresh (so it's not real-time), you must refresh the data, which imports the entire data set again (or utilize the PBI premium feature gradual refresh). The Power BI premium version has a 10GB dataset limit (with 400GB in preview, which is what Azure Analysis Services allows) and the Power BI free version has a 1GB dataset restriction. Note that when data is imported into memory, it is greatly compressed, thus you can import much larger datasets than these. In Power BI Desktop, go to Data sources.

DirectQuery: In Power BI Desktop, no data is imported or copied. Instead, Power BI Desktop searches the underlying data source of Azure Synapse as you create or interact with a visualization, ensuring that you're always viewing the most recent data in SQL DW (i.e. real-time). DirectQuery allows you to create visualizations over very large datasets where it would be impossible to do so otherwise (although, with support for 400GB datasets and Aggregation tables, the need to use DirectQuery because the dataset won't fit into memory goes away in many cases, and DirectQuery is only required if real-time results are required). See the list of data sources that DirectQuery supports.

Composite Model: Allows data from one or more DirectQuery sources to be easily combined in a single report, as well as data from a mix of DirectQuery sources and imported data. As a result, you can use numerous DirectQuery sources in conjunction with multiple Import sources.

Aggregation: Create an aggregated table from an underlying detail table (which will be in-memory if Import mode is selected) (which is set to DirectQuery meaning the detailed data is kept at the data source and not imported). If a user query requests data from the aggregated table, it will be retrieved from the in-memory table. Otherwise, a DirectQuery to the underlying detail table will be used. Using distinct summations from a single detail table, you can generate several aggregation tables. Consider aggregation tables to be mini-cubes, or a performance optimization strategy akin to indexes in SQL databases for speeding up SQL queries.

What’s new in Azure Synapse?

Two new performance features of Azure Synapse are:

ResultSet Caching: Query results are automatically cached in the user database for future use. This eliminates the requirement for recomputation by allowing subsequent query executions to retrieve results straight from the stored cache. Result set caching improves query efficiency (down to milliseconds) while also lowering computing resource consumption. Furthermore, queries that use cached results set do not consume any Azure Synapse Analytics concurrency slots and hence do not count against existing concurrency constraints.

Materialized View: A view that, like a table, pre-computes, saves, and maintains its data in SQL DW. When a materialized view is utilized, no recomputation is required each time. Queries that use all or part of the data in materialized views can perform better. Even better, queries can use a materialized view without referring to it directly, thus no changes to application code are required.

Power BI, Azure Machine Learning, and Azure Data Share are all related services on the Azure Synapse platform. When used together, Azure Synapse Analytics and Power BI become even more powerful, resulting in a unique, modern approach to data analytics. Azure Synapse enables Power BI professionals to deliver the scale, performance, and cost control that your projects require across a wide range of use cases. The Azure Synapse studio, a new shared web portal for building and maintaining diverse Azure Synapse artifacts, can be used to create interactive Power BI reports and enterprise-grade semantic models.