Microsoft is the world’s largest software company. Founded in 1975 and headquartered in Redmond, it has become a household name, primarily due to its Windows operating system and Office suite. Aside from these products, Microsoft has a vast range of enterprise software and cloud offerings including its own database, browser, various servers and ERP solutions.
Microsoft’s strategic development in the BI area dates back to 1996 when it purchased OLAP technology from Panorama. In just a few years Microsoft moved from being a surprising entrant into the OLAP market to become the market share leader. Its main database technologies are bundled in SQL Server, which many companies use today to build a central data warehouse.
With Microsoft Azure, comprehensive and innovative options for data and analytics are available. Azure consists of several data storage, data processing and analysis services. For data warehousing needs, Microsoft positions Azure Synapse Analytics (former Azure SQL Data Warehouse) and Azure Data Factory. Azure Data Factory is a dedicated managed cloud service for data integration projects. It is also able to run SSIS logic.
In Microsoft architectures, the above components work closely together. For example, Azure Synapse Analytics uses Azure Storage (which is also included in Azure Data Lake Storage) for data storage. Combined queries from warehouse data and big data or operational data (e.g., from Azure Cosmos DB) can be created via an Azure Synapse Link tool.
User & Use Cases
Only 14 percent of the survey respondents use Azure Synapse Analytics and another 14 percent use Azure SQL Data Warehousing. Meanwhile, 57 percent of respondents use Azure Data Lake Storage. Data Lake Storage is a distributed file system optimized for analytics. Special functions for data warehousing and data integration are not included in the strict sense of these terms. Data loading and queries are possible by using additional services. Against this background of more than 50 percent of respondents rating a file system, the distribution of tasks in the chart above is not easy to understand. For example, we would have expected the share of data storage/data provisioning to be significantly higher, and for data warehousing, data integration, data warehouse automation and data stewardship to be significantly lower down the list of tasks.
Even from an Azure Synapse Analytics perspective, this distribution would raise questions. From a purely technological point of view, Azure Synapse Analytics is limited in its functionality for data stewardship/data quality. Nevertheless, 38 percent of users taking part in this survey claim to perform this task. The only possible explanation here would be that data quality is understood as data adaptation and harmonization in the data preparation process.
Azure is used in companies of all sizes. The services are easy to consume and can easily scale with customers’ requirements. Azure is used by a median of 9 users per company, but the mean of 802 users is surprisingly high and indicates that there are some very large deployments out there. Perhaps some survey respondents included all analytical users in their user numbers.
Number of users using Microsoft Azure
Number of technical users using Microsoft Azure
Company size (number of employees)
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