Azure Analytics and Power BI Narrative

Why a holistic Analytics stack makes all the difference

Data is the new oil, and businesses need to harness its power to stay ahead of the competition. However, data analysis can be challenging and costly without the right tools and platforms. That’s why Microsoft offers Azure Analytics and Power BI, two best-in-class products that enable businesses to analyze and visualize data in a fast, easy and secure way.

Azure Analytics and Power BI can help businesses of any size and industry to transform their data into actionable insights. Whether you are a citizen data analyst, a citizen data scientist or an analytics professional, you can use these products to access, combine, model and explore data from various sources with code-based or no-code/low-code approaches.

Azure Analytics and Power BI also offer various advantages over similar services and offerings like Databricks. They are fully integrated with each other and with other Microsoft products, offering a comprehensive and consistent data platform. They also offer more flexibility and choice for different types of users and scenarios. Moreover, they provide more security and governance features than Databricks, ensuring data protection and compliance. Finally, they enable faster and easier data analysis than Databricks, allowing you to connect directly to your data sources and use rich visualizations and filters.

Azure Analytics and Power BI have helped many businesses across different industries to improve their operational efficiency, agility and innovation. For example:

• Walgreens Boots Alliance reduced its data warehouse costs by 75% by migrating to Azure Synapse Analytics.
• Unilever reduced its data preparation time from weeks to hours by using Azure Data Factory and Power BI.
• ASOS improved its data quality and governance by using Azure Data Lake Storage Gen2 and Power BI.
• Marks & Spencer used Azure Machine Learning and Power BI to optimize its pricing strategy and increase its sales.

A match made in heaven

Azure Analytics and Power BI are two Microsoft products that enable businesses to analyze and visualize data to make better decisions. Azure Analytics offers a range of cloud-based services for data ingestion, processing, storage and analysis. Power BI is a unified self-service and enterprise analytics solution for businesses⁴. The service allows you to visualize your data and share insights across your organization or embed them in your app or website⁴.

These two products can work together to support different types of users: Citizen Data Analysts, Citizen Data Scientists and Analytics Professionals⁵. Citizen Data Analysts are business users who can query, combine and visualize data from various sources to create their own reports⁵. Citizen Data Scientists are business users with advanced analytical skills who can create data models and apply machine learning⁵. Analytics Professionals are IT experts or data specialists who are responsible for providing secure and scalable data platforms⁵.

Azure Analytics and Power BI offer these users various self-service capabilities. For example:

• Citizen Data Analysts can use Power BI Desktop or Power BI Service to create their own reports and share them with others. They can also access predefined datasets or create new datasets⁵.
• Citizen Data Scientists can use Azure Machine Learning to train and deploy their own models. They can also use Power BI to integrate their models with reports

Best in class

Azure Analytics and Power BI are best in class and superior compared to similar services and offerings like Databricks for several reasons. Here are some concrete advantages:

• Azure Analytics and Power BI are fully integrated with each other and with other Microsoft products, such as Azure Machine Learning, Azure Synapse Analytics, Azure Data Factory, etc. This allows you to leverage a comprehensive and consistent data platform that covers all your needs from data ingestion to data visualization¹³⁴.
• Azure Analytics and Power BI offer more flexibility and choice for different types of users and scenarios. You can use code-based or no-code/low-code approaches, depending on your preference and skill level¹⁴. You can also choose between different pricing models, such as pay-as-you-go or reserved capacity¹.
• Azure Analytics and Power BI provide more security and governance features than Databricks. You can use Azure Active Directory for identity management, role-based access control for data protection, sensitivity labels for data classification, etc¹³. You can also use Power BI Premium Gen2 for enhanced performance isolation and scalability¹.
• Azure Analytics and Power BI enable faster and easier data analysis than Databricks. You can use Power BI Desktop or Power BI Service to connect directly to your Azure Databricks clusters or Databricks SQL warehouses without any additional configuration or installation³. You can also use Power BI’s rich set of visualizations, filters, slicers, drill-downs, etc., to explore your data interactively³.

In contrast, Databricks is a more limited and complex service that requires more coding skills

Operational Advantages

In addition to the advantages already mentioned, Azure Analytics and Power BI also offer operational advantages that can help businesses improve their efficiency, agility and innovation. Here are some examples:

• Azure Analytics and Power BI can help businesses reduce their operational costs by using cloud-based services that scale on demand and only pay for what they use¹. For example, Walgreens Boots Alliance reduced its data warehouse costs by 75% by migrating to Azure Synapse Analytics¹.
• Azure Analytics and Power BI can help businesses increase their operational speed by using automated and streamlined processes that reduce manual work and errors¹. For example, Unilever reduced its data preparation time from weeks to hours by using Azure Data Factory and Power BI¹.
• Azure Analytics and Power BI can help businesses enhance their operational quality by using reliable and consistent data sources that ensure data accuracy and integrity¹. For example, ASOS improved its data quality and governance by using Azure Data Lake Storage Gen2 and Power BI¹.
• Azure Analytics and Power BI can help businesses foster their operational innovation by using advanced analytics and artificial intelligence capabilities that enable new insights and opportunities¹. For example, Marks & Spencer used Azure Machine Learning

Sources:

(1) Power BI in Azure | Microsoft Azure. https://azure.microsoft.com/de-de/products/power-bi/

(2) Power BI usage scenarios: Managed self-service BI — Power BI. https://learn.microsoft.com/en-us/power-bi/guidance/powerbi-implementation-planning-usage-scenario-managed-self-service-bi

(3) Customer Success Stories | Microsoft Power BI. https://powerbi.microsoft.com/en-us/customer-showcase/

(4) Customer and Partner Success Stories | Microsoft Azure. https://azure.microsoft.com/en-us/resources/customer-stories/

(5) Now it’s personal: Unilever’s digital journey leads to real results for …. https://news.microsoft.com/source/features/digital-transformation/now-its-personal-unilevers-digital-journey-leads-to-real-results-for-consumers-and-employees/

(6) Power BI usage scenarios: Self-service real-time analytics. https://learn.microsoft.com/en-us/power-bi/guidance/powerbi-implementation-planning-usage-scenario-self-service-real-time-analytics

What now?

How about migrating to Power BI — let me show you how

Re-think your whole Analytics Architecture altogether, maybe