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Analyze data with MongoDB Atlas and Microsoft Intelligent Data Platform

 

Customers are increasingly expecting engaging applications that are informed by real-time operational analytics, but meeting these expectations can be a challenge. It is well known that MongoDB Atlas is one of the most popular operational data platforms that can be used to manage critical business data efficiently at scale.

However, in some cases, enterprises may also wish to apply the insights that they have gained from data warehouses, business intelligence (BI), and related solutions. In order to apply analytics and governance solutions to operational data stores, many enterprises use the Microsoft Intelligent Data Platform.

Using the Microsoft Intelligent Data Platform, MongoDB and Microsoft have partnered together to simplify the process of gleaning and applying comprehensive analytical insights to data stored in MongoDB using the Microsoft Intelligent Data Platform. It is discussed in this article how enterprises can successfully use MongoDB with the Microsoft Intelligent Data Platform to build more engaging, analytics-driven applications with MongoDB.

Microsoft Intelligent Data Platform + MongoDB

The MongoDB Atlas provides a unified interface for developers so they can create distributed, serverless, and mobile applications. It supports a diverse range of workload types such as operational, real-time analytics, and search. Since it is possible to model graphs, geospatial data, tabular data, documents, time series, and other types of data, developers do not have to go with multiple niche databases, which will result in highly complex, polyglot architectures as a result.

As a result of Microsoft’s Intelligent Data Platform, it offers a single platform for databases, analytics, and data governance by integrating Microsoft’s database, analytics, and data governance products together under one umbrella. In addition to all the Azure database services, the Microsoft Intelligent Data Platform also features Azure Synapse Analytics for data warehousing and analytics, Power BI for BI reporting, and Microsoft Purview for enterprise data governance requirements.

Even though customers have always been able to apply Microsoft Intelligent Data Platform services to MongoDB data, doing so has not always been as easy as it could have been.

 As a result of this new integration, customers will be able to run analytics and data warehouse operations seamlessly on data they store in MongoDB Atlas, based on the operational data that they store in it. Using Microsoft Purview, customers will also be able to manage and run data governance policies against MongoDB data more easily, ensuring compliance and securing their most critical MongoDB data. Furthermore, with the use of Power BI, customers will be able to query and extract insights from MongoDB data with ease, using powerful inbuilt and custom visualization tools.

Let’s explore each of these integrations in more detail.

MongoDB Atlas and Azure Synapse Analytics operationalize insights

There are many types of workloads that MongoDB Atlas can handle, such as transactional, search, operational analytics, etc., which makes it a great platform for operational data analysis. The platform is capable of implementing a wide range of application types, such as distributed, serverless, mobile, and so on. In the case of data warehousing workloads, long-running analytics, and AI/ML applications, we complement Azure Synapse Analytics very well. There are a number of ways in which MongoDB Atlas can be integrated with Azure Synapse Analytics, either as a source resource or a sink resource. As a result of using this connector, you will be able to:

  • Get all the historical data from MongoDB Atlas into Synapse
  • To run SQL-based or Spark analytics on incremental data, retrieve incremental data in batch mode based on filter criteria

With the sink connector, you can store the analytics results back to MongoDB, which will then be able to power the applications enabled on top of MongoDB.

The presence of real-time analytics is essential in many enterprises, for instance, to detect fraud, detect anomalies in IoT devices, predict stock depletion, and maintain machinery in a timely manner. A delay in getting insights could have serious consequences. 

Business intelligence reporting and visualization with PowerBI

As a result of MongoDB Atlas and Microsoft PowerBI combining, customers now have access to a sophisticated real-time data platform with the ability to present both specialized operational and analytical query engines on the same data sets in real time.

MongoDB is also excited to announce the upcoming MongoDB Atlas Power BI Connector, which will offer Power BI users the opportunity to access the richness of JSON document data in MongoDB Atlas (see Figure 2). As a result of this MongoDB Atlas Power BI Connector, users will have access to their Atlas cloud data for the first time.

Beyond providing mere access to MongoDB Atlas data, this connector will provide a SQL interface to let you interact with semi-structured JSON data in a relational way, thereby ensuring you can take full advantage of Power BI’s rich business intelligence capabilities. Importantly, through the connector, support is planned for two connectivity modes: import and direct. This new MongoDB Atlas Power BI Connector will be available in the first half of 2023.

 

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