GIANT Stories at MongoDB

Make Data-driven Decisions using MongoDB and Looker

Seth Payne

Company, BI

Today we are announcing a partnership and integration with Looker, a leader in modern, user-friendly business intelligence solutions. Like most BI tools, Looker works well with relational data, so the integration with MongoDB is made possible through the MongoDB Connector for Business Intelligence.

Using a simple, yet highly functional and powerful interface, Looker can ingest data from a number of different data sources empowering business users to create and manage reports and dashboards and make data-driven decisions. Now that MongoDB data can be queried by Looker directly, this removes the need to perform any ETL operations on MongoDB data.

Adding MongoDB as a data source is simple and can be accomplished through Looker’s admin interface for connections. The simplest way to get data into Looker is to use MongoDB Atlas, our DBaaS offering. Alternatively, customers can also connect to on-premises of self-managed instances. Due to MongoDB’s distributed architecture, you can connect to a dedicated secondary replica assigned to analytics and report away without impacting operational workloads running against other nodes in the cluster.

By combining the flexibility of MongoDB, along with Looker’s simple, intuitive, yet powerful interface, business users can quickly and easily gain insights from their MongoDB data. Users can create and manage dashboards, schedule reports, and even share these with colleagues. With Looker and MongoDB, business users can better understand data, identify trends, and make timely decisions based on solid analysis.

To learn more about MongoDB’s integration with Looker, please stop by our booth at Looker JOIN 2018 this week in San Francisco. There you will see hands-on demonstrations of the integration and examples of reports and dashboards that can be created using MongoDB and Looker together.

MongoDB’s BI Connector the Smart Connector for Business Intelligence

Ken W. Alger

Cloud, Atlas, BI

In today's world, data is being produced and stored all around us. Businesses leverage this data to provide insights into what users and devices are doing. MongoDB is a great way to store your data. From the flexible data model and dynamic schema, it allows for data to be stored in rich, multi-dimensional documents. But, most Business Intelligence tools, such as Tableau, Qlik, and Microsoft Excel, need things in a tabular format. This is where MongoDB's Connector for BI (BI Connector) shines.

MongoDB BI Connector

The BI Connector allows for the use of MongoDB as a data source for SQL based business intelligence and analytics platforms. These tools allow for the creation of dashboards and data visualization reports on your data. Leveraging them allows you to extract hidden insights in your data. This allows for more insights into how your customers are using your products.

The MongoDB Connector for BI is a tool for your data toolbox which acts as a translation layer between the database and the reporting tool. The BI Connector itself stores no data. It serves as a bridge between your MongoDB data and business intelligence tools.

MongoDB BI Connector Flow

The BI Connector bridges the tooling gap from local, on-premise, or hosted instances of MongoDB. If you are using MongoDB Atlas and are on an M10 or above cluster, there's an integrated built-in option.

Why Use The BI Connector

Without the BI Connector you often need to perform an Extract, Transform, and Load (ETL) process on your data. Moving it from the "source of truth" in your database to a data lake. With MongoDB and the BI Connector, this costly step can be avoided. Performing analysis on your most current data is possible. In real-time.

There are four components of a business intelligence system. The database itself, the BI Connector, an Open Database Connectivity (ODBC) data source name (DSN), and finally, the business intelligence tool itself. Let's take a look at how to connect all these pieces.

I'll be doing this example in Mac OS X, but other systems should be similar. Before I dive in, there are some system requirements you'll need:

  • A MongoDB Atlas account
  • Administrative access to your system
  • ODBC Manager, and
  • The MongoDB ODBC Driver for DSN
  • Instructions for loading the dataset used in the video in your Atlas cluster can be found here.

    Feel free to leave a comment below if you have questions.

    Get started with MongoDB Atlas today to start using the MongoDB Connector for BI to examine and visualize your data.

Just Released: MongoDB ODBC Driver

Seth Payne

Releases, BI

Earlier this month, we released the new ODBC driver for the MongoDB Connector for Business Intelligence (BI Connector). In this post, we’ll walk through installation and setup of an ODBC connection on Windows 10 running the 32bit version of Excel.

Using Power BI to Gain Insight Into your MongoDB Data

Seth Payne

Technical, BI

We are happy to announce updates to the MongoDB Connector for Business Intelligence for use with Microsoft’s Power BI Desktop. Now, it is simpler than ever for Power BI users to access data stored in MongoDB and use Power BI’s powerful analytical and visualization tools to gain insights into the data, and then effectively share these insights with colleagues.

Within just a few minutes, you can expose MongoDB data directly to Power BI to begin creating meaningful charts, dashboards, and reports.

MongoDB as a Data Platform for Business Intelligence

As both MongoDB’s popularity and adoption continue to rapidly grow, organizations are choosing MongoDB as the data platform that supports a variety of applications where tabular, or relational, database systems had been used historically. MongoDB’s document data model presents the best way to work with data for business critical applications, while distributed systems design allows users to intelligently put data where they want it, and enable the freedom to run anywhere - on premise or in the cloud.

But data platform environments are rarely, if ever, homogenous. And, given both the longevity and large install base of enterprise RDBMS, it is common for MongoDB to be part of a larger ecosystem that includes a variety of data sources, many of which are tabular in nature. Because of the need to manage data from multiple systems, administrators are looking for ways to expose all their data to their non-technical business users in a consistent and friendly way, no matter where that data is physically stored.

The MongoDB BI Connector enables Power BI users to easily query, analyze and visualize data stored in MongoDB in the same manner as with other Power BI data sources. No knowledge of MongoDB or the MongoDB Query Language (MQL) required!

Exposing MongoDB Data To Power BI Desktop

One of the benefits of using MongoDB as a platform for BI, is that it eliminates the need for complex ETL operations. BI data workloads can be isolated; separating operational workloads from analytics on separate replica nodes, all operating as a part of the same cluster. The data can also be exposed directly to end users without the need to modify and transfer data before it becomes available to analysts.

Power BI can import MongoDB data through a direct connection to the MongoDB BI Connector or, via ODBC. Once a data connection has been defined, simply select the data you want to work with and import it.

After the import is complete, you can begin working with the data in Power BI Desktop as you would with any data source. If you need to refresh your data, you can easily do so at any time.

Data that resides right in your app is a gold mine when it comes to understanding your customers, but who has time to wait for nightly ETL workflows? With the MongoDB Connector for BI you can take control of your data and get to insights faster. See just how quickly you can discover something!

New to MongoDB Atlas — Fully Managed Connector for Business Intelligence

Driven by emerging requirements for self-service analytics, faster discovery, predictions based on real-time operational data, and the need to integrate rich and streaming data sets, business intelligence (BI) and analytics platforms are one of the fastest growing software markets.

Today, it’s easier than ever for MongoDB Atlas customers to make use of the MongoDB Connector for BI. The new BI Connector for Atlas is a fully managed, turnkey service that allows you to use your automated cloud databases as data sources for popular SQL-based BI platforms, giving you faster time to insight on rich, multi-structured data.

The BI Connector for Atlas removes the need for additional BI middleware and custom ETL jobs, and relies on the underlying Atlas platform to automate potentially time-consuming administration tasks such as setup, authentication, maintaining availability, and ongoing management.

Customers can use the BI Connector for Atlas along with the recently released MongoDB ODBC Driver to provide a SQL interface to fully managed MongoDB databases. This allows data scientists and business analysts responsible for analytics and business reporting on MongoDB data to easily connect to and use popular visualization and dashboarding tools such as Excel, Tableau, MicroStrategy, Microsoft Power BI, and Qlik.

When deploying the BI Connector, Atlas designates a secondary in your managed cluster as the data source for analysis, minimizing the likelihood an analytical workload could impact performance on your operational data store. The BI Connector for Atlas also utilizes MongoDB’s aggregation pipeline to push more work to the database and reduce the amount of data that needs to be moved and computed in the BI layer, helping deliver insights faster.

The BI Connector for Atlas is currently available for M10 Atlas clusters and higher.