![]() Here I’ve checked the statistics on fields’ data types: the percentage of data types used for this field in all the documents within the collection. On the main page of the “athletes” collection, I’ve checked the information about the collection, edited the data in an interactive mode and tried out simple and complex queries.Ī schema visualization tool helped me understand my data. This helped me to analyze the presence of documents, data types and the distribution of values for specific fields within the collection.įirst of all, I connected to the MongoDB instance running on localhost using the Compass application. jsonArray Understanding the Data with CompassĪt first, I’ll mention some database management features.Ĭompass is able to generate histograms to represent the data frequency. To import this into MongoDB, I’ve executed the following command in the CLI: mongoimport - db - collection athletes - type json - file athletes.json This dataset has a typical JSON structure which is different from the format required by MongoDB. We will load data into a pivot table and explore the possibilities this offers.Īs a data source for my research, I’ve chosen a dataset on 120 years of Olympic history and results. The second part is dedicated to further MongoDB data analysis. Then you can explore what functionalities Compass offers and what analysis you can conduct using this tool. The first part of the visualization process is to set up a connection to a MongoDB database with Compass. I’ve managed to embed it into my Angular 4 application and used it for data analysis. While Compass is a stand-alone application, I’ve discovered that Flexmonster is integrated directly into the web project. Flexmonster Pivot Table is a tool for advanced web reporting and analysis.The intuitive interface helped me to focus on the meaning of data. It provides a real-time view of your data. Compass is a GUI application for in-depth analysis and visualization of MongoDB data and a collections’ schema. ![]() I wanted to work out a workflow for data analysis which combines database management analysis, data aggregation and data visualization. My goal was to analyze a dataset from a MongoDB database. Today, I want to tell you about my experience in exploring such visualization tools. With a myriad of visualization tools available, it is hard to find the right one for MongoDB data which has out-of-the-box functionality. ![]()
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