The Jupyter does an impressive job of hiding its power behind a simple user interface.With the concise interface and design, users can easily handle the software without any help.We no longer have to squint or click around in search of the feature we’re trying to access: The button is right there in that simple interface for us to tap.Its emphasis on performance and a its intriguing minimalistic user interface will attract a lot of well-deserved attention. You can generate plots, histograms, power spectra, bar charts, errorcharts, scatterplots, etc, with just a few lines of code, because matplotlib tries to make easy things easy and hard things possible. Matplotlib, a python 2D plotting library which produces publication quality figures in a variety of hardcopy formats and interactive environments across platforms,is included in Jupyter. Jupyter roles as a excellent data visualization platform for data in MultiDBs. By login into the system, users can check their notebooks. Each document for each user can be saved to our server. IPython Notebook is a is a web-based interactive computational environment where you can combine code execution, text, mathematics, plots and rich media into a single document.In Jupyter,data imported from MultiDBs database can be analyzed and viewed in different ways using python by implement Ipython Notebook. It aims to utilize iPython(Jupyter) notebook to do data analysis on MultiDBs datasets. MultiDBs INotebook Project is a sub-project for MultiDBs project.