Learn basic analysis with this Learnvest article.
How to Do Basic Data Analysis in Excel
All the formulas in Excel are already labeled—but if you want to do more advanced analysis, why not import your raw data from a source? With my Data Analysis Toolpak add-in, you can quickly and easily browse hundreds of charts and graphs in Excel and simply download them to your computer. With open source tools like GraphicsBeat and Malware Scanner & MalwareRadar, it’s simple to save your data into your own source code, so you can run analysis projects yourself. I recommend starting with this option if you have access to a Java library like, but I also recommend visualizing your charts and graphs using 3D Merge, Visual Sentry, and Narrator. If you have Access, you can use Microsoft OneNote to add text to a chart in Excel, or import a one-sheet file to VisualBase Pro to run your data quickly.
If you’re interested in data exploration, look into the DataScaler add-in. This add-in is great for data mining and chart processing as it does all the work for you, running in a background process in its background without your knowledge, while allowing you to connect to servers with Google Cloud, OpenTree, Microsoft Azure, Amazon Web Services, and StorageTitan.
If you’re thinking about using DataScaler to build a data visualizer, check out the DataScaler Makeover tool. Most of the time, I suggest visiting a source like CodeJournal to share your code with fellow coders and join the GitHub Project. Once you’ve created some code, it’ll be automatically transferred into the source code like Visual Beat or Linux Journal and then run as a command line. You can also create a database, import sources and data, or export in Excel. In addition to starting off with a clean store, I recommend reading through some data creation and visualization guides.
Moscothar made a great Android/iOS data analysis app that supports multiple data types. Mogothar has several parts: FileView and DataStream, the first visualizations, an easy-to-use SDK for app-building and data modelling, and DataGrid which is the visualization component. In addition to the DataStream Visualizer app (which is iOS-only) you can download the SDK and access DataStream data in VisualBase Pro, Visual Sentry, or Narrator to run the VisualStream Visualizer. In the end, we hope that you get some exposure to data visualization and that you try some of these visualizations with your data in VisualBase Pro. The Linux Journal extension is a nice feature. If you’re making a high-performance computation project (think machine learning or cryptography), this is one of the best visualizations for doing math and statistics.