What data do I need for modeling? Are data types important? What if I have too many columns? We have highlighted few popular datasets so you can get to know Graphite better. After that, it's all up to you, collect your data and start having insights and fun!
Car Sales (source: GitHub) - The dataset contains monthly data on car sales from 1960 to 1968. It is great for our time series forecast model with which you can predict sales for the upcoming months.
Airline passengers (source: GitHub) - Every Data Scientist throughout his career runs by this dataset. It's a great test example for various time series forecast models, including ours too.
Daily admissions (source: dbenson.co.uk) - Machine Learning models can be applied in various fields. For example, this dataset contains daily admissions from a respiratory center. It can be used to predict the number of patients for future days with our Timeseries Forecast Model.
eCommerce orders example (source: dbenson.co.uk) - This is a demo CSV with orders for an imaginary eCommerce shop. You can use it for Timeseries forecasting, RFM model, General Segmentation, or New vs Returning Customers model in Graphite.
Mall Customers (source: Kaggle) - a demo Mall Customers dataset from Kaggle. Ideal for General customer segmentation in Graphite.