Diabetes can be discovered from some parameters well known to the medical community. In this way, in order to help the medical community and computerized systems, especially AI, the National Institute of Diabetes and Digestive and Kidney Diseases published a very useful dataset for training ML algorithms in the detection/prediction of diabetes. This publication can be found on the largest and best known data repository for ML, Kaggle at https://www.kaggle.com/datasets/mathchi/diabetes-data-set.

One of the crucial business dimensions is the dimension “Where”. It is necessary to know where a customer was born or where he lives. Where will the order be delivered? Where have there been more sales, and where can we sell more? Where are our stores located? From Where is the customer accessing our e-commerce? These and other principal questions use the “Where” dimension. Today the best service to provide geographic accuracy and quality for these data is Google Maps.

In the main software development methodologies there is always a chapter dedicated to testing. It is a mandatory approach to achieving quality in deliveries on an ongoing basis.

There are two types of test:

Globals are the core of the InterSystems IRIS for data persistence. It is flexible, allowing store JSON documents, relational data, object oriented data, OLAP cubes and custom data models, like Mindmaps. To see how to store, delete and get mindmap data using globals, follow these steps:

1. Clone/git pull the repo into any local directory

This is the third part of the series of articles on migrating from the main databases on the market to InterSystems IRIS. In this part, the procedures for migrating from DB2 will be detailed.As described in previous articles, there are currently a few options to do the migration. However, the two most popular options include the usage of DBeaver (https://openexchange.intersystems.com/package/DBeaver) or SQLGateway.