The increasing use of Electronic Health Records (EHRs) enables a better analysis of patient data, improving the quality of medical care. EHRs must be processed in order to provide a variety of services to the physician, such as risk classification and summarization. EHRs usually are stored in unstructured text or Excel files containing different data formats and types, missing information, and, sometimes, inconsistent information. Therefore, before analyzing the data, we often need to transform and integrate it. In this presentation, we show some examples of data integration tools that can be used to extract and transform data. As example, we use an Excel file containing exam information regarding patients with ALS (Amyotrophic Lateral Sclerosis).