Google Cloud Dataprep

For proper preparation of our data, it is necessary to perform a series of operations involving the use of different algorithms. As we have anticipated, this work can take a long time and uses many resources. Google, within the Cloud service, offers the ability to do this job in a simple and immediate way: Google Cloud Dataprep.

It is an intelligent data service that allows you to visually explore, clean up, and prepare for structured and unstructured data analysis. Google Cloud Dataprep is serverless and works on any scale. It is not necessary to distribute or manage any infrastructure.

Google Cloud Dataprep helps to quickly prepare data for immediate analysis or for training machine learning models. Normally, the data has to be manually cleaned up; however, Google Cloud Dataprep makes the process extremely simple by automatically detecting schemas, types, joins, and anomalies such as missing values. With regard to machine learning, different ways of data cleaning are suggested that can make the process of data preparation quicker and less prone to errors.

In Google Cloud Dataprep, it is possible to define data preparation rules by interacting with a sample of the data. Use of the application is free. Once a data preparation flow has been defined, you can export the sample for free or run the stream as a Cloud Dataprep job, which will be subject to additional costs.

With the use of Google Cloud Dataprep, you can perform the following operations:

• Import data from different sources
• Identify and remove or modify missing data
• Identify anomalous values (outliers)
• Perform searches from a dataset
• Normalize the values in the fields in the dataset
• Merge datasets with joins
• Add one dataset to another through merge operations

These operations can be performed without the need for technological infrastructure in a very short time.