Process Data

Once data is collected, it will be processed, unified, and transformed. One of the biggest challenges companies are facing is setting up and maintaining processes that reliably collect and transform data so you can extract value from it any time you want. We are very experienced and have extensive knowledge of the way to go. 

We are experienced in ETL toolings such as Google Cloud Dataflow and the graphical version named Cloud DataFusion. Cloud Dataflow is an autoscaling ETL tool that unifies batch and streaming analytics. We also apply transformations in a data store such as Big Query, which is called ELT.

Customer identification by establishing an Identity Graph
A unique identifier can be used to link all of an individual customer's information from multiple sources so that it is accessible to all relevant teams and systems. We will build your company's unique Identity Graph to link and, as a result, keep track of all your customer interactions to be able to communicate one to one and to apply reliable measurement. Using Google Cloud Firestore or a Graph database, we build simple and sometimes complex unifications.

Google Cloud Dataprep is one of Google’s data services for cleaning and preparing structured and unstructured data for reporting, machine learning, and analysis. Dataprep interprets the data transformation through a proprietary inference algorithm. You can read the story on how we use Cloud Dataprep for our own needs in this article.