From collection and preparation to processing and interpreting, we’ve got you covered. You can focus on your business objectives and we’ll even help you to cut down your cloud costs.
Collecting raw data is the first step in the process. Data is pulled from all available sources, including sensors, data lakes and warehouses. It is very important that the sources are trustworthy and well-structured.
In this second step we clean and organize the raw data. The purpose of this step is to eliminate bad, incomplete or incorrect data.
We define the structure of the data and ensure that only usable data comes through the pipeline and is then entered into its destination. Not carefully screened data can produce highly misleading results.
During this phase the data is subjected to various means and methods of powerful technical manipulations using Machine Learning and Artificial Intelligence algorithms to generate an output.
You have total control over the data. It means you can decide how frequently you want to run the algorithm, how you want to visualize it and how much latency you want to tolerate.
The importance of this step is that it allows quick access and retrieval of the processed information. In addition, properly stored data is a necessity for compliance with data protection legislation like GDPR.