Data Collection
Bring in data from internal and external sources and gather information about data that will be processed.
Enable virtual data views and service APIs for consumption of data at any point in the system for reporting, analytics and decision making.
Enable iterative process of data discovery and data preparation for analysis. Enable Data Analysts or Data Scientists to use statistical learning, machine learning, deep learning, quantitative analysis and other analytical methods to gain insights from data.
Organizations, big or small; have large amounts of varying data to comb through in order to answer critical business questions. Data engineering is designed to support the process, making it possible for consumers of data, such as data scientists, analysts, and executives to reliably, quickly and securely inspect all of the data available.
Bring in data from internal and external sources and gather information about data that will be processed.
Process the prepared data into schemas and strictures. Assure quality level and collects robust metadata at each step.
Build services, API’s and/or message queues to distribute updates, changes and new data to downstream systems, applications and users (consumers), real time, near real time or batch.