Data engineering is gaining prominence because of the fact that organizations are choked by a deluge of data ranging from logs in multiple formats to valuable business information lying unstructured in the vast Internet.
Data scientists who had to analyze and build models spent 80% of their time spotting and cleaning data. That’s when the need to fork their responsibilities came in, giving rise to a new breed of macho data engineers.
A data engineer comes to the rescue by understanding the data needed for a business, identifying the relevant new data sources, extracting the data in usable formats, making sure the data is error free and loading them for data scientists and analysts to work on.
Strong Data Warehouse skills with a thorough knowledge of Data Extraction, Transformation, loading (ETL) processes and Data Pipeline construction expertise stood out as the essential and basic qualifications of an ideal Data Engineer.
This blog was featured first on insideBigData and you can read the full article here.
Mobius has been a versatile player in the data space focusing on data extraction and data cleansing services, apart from collecting data from various external sources. We’ve also incorporated Machine Learning(ML) and Natural Language Processing(NLP) in our data extraction methods making it easy to digest huge volumes of unstructured data locked in pdfs and HTML pages. The data extracted is also presented in desired formats that can be easily injected into your system through APIs.
Get in touch with us to simplify your data extraction process!