We are in the era of automation , the key focus of any organization at present time is to drive maximum business value by analyzing the data as efficiently as possible , hence for this every business is menting out ways to collect more and more deeper and essential insights out of there customers , in order to understand them better and create value for them in the best possible way beating up there competition.
Since the past 10 years , with the advent of new technologies the collection of data has fairly increased . The internet penetration even in the remote regions of the country has drastically increased mainly during the past 3-4 years due to the mind boggling policies of the telecom giants of the country ,with their affordable internet plans as well as due to the influx of heavy dependency on the internet during the hard time of the covid outbreak. This has resulted in more people leaving their social footprints of data in the doorsteps of several organizations hungry for it , than ever before in time. These policies have made us a complete slave of the information (sadly both fake and real ) on the internet in this information era.
This situation has led organizations to rethink their IT infrastructure , because organizations can dig a goldmine of information about their product, services and customers and use it to their advantage , like never before, by providing ultimate user experience to clients. But the incoming data is now “ Big Data “ thus , more higher availability , better speed , lesser downtime , live streaming of data and scalable storage solutions are required for the data managementtoday , which has created a whole new world of jobs for the data professionals in the field of Data Engineering , Data Analytics , Data Science , Business Analysis , Machine learning , Cloud system administrators and some other fancy jobs trending in market in the present time. The whole crux of any ofthese things invented by humans is to try out each and every way to retain customers and make them get accustomed to using your product or services
Some roles are business-oriented, some involve more engineering, some focus on research, and some are hybrid roles that combine different aspects of data management. Until the last decade data science was considered as the prime job in the market but now, data engineering is the next big thing in the data field of work because of much more jobs , which is because of the high number of clients interested in ripening the fruits of good data management.
What is Data Engineering
Data Engineering is one of the most foundational steps in the complete data management infrastructure , though it is difficult to exactly define it because various companies use the term vaguely , for example some consider data engineering as an extension of Analytics , some take it as an extension of Software engineering , some as senior Database Administrators etc but the most basic thing which differentiates all these roles is that "Data engineers work with the platforms while Data scientists work with businesses , it's the job of data analysts to know both the fields and dwellthem together".
Mostly a data engineer works in some or all of these 6 key areas:
- Data ingestion - Extracting data from sources in correct formats without errors as fast as possible.
- Data warehousing - Storing the data in a repository or a format for further usage like data modeling , data transformation , ETL etc
- Enable analytics - Exposing the data to the analytics applications for data scientists /analysts to use it for further business based grilling of it.
- Data Applications - Developing or assisting in productized analysis - whether simple spreadsheet reports, to simple webforms, to full featured web or mobile applications.
- Database Management - Understanding of different SQL , NoSQL , Oracle , Hadoop , Linux , Hive , Scala based database systems and managing data efficiently and handling live CRUD operations.
- Cloud Integration / Migration - Managing data platforms hosted in a mix architecture with cloud and on premise traditional DBMS’s and Migrating complete data infrastructures to Cloud ( AWS , Azure , GCP ).
Key things in modern day Big Data Projects
Today we see most requirements with data stack changing rapidly and new tools and frameworks coming in every now and then to have a robust architecture which is scalable and maintainable in the long term . Hence the need for maintaining a changelog of the infrastructure changes and tweaks for further review is a must today. We also need to constantly communicate with and reflect on the exact needs of clients by working possibly in an agile project framework to utilize the best possible outcomes from the available resources.
How GeoPITS can help you
We help you to elevate and evaluate your business operations using streamlined data management. Making data as a single Source of Truth for your business is our mission . We actively manage around 900+ Databases, 75+ Database Migrations to Cloud , 2M+ Database transactions per day for around 60+ clients in India and worldwide.
Get in touch with our team for more details by clicking this link - https://geopits.com/contact