Data science is a booming industry. Professionals from different segments are enrolling for data science courses to ace their career and keep in pace with the competition. A large number of organizations are switching to exploit data for deriving valuable insights and to subsequently aid business growth.
However, switching to data science or making a career in it is not that easy. To become a data scientist, one needs to have a desire to play with data. Besides, there is a plethora of skills that one needs to master to thrive career as a data scientist.
While as you get into the data science field, you will come to know about various focus areas. These focus areas will determine your expertise and compatibility for a specific job role.
Given below are 5 major areas in data science which are the key part of every big organization.
1. Data Engineering – Data engineers are responsible for transforming raw data into a useful format to facilitate its analysis. Their job involves managing sources, structuring data, quality determining, proper storage, and accessibility of data for easy usage by other analysts.
The skills needed by a data engineer include Python, SQL, Scala, Hadoop, Spark, ETL, Hadoop.
The job roles are available in the data engineering domain: Data Engineer, Database Developer, Data Analyst.
2. Cloud and Distributed Computing – Since a lot of organizations these days are switching to cloud infrastructure, there is a huge demand for professionals in this dedicated segment. Cloud computing and architecture generally involves designing and implementation of enterprise infrastructure and platforms for cloud and distributed computing. The job role involves analyzing system requirements to ensure that the existing applications have seamless integration.
The job roles are available in Cloud and Distributed Computing domain: Cloud Architect, Platform Engineer, Cloud Engineer.
3. Data Mining and Statistical Analysis – Data mining is a specialization concerned with deriving insights from data using methodologies. Technically, it refers to using statistical models, data analysis, and predictive models for analyzing hidden patterns and trends in data sources. The professionals in this job role address business problems using data findings. The data gathered could be transformed into several meaningful structures based on the type of business.
The job roles available in Data Mining and Statistical Analysis domain: Data Scientist, Statistician, Business Analyst.
4. Database Management and Architecture –
Database management and architecture refer to designing, deploying, and managing databases for high volume data. The database management systems enable establishing a link between types of data while providing provision for newer updates. The structured format of databases assists management to use complex data efficiently.
The job roles available in Database Management and Architecture domain: Database Analyst, Database Administrator, Data Specialist.
5. Machine Learning/ Cognitive Computing Development –
This is an advanced version of data mining and statistical analysis. The professionals involved in this field are responsible for building predictive models based on the use cases. However, these people are more involved in gathering inputs for feeding models. They create models/algorithms and train them with data to determine patterns from complex data sets.
The job roles available in this domain: ML Engineer, Cognitive Developer, AI Specialist, Researcher.