It is no more secret today that the key to a successful business is a data-driven decision making. Data lies at the heart of the decision-making process of all the organisation today and that has prompted the evaluation of data based job roles in the industry likeData Analyst,Data EngineerandData Scientists. So lets clear out what are the major differences between these jobs and skills needed to achieve them and their average salary.
A data analyst is the one that gathers, investigates and represents data in a way so that everyone can understand it. The data that is gathered by data analyst usually comes from a single source. They are responsible for cleaning, organising and translating raw data into actionable business insights, which are further used by the organisation to make data-driven decisions. Data visualization is a vital part of their professional day to day routine.
collect & interpret data from source
Analysing the results using statistical techniques
extract data from primary and secondary data sources
maintain databases systems and update it
data mining , structure the raw data
basic programming knowledge such as R, Python ,SAS etc
SQL/Data base knowledge
knowledge in any data visualization tools such as Tableau,Qlikeview and powerBI
average salary: 65k USD to 107k USD per annum
Data engineers are the ones who are responsible for building and optimizing the system that are needed by the data scientist and data analyst to perform their tasks. They construct data pipelines for the organizations, meaning that they ensure that the data is accessible to anyone who needs to work on it. Along with that the primary responsibilities of Data engineer include ensuring that the data is properly received , transformed and stored along with building infrastructure . We can say that Data engineers and data scientists work closely together with data. So basically data engineers report to data scientists with "big data" that they prepare in order to be analyzed by the scientist.
Develop, construct, test and maintain the architecture
Provide and implement theways in whichto boosttheresponsibleness,efficiencyand quality ofthe information
To build the data pipelines
create and integrate APIs
Develop the data set processes for data modelling, mining and production.
Expirence in Hadoop, MapReduce , Pig, Hive, Programmming, Data streaming
Database system, with knowledge in SQL and NoSQL database
Applied maths and statistics
Average salary: 80k USD to 170k USD per annum
A Data scientist is a professional who analyses the data strictly from a business point of view and is responsible for delivering the predictions that aid in business value. They deal with both structured and unstructured data. They also identify the right arenas of data from where they can find relevant patterns so as to help in case any business-related problem arises. They extensively use machine learning for their prediction purposes, so training and optimizing data models is a vital part of their professional day to day routine. They are also more adept to making better business judgements.
Select features, build, and optimize classifiers by using the machine learning techniques
Performing data mining and analysing by using the latest techniques
Perform proper data analysis by processing, sorting and data integration
Develop data algorithms & models
Perform predictive analysis using the concept of machine learning & predictive algorithms
Requries strong business acumen & advanced data visualization competencies
Must have proficiency in any programming languages such as Python, R, Java, C/C++ or SAS
Big data Hadoop, machine learning or deep learning
Average salary: 95k USD to 250k USD per annum