As fields such as Machine Learning, Big Data, Data Analytics, and Data Mining become more and more relevant to the industry, these fields have started to ask more from the people with the relevant skills in order to gain more momentum, traction, and ultimately a strong grip on the industries looking to affiliate themselves with the power and prowess that data and its analytics promise.

Consequently, businesses and companies have pitted themselves against each other to land themselves a person who has both the skills and the fortitude to turn their business upside down and to top it all, they are willing to splash tremendous amounts of cash for the same. So, if you also want to be one of those people, let us take a gander at the job prospects that these fields contain.

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Some of the key career paths and the requisite skills needed for one to choose and pave for themselves in the data science industry are:


A job profile that wants the complete package in a single person. Responsible for almost everything that happens in a data related project ranging from designing and implementation of models to mining and researching simultaneously, the work profile of a data scientist is as wide as it gets. Developing new models, researching and reporting of new methodologies, working with developers are some of the core functionalities of a data scientist, and in order to become one, one must have an extensive and applied knowledge of languages such as R, Python, Hive, SQL etc. along with unparalleled knowledge of statistics and computational modeling.


A data architect is the one responsible for designing and developing the underlying framework on which the entire business does its analysis, calculations, regressions, or whatever. Various forms of data require a completely different framework design in order to be implemented, which is why a data architect should be well versed in languages such as Hive, XML, SQL etc. in order to integrate the data set to a wide range of discrete systems and technologies.


All those sets of data and framework are of no use if there do not exist the proper algorithms, prototypes, and computational models that run according to the frameworks designed by the architects. This is exactly what the job profile of a data engineer is. To scan and sift the data for any abnormalities, sort it according to the use and demands of the analysts, and making sure that no redundancies exist in the final input data are some of the key highlights of a data engineers’ job, which require an immense knowledge of DBMS, API’s, and modeling tools.


Once the entire data set has been sorted, implemented on the required frameworks, updated according to the underlying algorithms, now comes the time to actually derive what the data is actually all about. This here is the job of a data analyst: to extract meaningful dissertations from the data, collect the useful and desired information, identify the various trends highlighted in it, and finally representing in a user-readable format are the key aspects of a data analyst, for which working on R and Python in order to understand and implement machine learning algorithms, working on spreadsheets, and above all; an analytical mind is what’s required.


Being the hottest industry in the world at the moment, the fields of data analytics and data science are really worth considering your future and career for. Join a data science course in hyderabad course today.

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