www.dasca.org

Data scientists refer to those professionals who provide context to the vast amounts of data that can be generated from a particular organization and provide it as actionable intelligence that acts as a major compass for the direction the company wishes to progress towards. This data is received from several source metrics, including transactions histories, sensors, social media, log files and GPS plot-points. Their objective is to discern and create valuable and predictive insight that ha huge sway on business decisions and utilized for optimizing/developing the overall harmony of operations. With progres in technology, access to faster internet speeds and greater processing power allows us to develop innovative tools for examination of data and simple, consistent use of cloud-oriented solutions. The technical benefits of having a data science department at an organization has made it one of the most promising and lucrative IT careers, with an estimated average earning package of $85,000-$90,000. The scope of earning increases as the professional diversifies and/or specializes, as time goes on.


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Here are some of the skills required and daily responsibilities of data scientists-

•In-depth data mining, creating sustainable models, and generating hypotheses are among some of their chief tasks which are in direct support of high-level business goals.

•Expected to stay up to date with the latest tools for analysis, machine learning, modelling, etc if they are to be accurate.

•Strong educational background in statistics, business, mathematics, and computer science.

•Communication skills must be top notch- to process and present data-oriented context, both visually, and verbally

•Data scientists use custom algorithms to determine incomplete data sets and help solve analytical errors.

•Big data scientists utilize presentation skills to be effective. Relevant information must be acquired from verified sources and present in the form of understandable visualizations.

•Many data scientists use Hadoop – an open-source Apache framework – to analyze & mine big data sets.

•Comprehensive machine learning expertise allows big data professionals to use SQL, Python, Unix, PHP, R and Java – which they utilize to alter or develop custom analytical models and solutions.

•Data scientists must be capable of operating in a team with a diverse composition- consisting of with managers, IT administrators, programmers, statisticians, graphic designers, and experts in the company’s products or services.

IT- Oriented Professionals

There are two main types of positions that may be delegated here, namely Hadoop Developer and Hadoop Administrator in terms of the manner in which roles are delegated. Hadoop is a sophisticated data analytics platform, which is affordable and flexible in usage. The professionals who operate within these parameters try to design, develop and implement different kinds of data processing applications with live updating technology. As such, extensive knowledge of the Hadoop framework becomes essential. Hadoop Administrators also ensure their focus is on configuring, deploying and maintaining Hadoop clusters.

Analysis- Oriented Professionals

These individuals are suited to positions in which are familiar with big data analytics mechanisms, and the primary types of jobs here are data analyst and data scientist. A standard education just does not cut in in these positions and data science certifications, with role specializations are considered very important. A career in big data will be hugely rewarding the coming years, and there is a need for professionals who analyze, manipulate data and derive meaningful insights. A big data professional deals with big data applications, but also the total scope of the data being interpreted for the sake of accurate analysis. These are the professionals that drive change and are able to harness the potential of big data analysis in the coming years.

More info: dasca.org

Big Data Career

www.dasca.org

Types Of Careers In Big Data

Data scientists refer to those professionals who provide context to the vast amounts of data that can be generated from a particular organization and provide it as actionable intelligence that acts as a major compass for the direction the company wishes to progress towards. This data is received from several source metrics, including transactions histories, sensors, social media, log files and GPS plot-points. Their objective is to discern and create valuable and predictive insight that ha huge sway on business decisions and utilized for optimizing/developing the overall harmony of operations. With progres in technology, access to faster internet speeds and greater processing power allows us to develop innovative tools for examination of data and simple, consistent use of cloud-oriented solutions. The technical benefits of having a data science department at an organization has made it one of the most promising and lucrative IT careers, with an estimated average earning package of $85,000-$90,000. The scope of earning increases as the professional diversifies and/or specializes, as time goes on.


Show Full Text

Here are some of the skills required and daily responsibilities of data scientists-

•In-depth data mining, creating sustainable models, and generating hypotheses are among some of their chief tasks which are in direct support of high-level business goals.

•Expected to stay up to date with the latest tools for analysis, machine learning, modelling, etc if they are to be accurate.

•Strong educational background in statistics, business, mathematics, and computer science.

•Communication skills must be top notch- to process and present data-oriented context, both visually, and verbally

•Data scientists use custom algorithms to determine incomplete data sets and help solve analytical errors.

•Big data scientists utilize presentation skills to be effective. Relevant information must be acquired from verified sources and present in the form of understandable visualizations.

•Many data scientists use Hadoop – an open-source Apache framework – to analyze & mine big data sets.

•Comprehensive machine learning expertise allows big data professionals to use SQL, Python, Unix, PHP, R and Java – which they utilize to alter or develop custom analytical models and solutions.

•Data scientists must be capable of operating in a team with a diverse composition- consisting of with managers, IT administrators, programmers, statisticians, graphic designers, and experts in the company’s products or services.

IT- Oriented Professionals

There are two main types of positions that may be delegated here, namely Hadoop Developer and Hadoop Administrator in terms of the manner in which roles are delegated. Hadoop is a sophisticated data analytics platform, which is affordable and flexible in usage. The professionals who operate within these parameters try to design, develop and implement different kinds of data processing applications with live updating technology. As such, extensive knowledge of the Hadoop framework becomes essential. Hadoop Administrators also ensure their focus is on configuring, deploying and maintaining Hadoop clusters.

Analysis- Oriented Professionals

These individuals are suited to positions in which are familiar with big data analytics mechanisms, and the primary types of jobs here are data analyst and data scientist. A standard education just does not cut in in these positions and data science certifications, with role specializations are considered very important. A career in big data will be hugely rewarding the coming years, and there is a need for professionals who analyze, manipulate data and derive meaningful insights. A big data professional deals with big data applications, but also the total scope of the data being interpreted for the sake of accurate analysis. These are the professionals that drive change and are able to harness the potential of big data analysis in the coming years.

More info: dasca.org

Big Data Career