A lire sur: http://cloudtimes.org/2013/05/20/what-it-takes-to-be-a-big-data-analyst/
Big Data
is in. There is a huge demand not only for Big Data Scientists but for
Big Data Analysts as well. While a big data scientist needs various
capabilities and skills to analyze and mash up various data sources, a
big data analyst on the other hand performs data analysis on a
particular system only. In short, a big data analyst is some sort of an
assistant to the big data scientist.
Because a big data analyst’s job description is almost similar to that of a big data scientist but on a smaller scale, the skills required are also the same as that of a big data scientist. He must be able to support management and business with insightful and clear analyses. He must be knowledgeable about modeling techniques; data mining; as well as explaining, creating, and testing data in order to provide a concise and clear report.
A big data analyst also needs to have a deep understanding and experience about business intelligence and real-time analytics. He has to be adept with various statistical applications, programming languages, and SQL databases. MapReduce and Hadoop knowledge is also required. The big data analyst must also be able to use scripting languages.
A big data analyst must also posses testing skills as he will be required to do A/B testing in order to create reports for senior management. Aside from technical skills, he also must possess personality traits. He must be curious enough to dig into data and search for different patterns in order to discover new insights. He must be both independent and confident to manipulate big data sets to create reports for management. A big data analyst is usually a graduate of business administration, finance, economics, computer sciences, statistics, and mathematics.
A big data analyst must be able to handle stress very well especially when he is required to produce new insights from data sets quickly. He must also be proactive in searching for direction and requirement clarifications. He must be a team player and able to communicate difficult ideas and findings in layman’s terms. He must also possess strong presentation, written and oral communication, and interpersonal skills.
Big Data
is in. There is a huge demand not only for Big Data Scientists but for
Big Data Analysts as well. While a big data scientist needs various
capabilities and skills to analyze and mash up various data sources, a
big data analyst on the other hand performs data analysis on a
particular system only. In short, a big data analyst is some sort of an
assistant to the big data scientist.Because a big data analyst’s job description is almost similar to that of a big data scientist but on a smaller scale, the skills required are also the same as that of a big data scientist. He must be able to support management and business with insightful and clear analyses. He must be knowledgeable about modeling techniques; data mining; as well as explaining, creating, and testing data in order to provide a concise and clear report.
A big data analyst also needs to have a deep understanding and experience about business intelligence and real-time analytics. He has to be adept with various statistical applications, programming languages, and SQL databases. MapReduce and Hadoop knowledge is also required. The big data analyst must also be able to use scripting languages.
A big data analyst must also posses testing skills as he will be required to do A/B testing in order to create reports for senior management. Aside from technical skills, he also must possess personality traits. He must be curious enough to dig into data and search for different patterns in order to discover new insights. He must be both independent and confident to manipulate big data sets to create reports for management. A big data analyst is usually a graduate of business administration, finance, economics, computer sciences, statistics, and mathematics.
A big data analyst must be able to handle stress very well especially when he is required to produce new insights from data sets quickly. He must also be proactive in searching for direction and requirement clarifications. He must be a team player and able to communicate difficult ideas and findings in layman’s terms. He must also possess strong presentation, written and oral communication, and interpersonal skills.
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