The world produces 2,500,000,000, 000,000,000+
bytes of data every day, that’s equal to 10 million Blu-Ray disks stacked the height of 4 Eiffel Towers. Source: http://www.vcloudnews.com/every-day-big-data- statistics-2-5-quintillion-bytes-of-data-created-daily/
A Data Scientist solves problems
with large amounts of data. Example: Analyze tweets to figure out whether or not a tweet sent to a company is positive or negative.
A Data Scientist will be
able to take data science projects from end to end. They can help store large amounts of data, create predictive modeling processes and tell stories about the findings Data Scientist
Data Engineers are versatile generalists
who create data pipelines to help process large amounts of data. They typically focus on coding, cleaning up data sets, and implementing requests that come from Data Scientists. Data Engineer
DJ Patil Data Scientist As
the former Chief Data Scientist of the United States Office of Science and Technology Policy, DJ is the perfect prototype of the Data Scientist.
Doug Cutting, Data Engineer The
creator of Hadoop and a member of Apache’s Board of Directors is a model of the data engineer who builds tools to process big data.
Roger Huang, Data Analyst The
humble author of this piece, while nowhere near as talented as the two individuals referenced above, did serve a brief stint as a data analyst for a pharmaceutical company.
Data science is a new and
exciting field filled with lucrative career paths. Curious to learn more? Check out Data Science Career Track!