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Articles related to "degree"


Miami broke its all-time heat record for June, but no warnings were issued. Here's why

  • Yes, but every National Weather Service (NWS) office has different criteria for heat advisories and excessive heat warnings that take into account a region's topography, climatology and potential urban heat island effects.
  • In order to receive a heat advisory, Miami must have a heat index value of 108 degrees or higher for at least two hours.
  • In Minneapolis, the criteria for a heat advisory is a heat index value of 95 degrees or a wet bulb globe reading of 86 degrees.
  • Back in 1997, the NWS office in Philadelphia partnered with researcher Dr. Laurence Kalkstein of the University of Miami to come up with new criteria for issuing heat alerts in this region.
  • Since it's so hot for much of the year in the desert, NWS offices in the Southwest do not issue heat advisories, only excessive heat warnings.

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I Followed Data Engineer Resumes To Learn How To Break Into The Field

  • Utilizing expertise across software engineering, devops, and data science, it’s arguably even more interesting.
  • More than 50% of previous roles fell into software engineering (SDE), data science (DS) and business intelligence (BI).
  • So if you’re interested in data engineering, it may make sense to become a software developer or data scientist first.
  • According to Payscale, the average data engineering role ($92k) pays more than software engineering ($86k) and data science ($87k) roles.
  • I suspect this is partly attributable to data engineer roles being on average more senior than SDE and DS roles.
  • What is the highest education level achieved before obtaining a data engineering role?
  • Among 50 resumes, 90% had master degrees, 10% had bachelor degrees, and none had PhDs. The role is arguably less “academic” than data science.
  • This supports my hypothesis that data engineering is not an entry level job, and requires competencies best developed in other roles.

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I Followed Data Engineer Resumes To Learn How To Break Into The Field

  • Utilizing expertise across software engineering, devops, and data science, it’s arguably even more interesting.
  • More than 50% of previous roles fell into software engineering (SDE), data science (DS) and business intelligence (BI).
  • So if you’re interested in data engineering, it may make sense to become a software developer or data scientist first.
  • According to Payscale, the average data engineering role ($92k) pays more than software engineering ($86k) and data science ($87k) roles.
  • I suspect this is partly attributable to data engineer roles being on average more senior than SDE and DS roles.
  • What is the highest education level achieved before obtaining a data engineering role?
  • Among 50 resumes, 90% had master degrees, 10% had bachelor degrees, and none had PhDs. The role is arguably less “academic” than data science.
  • This supports my hypothesis that data engineering is not an entry level job, and requires competencies best developed in other roles.

save | comments | report | share on


I Followed Data Engineer Resumes To Learn How To Break Into The Field

  • Utilizing expertise across software engineering, devops, and data science, it’s arguably even more interesting.
  • More than 50% of previous roles fell into software engineering (SDE), data science (DS) and business intelligence (BI).
  • So if you’re interested in data engineering, it may make sense to become a software developer or data scientist first.
  • According to Payscale, the average data engineering role ($92k) pays more than software engineering ($86k) and data science ($87k) roles.
  • I suspect this is partly attributable to data engineer roles being on average more senior than SDE and DS roles.
  • What is the highest education level achieved before obtaining a data engineering role?
  • Among 50 resumes, 90% had master degrees, 10% had bachelor degrees, and none had PhDs. The role is arguably less “academic” than data science.
  • This supports my hypothesis that data engineering is not an entry level job, and requires competencies best developed in other roles.

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New research finds fitness tracker data could predict your marathon performance

  • We found it’s possible to calculate a critical speed value that we can use to predict a runner’s marathon time with a good degree of accuracy.
  • By analyzing training data from 25,000 athletes, we found we could estimate their critical speed and predict their marathon performance with 92% accuracy.
  • Considering how many things can impact marathon performance (during training and on race-day) and the different levels of fitness across recreational athletes, this is a high degree of accuracy.
  • This means that using raw training data to estimate your critical speed, your smart watch or favorite fitness app may soon be able to predict your finish time to an even higher degree of accuracy, as well as providing real-time feedback and advice about how best to pace your race.

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