Data Analysis Learning Path on SlideRule

SlideRule is a new startup focused on being on online learning hub. One of the sections of the site allows experts to create “learning paths” for a topic. Well, Claudia Gold, data scientist at Airbnb, created a learning path for data science titled Data Analysis Learning Path. The learning path covers: topics, timelines, resources, and links necessary to acquire the skills needed to be a data scientist.

Happy Learning.

Accel Partners: Data Visualization and Data Stories

Accel Partners, one of the largest big data investment firms, hosted a panel discussion on Data Visualization and Data Stories.

Hilary Mason, Data Scientist in Residence at Accel, hosts the discussion. Two great visualization experts that come up in the talk are, Fernanda Viégas and Martin Wattenberg.

Analytics Handbook is Free – 2 Books, tons of great interviews

Three students from the University of California Berkeley have set out a mission to inform young professionals about the importance of data, big data, and data science. The name of the project is Analytics Handbook, and so far there are 2 books available for free. The books consist of very detailed interviews with some of the current thought-leaders in data science.

The download actually includes 2 books:

  • One for Data Analysts/Data Scientists
  • Another for CEOs and Managers

The “Top 5 Takeaways” list at the beginning of each book book is worth the download. Plus, the interviews contains many nuggets of helpful tips.

Thank You For The Half A Million Pageviews

As of yesterday, the Data Science 101 blog has hit 500,000 page views. Thank you to everyone that has read a post, commented, tweeted, liked, disliked, shared a link, or emailed me regarding the blog. I have enjoyed it so far.

Now here is a few numbers about the blog.

  • Colleges with Data Science Degrees has received more than 50,000 pageviews. The page has never gone viral; it just gets a steady stream of views everyday.
  • New Data Science Certificate Program has received just under 17,000 views. Most of those were on 1 day when the post was at the top of Hacker News.
  • Then, there are many posts with between 1000 and 10,000 pageviews.
  • The blog started in February of 2012
  • There were 416 total blog posts
  • 30% of my traffic comes from search engines
  • From a sample size of 1 blog, the formula to hit 500,000 pageviews is:

    2 \hspace{.1cm} years + 416 \hspace{.1cm} posts = 500,000 \hspace{.1cm} views

Stay tuned, there is more good stuff in the coming weeks.

Big Data Jobs Are Booming…And So Are the Salaries

Lots of Big Data Jobs

iCrunchData, one of the most popular data science job sites, keeps an index of the data science job market. Recently, the index just passed 500,000 big data jobs posted online. That is a phenomenal number, and it just goes to show the massive need for more people with big data skills. Also of note, analytics jobs are at nearly 250,000 and even statistics jobs are approaching 70,000 according to the index.

The Jobs Pay Well

DataJobs, another popular data science job site, recently published Big Data Salaries: An Inside Look. DataJobs breaks down the salaries by job title and experience level. Here are some of the details:

  • An entry level data analyst should expect a yearly salary in the range of $50,000 to $75,000. A more experienced data analyst should expect as high as $110,000.
  • The range for a data scientist goes from $85,000 up to $170,000.
  • An analytics manager, depending upon the number of direct reports, can command a salary up to $240,000 for 10 or more directs.
  • A big data engineer can expect a salary of $70,000 to $165,000, depending upon level of experience and the company.

If you have the right skills, right now is an excellent time to find a big data job. If you don’t yet have the skills, it is a good time to start learning because the current trend of open big data jobs is showing no signs of slowing down.

Data scientists need their own GitHub. Here are four of the best options

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Ryan Swanstrom:

This article contains some really great information. I think these startups have huge potential.

Currently, I am a big fan of Sense. I will hopefully be posting more about Sense in the coming days.

Originally posted on VentureBeat:

Imagine if a company’s three highly valued data scientists can happily work together without duplicating each other’s efforts and can easily call up the ingredients and results of each other’s previous work.

That day has come.

As the data scientist arms race continues, data scientists might want to join forces. Crazy idea, right?

Two San Francisco startups — Domino Data Lab and Sense — have emerged recently with software to let data scientists collaborate on multiple projects. In a way, it’s like code storehouse GitHub for the data science world. A Montreal startup named Plot.ly has been talking about the same themes, but it brings a more social twist.

Another startup, Mode Analytics, is building software for data analysts to ask questions of data without duplicating previous efforts. And at least one more mature software vendor, Alpine Data Labs, has been adding features to help many colleagues in…

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