Skip to main content

10 Things to do after Tableau Conference 2015

So you just had a whirlwind of a week where you were exposed to 10,000+ fellow data nerds. You were inspired by others work, incredulous at the things you saw Tableau could do, excited for all the new feature announcements, giddy over the amazing speakers and feverishly taking notes as to not forget a thing. Your feet probably also ache, you had a great nights sleep in your own bed and you're ready for a Netflix weekend with the SO and/or kiddos. But what about now? What's next? Here's 10 things you can do now to continue the spirit of the conference and continue to grow in your practice:

  1. Connect with your colleges this week at work to reflect and share your conference experiences and to strategize how to harness the momentum, new connections and gained knowledge in your everyday practice.

  2. Now is the perfect time to catch up on the conference Twitter hashtag #data15 among others (like #datapluswomen!). See the conference through others eyes, find out about the moments you missed and discover new folks to follow! Also, did you know that each conference session had hashtag? While you're at it, use the conference app to lookup the sessions you attended or the ones you wanted to attend!

  3. Download Vizable, the free app that turns your data into beautiful, interactive graphs. It was revealed and went live during Day 1 of the conference and it has already been a big hit! Requires iOS 8.0 or later. Compatible with iPad.

  4. Daniel Pink talked about the power of regularly devoting time to be creative outside of your daily responsibilities. He discussed a few examples of companies that do this and call it such names as Genius Hour, Friday Evening Experiments or Ship it Days. Have a conversation with your manager about testing this out on your team or consider incorporating it into your life outside of work even if just for 1 hour per week.

  5. Download Tableau Public and start experimenting publically with data! It's a fantastic way to connect with the community and strengthen your Tableau skills while you're at it. Don't know where to start? Watch the tutorials!

  6. Consider volunteering with the Tableau Foundation. Tableau Service Corps is a volunteer network of Tableau experts eager to help non-profits do more with their data. If you're looking to make a difference by offering your skill set today, this is the perfect opportunity.

  7. If you haven't already, make sure to use the conference app to rate and provide feedback for your session presenters. This will prove invaluable to them and help make for a great #Data2016.

  8. Speaking of #Data16, did you know you can already register and save $500!? Next years conference will be in Austin, TX. Consider writing yourself a memo for things you wish you did/brought/etc. this year. For me, that will include comfortable shoes, bandaids/blister block and business cards!

  9. Check your inbox for an e-mail from Tableau with all the Tableau Conference materials! Take a stab at the hands-on workshop materials, browse attachments from sessions you were unable to attend and drink from the fire hose!

  10. If you tagged attendees in the app, collected business cards or followed conference attendees on Twitter, don't forget to connect with them on LinkedIn. 

What additions would you add to this list!?

Some of my team members (I'm by the 2nd 'A'!)

Comments

  1. This comment has been removed by the author.

    ReplyDelete
  2. The article provided by you is very nice and it is very helpful to know the more information.keep update with your blogs .I found a article related to you..once you can check it
    Tableau online training

    ReplyDelete
  3. Great Article. its is very very helpful for all of us and I never get bored while reading your article because, they are becomes a more and more interesting from the starting lines until the end.

    Tableau online course

    ReplyDelete

Post a Comment

Leave a comment!

Popular posts from this blog

Using Python for Sentiment Analysis in Tableau

This weeks Makeover Monday 's data set was the Top 100 Song's Lyrics. After just returning from Tableau's annual conference and being eager to try their new feature, TabPy , this seemed like the perfect opportunity to test it out. In this blog post, I'm going to offer a step-by-step guide on how I did this. If you haven't used Python before, have no fear - this is definitely achievable for novices - read on!  For some context before I begin, I have limited experience with Python. I recently completed a challenging but great course through edX that I'd highly recommend if you are looking for foundational knowledge -  Introduction to Computer Science and Programming Using Python . The syllabus included advanced Python including Classes and thinking about algorithmic complexity. However, to run the analysis I did, it would be helpful to look up and understand at a high level: basic for loops lists dictionaries importing libraries The libraries I

#MakeoverMonday: Data Science Degrees and Tile Maps

I have recently been experimenting with what I've seen being referred to as a tile map, grid map or periodic map. NPR did a great write up on traditional choropleth maps, cartograms and tile maps. Some awesome Tableau folks have also done great tutorials and published these non-traditional map types publically including Brittany Fong , Matt Chambers and Kris Ericson . There are definitely instances where this type of map enhances the data view or enables better flow and certainly some where it won't be suitable (for example, showing data at the county level among others - example ). I came into this field from a non-traditional background like many others. There's definitely an emergence of new or rebranded data science degree and certificate programs. I was excited when I came across Dan Murray's article on the Interworks Blog  that used data and an awesome tableau visualization to show programs throughout the U.S. Since I came across this at the same time tha

Open Data Sets

A connection of mine recently shared a great resource with me for those of you who are aspiring data scientist or just love data. It's an open-source data science program that can be found here:  http://datasciencemasters.org/ . Check out this great data repository compiled by the project: Open Data List of Public Datasets  - user-curated DBpedia  - utilizing a large multi-domain ontology Public Data Sets on AWS  - common web crawl corpus, NASA satellite imagery, Human Genome, Google Book NGrams, Wikipedia Traffic, Million Song Dataset, Federal Reserve Economic Data, PubChem, more. Governmental Data Compendium of Governmental Open Data Sources Data.gov (USA) Africa Open Data US Census  - Population Estimates and Projections, Nonemployer Statistics and County Business Patterns, Economic Indicators Time Series, more. Non-Governmental Org Data The World Bank  - business regulation measures, company-level data in emerging markets, household consumption pattern