Strata 2014 Retrospective
This year I was fortunate enough to be able to attend the Strata conference put on by O’Reilly and Associates. I started this retrospective by doing a SWOT analysis of my experience. I then expand with some logistics info and take away research ideas.
I had high expectations for this conference given its marketing. The last conference of this caliber that I had attended was ÜberConf.
- The chairs in the session rooms were comfortable.
- Healthy snack options were available at breaks.
- Sponsored sessions were identified on the agenda.
- There were lots of vendors at the expo.
- Most if not all vendors had technical people on hand.
- Mobile app had maps and schedule.
- They did provide a daily print out of the session schedule and map.
- The mobile app was more frustrating than useful. It was always wanting to update.
- Being registered in the directory means you’ll start getting spam before the conference even starts.
- Navigating the website to find specific session information was difficult. Easier to find it through Google.
- This is not an inexpensive conference to attend in terms of conference cost, travel and hotel expense.
- Full day workshop
- Late notice on software to pre-install
- Not enough AC outlets
- No tables!
Unless they address the logistics issues of the workshop environment I can not recommend attending one.
- From key notes, sessions and the vendors you get to learn about what tools/processes the future holds.
- Discern what tools/processes people are using now.
- Talk with other attendees about the work they are doing and the approaches they are taking to it.
- Some insights I had are:
Threats (or why wouldn’t I want to attend)
- Fundamentals are potentially better learned with targeted training.
- Attending this conference could prevent you from attending another more relevant conference.
- The target audience for this conference is narrow. People that identify with big data, data science and business intelligence are well served by this conference.
When attending it helps to have specific questions or problems you are looking to solve. This gives you a good context when choosing sessions and meeting with vendors. (There are lots of vendors!)
The conference wireless was acceptable for as many people that were using it. Internet in the hotel lobby was very good. There is wired internet available in the hotel room for free. I did not have an opportunity to use it. There is also pay to use wireless available in the room.
I came away from the conference with much I want to research and experiment with and people to connect.
Tools and Libraries
- wakari.io web based Python data analysis
- Anaconda Scientific Python development environment
- Getting IPython set up by hand is a pain—Anaconda is a must on Windows machines.
- Pandas Python data analysis library
- Microsoft PowerBI (Office 365)
- The R programming language
- Pentaho, Tableau and other BI tools
- Adjacency Matrix
- pivot and fold operations
- hexagonal binning
- use visualization for data quality checks
- confusion matrix
- predictive modeling fundamentals
- machine learning
- The work of John Tukey (Statistics)
- Abe Gong (@AbeGong) Jawbone Sidekick pattern
- Monica Rogati (@mrogati) Jawbone UP
- Emil Eifrem (@emileifrem) Neo4j
- Wes McKinney (@wesmckinn) Pandas creator
- Joe Hellerstein (@joe_hellerstein)
- Jeffrey Heer (@jeffrey_heer)
Joe and Jeffrey presented: Data Transformation: Skills of the Agile Data Wrangler
Can we make big data management easier? Her 3 research threads are: effective, easier and cost effective.
I came away with a better appreciation of what constitutes data science, the skills needed, the tools utilized and the vendors in the different areas. If I attend again in the future I would likely skip the workshop day. I would do additional prep working thinking about specific questions I may have for the technical people that the vendors make available.