Double the Simplification
Per the Simplify Part I post last week I originally planned on this being just a two-part series on my (and this blog’s) direction as we head through 2017. Personal habits/priorities for Part I and then technical focus for Part II. However, the more I thought about it, I found this scope and the Part I post itself too limiting so I’m revising this to a four-part series. Part II below is more targeted at specific actions and goals for 2017. Part III will lay out the tools I intend to focus on both in projects and in my blogging and research time (why the align with ‘Simplify’, synergies between them, etc). Part IV will be more oriented toward management and administration of BI solutions and environments. Similar to the recent Tabular metadata reporting post, I’m increasingly interested in different techniques and processes to make BI teams and environments more productive and resilient to change.
Simplify in 2017: Part II
In short, if you review or read through Part I, I was being descriptive of current and past habits about removing clutter to focus my attention on learning and delivering value. Some level of background was perhaps necessary but I failed to identify the specific changes or actions to improve. I don’t necessarily regret the closing line “cautiously optimistic if don’t stray…” or think it’s necessarily false but I think it’s a mistake to just expect (hope?) good things will happen because you’re doing the right things. I think naming off some specific, tangible outcomes and actions is necessary and, in my experience at least, I just feel better when I’m pursuing a goal (ie ‘Insight Quest’).
So what are these specific, tangible actions?
- Every single day I should be writing and/or tuning relevant queries and scripts. (ie DAX, SQL, M, R, TMSL, PowerShell, and maybe some Spark SQL and U-SQL too). This is just common sense – people that are great at what they do work on their craft constantly. Additionally, I’ve amassed a very helpful mini-library of sample code and queries for various scenarios that often directly benefit my projects.
- I’m typically a passenger on my daily commute and between both trips have about two hours of reasonably quiet time. In 2016 I all too often used that time to listen to music or browse the web. In 2017, for at least one of these trips (to work or coming home) I should be focused on specific technical skill or idea.
- The Boston Business Intelligence group, which hasn’t held event for several months, should be active again with monthly meetings. I’ve already started down this road and I’m hopeful our next event will be on 3/22 at the Microsoft office in Burlington, MA. My thought is the group’s speakers and content should cover the ‘here and now’ (SQL 16′) as well as what’s coming with vNext for MSBI professionals but also offer real value for SQL Server DBAs and Power BI users and developers in the broader ecosystem.
- YouTube Channel. I mentioned this back in my November update but haven’t made progress yet, unfortunately. I think about it regularly and Guy in a Cube was probably right in that I should probably not worry too much about quality as I get started. Maybe this will turn out to be fun – if not, I enjoy writing blog posts and papers anyway.
Coming back to a high level I think you only grow if you consistently do things that you’re at least a little afraid of. This can take many forms but the basic idea is just not to get too comfortable with anything – titles, acronyms, money, anything and to put yourself in situations where you’re not 100% sure you can do something. In some ways, the act of taking risk such as with a technology that isn’t quite mature yet or adopted broadly, is what actually provides some level of security over time.
That said, I think the balance with taking risks and pushing yourself into new areas is not to over extend or try to be something you’re not. The data and analytics world is far too large and dynamic to not accept some gaps and soft areas. I believe it’s much better to have a deep knowledge of tools and skills with synergies and dependencies (and roadmaps) – things you can actually deliver at scale and quality – rather than 100-200 level knowledge across the data and analytics marketplace. It’s not a specific goal but there’s a good possibility that someone (or more) that share some of these ideas and values will join me at Frontline Analytics later this year.