Category: Learning

Rolf Tesmer has weighed in with his thoughts on the “Data Platform”:

What this has meant is that innovation – in particular in the Azure Public Cloud, ISV’s, new data services/products, and new data related infrastructure – has accelerated dramatically and changed the very definitions of what was previously accepted as comprising the “Data Platform”.

Nowadays when I talk to customers about the “Data Platform” it encompasses a range of services across a mix of IaaS, PaaS and SaaS.  The decision of which data service to deploy now comes down to matching the business case technical requirements with the capability of a purpose built cloud service – as opposed to (in the past) trying to fit an obvious NoSQL use case into a traditional RDBMS platform.

I now see the “New Data Platform” as much broader than ever before and includes many other “non-traditional” data services…

Cf. Eugene Meidinger (who started this) and me (who exacerbated this).  This is an area ripe for consideration.

Kellan Danielson and the rest of the Power Pivot Pro team discuss the pace of change in the data platform:

@djharshany I’ve found Pocket (https://getpocket.com/) really useful for saving items for later. I’m on a schedule as well – I save a lot of articles and then pour through them when I’m on an airplane or waiting in line somewhere. #productivityhack

I think this furious pace of technological development has made me much more aware 1) of the amount of noise out in the world that I’m safe ignoring and 2) of how we need to stay vigilant in producing content that cuts through the noise.

Given that these are people who specialize in the fastest-moving part of the Microsoft data platform, it’s worth getting their thoughts on the rapid pace of change.

Aaron Bertrand has provided an index to his bad habits series:

Here is an ongoing list of articles that I consider to be along these lines – either promoting best practices or eradicating bad habits; not all are explicitly framed as a “bad habit,” but they do all represent in some way things I wish I observed less often. Some of my opinions are controversial, and many have evoked very passionate comment threads – so I recommend scrolling down for those, too.

It’s a pretty long list.

Adrian Sampson explains some common mistakes in statistical analysis, particularly in computer science papers:

It’s tempting to think, when $p\ge \alpha$, that you’ve found the opposite thing from the $p<\alpha$case: that you get to conclude that there is no statistically significant difference between the two averages. Don’t do that!

Simple statistical tests like the $t$-test only tell you when averages are different; they can’t tell you when they’re the same. When they fail to find a difference, there are two possible explanations: either there is no difference or you haven’t collected enough data yet. So when a test fails, it could be your fault: if you had run a slightly larger experiment with a slightly larger $N$, the test might have successfully found the difference. It’s always wrong to conclude that the difference does not exist.

It’s an interesting read.  H/T Emmanuelle Rieuf.

Julia Evans looks at what DevOps means in practice:

I enjoyed reading this article about devops at Etsy. One of the really key things about this article is – there is no devops organization at Etsy. It’s about how developers and operations people work productively together! Also, it was a slow incremental migration towards different practices. They did not wake up one day and become devops. I think this is the first talk that used the term ‘devops’?

It’s also not about “everyone is a software developer” – one of the authors of this book, Katherine Daniels, is a senior operations engineer at Etsy at Etsy. I don’t know any of the details of her job, but my impression is that she has a lot of expertise in operations. It’s not like “make operations so easy that nobody has to an expert at it”. Of course you need people who know a ton about operations! Probably those people write software as part of their job?

One of the scariest realizations that I’m slowly coming to (other than “Information Technology is people!”) is the sheer number of overlapping dependencies in the tech world.  A bit earlier in my career, I felt like I could be “a SQL Server guy” and focus on that while not caring too much about the outside world.  It seems like saying that you want to be “just an X” has become more difficult at the margin, and DevOps is just one example of this:  keeping an edge means going broader about more things while still trying to dig deeper in relevant areas.  That’s a tough balancing act.