What sounds interesting at GOTO Copenhagen 2015?

The GOTO Copenhagen conference is still a couple of months away, but I have taken a look at the talks, and spotted a few that I think will be interesting.

Generally speaking, I don't go for technology specific talks - by which I mean that I tend to go for talks about processes (e.g. Agile), concepts (e.g. Big Data) or general architecture, rather than talks about specific languages, or even worse aspects of languages, or about specific programs (e.g. a specific NoSQL database). I don't mind examples at a talk being language specific, but I prefer to be able to apply the concepts from the talk broadly.

Having said that, I am as prone to follow hype as everybody else, so if something new and exciting is presented, I might very well go there, even if it breaks my general preferences for talks.

When you see my list, you'll notice that I haven't filled my schedule. This is quite common for me - I rarely know what I want to see at a conference when I begin my day. Instead I like to hear the talks getting presented in the morning, and then decide what to go to.

If you tend to skip those talk presentations, I think you're really missing out. Some of the most exciting talks I've listened to was not remotely on my schedule until I heard them presented at the start of the day.

So... onwards to my list.

The first talk I noticed was Richard Lander's How to train your corporation to prefer open source.
Microsoft has gone through an incredible change in regards to their stance on Open Source in the last few years, to the degree where now they have Open Sourced most of the .NET platform. This is hardly something one would have guessed a few years ago (even though Microsoft has never been as anti-OS as some people think it has), so I definitely want to hear how this happened.

I don't usually go to IOS-related talks, but I might just go to Jorge D. Ortiz Fuentes' Test Driven Development (by controlling dependencies).
There is no description of the talk, but I am always interested in seeing how people handle dependencies, as I think this is an overlooked problem-area in my software development Projects. Given it is in the IOS and Swift track though, there is a high likelihood of me giving the talk a pass.

Other than the mentioned talks, I will probably spend the rest of the first day listening to talks in either the Game Changing Methods and Practices track or the Fast and Continous Delivery track.

On the second, and final, day of the conference, there are four tracks that all sounds interesting - Reactive Architectures, The State of Data, Front-end: The Bleeding Edge, and Security, Safety and Privacy.

In the first track, Reactive Architectures, I am probably going to Jonas Bonér's The Sadness at the End of the Happy Path and Dave Farley's Reactive Systems: 21st Architecture for 21st Century Systems.
Building resilient and high-performance systems is hard to do, and any ideas on how to do it better, are definitely welcome.

If I am not going to Dave Farley's talk, I will certainly be going to Dave Thomas' The State of Data 3.
I have seen Dave Thomas talk a number of times, and his talks are often quite amusing, but also, more importantly, highly informative. Big data is his field, so I expect the talk to be as great as always.

A talk that sounds interesting, is Phil Winder's Modern Fraud Prevention using Deep Learning, which is at the same time slot as  Andreas Halberg's Secure Coding Patterns - another talk that sounds useful for when developing systems.

As always, when at multi-track conferences, there are often several talks I find interesting at the same time, and which I won't choose between until the last minute. Again, much depends on how the talks are presented, and whether I have heard the speaker before. Usually there are a few speakers that are "must-go-to" for me at the GOTO conferences, but this doesn't seem to be the case at this conference. This is not a bad thing - it gives me the opportunity to get to know new great speakers.

Disclaimer: As a blogger who blogs from the conference, I get a free ticket (like I have done for the last couple of years). The deal comes with no strings attached, except for an agreement on me writing a certain number of blogposts about the conference. The conference has no say over the content of the blogpost.

Size doesn't matter

Big data.

A couple of years ago, at a GOTO Aarhus conference, I took a break from the sessions, and walked around in the vendor area. Here I was lucky enough to be able to listen in on a conversation between Dave Thomas and Jim Webber, where Dave Thomas was explaining to Jim Webber why graph databases, like neo4j, were not suited for the type of stuff he was doing. Basically, what Dave Thomas did, was to take all global stock data several times a day, and run some analysis on it (I am obviously simplifying it, and probably explaining it wrong).

This is the sort of things I think of when I hear the words "big data".

Since that's the case, I have been somewhat skeptical when people start talking about big data in Denmark, because we have very few domains where there are anything remotely close to such data amounts (health care probably being the one exception).

It turns out that I've basically misunderstood the concept of big data, and that I underestimated the amount of data out there.

At GOTO Copenhagen, I went to a talk with Eva Andreasson, where she gave an overview of the big data landscape, mostly at the vendor level. During this session, she made a number of important points, which made me realize I have to change my view on big data and its usage in Denmark.

First of all, Eva Andreasson made clear that only about 10% of all data out there is what we traditionally would consider data (e.g. data about companies or people). The rest of it is all the trace data that people leave around when they navigate the internet, doing whatever shopping or browsing they want.

Such trace data, put together with traditional data, allows companies to analyze end-user behavior much better than traditional data alone. E.g. while traditional data will tell you what customers bought, trace data will tell you what products customers spent a long time looking at, without buying them at the end - allowing the company to do some further analysis on what it would take to get the customers to buy the product.

Another thing that Eva Andreasson made clear, is that big data isn't just about working on large data amounts. It is also about aggregating new data sources into existing use scenarios of existing data, and about making new use scenarios of the data that you work with, allowing you to look at things in new ways, hopefully gaining new insights.

Based on these two points, it is clear to me that I have to reevaluate my understanding of when big data is relevant. And judging from the conversations I've had with other people about big data, I am not alone in this.