Win the cloud with Winnaker!

Win the cloud with Winnaker! I am happy to announce that we, at Target, decided to open source a tool called Winnaker. This tool will allow the user to audit Spinnaker from an end user point of view. But first what is Spinnaker? The first time I heard the word Spinnaker, my reaction was, “wait, what does that even mean in English?” Shortly after, I found myself implementing a demo of Spinnaker as a potential replacement for our internal cloud deployment tool. Spinnaker is a cloud agnostic continuous delivery tool, which means we can push our code to any cloud...

How Target Performance Tunes Machine Learning Applications

At Target we aim to make shopping more fun and relevant for our guests through extensive use of data – and believe me, we have lots of data! Tens of millions of guests and hundreds of thousands of items lead to billions of transactions and interactions. We regularly employ a number of different machine learning techniques on such large datasets for dozens of algorithms. We are constantly looking for ways to improve speed and relevance of our algorithms and one such quest brought us to carefully evaluate matrix multiplications at scale – since that forms the bedrock for most algorithms....

(Data) Science or Witchcraft?

On my first encounter with it, around early 2010’s, I was mystified. It sounded like witchcraft and I imagined the practitioners to be a coven of witches and wizards, all holding Ph.D.s in the dark art of “Data Science” and being respectfully addressed as “Data Scientists”. It was believed they would magically transform haystacks into gold and then ask for your first-born in return as a reward for their service (a la Rumpelstiltskin) There is no denying the fact that the title “Data Scientist” is the most coveted one these days and has a nice ring to it. It’s also...

Bare Metal Big Data Builds

When you first think about scaling an on-premise Hadoop cluster your mind jumps to the process and the teams involved in building the servers, the time needed for configuring them and then the stability required while getting them into the cluster. Here at Target that process used to be measured in months. The story below outlines our journey around scaling our Hadoop cluster, taking the months to hours and adding hundreds of servers in a couple weeks.

Real-time Big Data at Target

An enterprise as large as Target generates a lot of data and on my Big Data platform team we want to make it as easy as possible for our users to get it into Hadoop in real-time. I want to discuss how we are starting to approach this problem, what we’ve done so far, and what is still to come.

The Dojo

At Target we’re always looking for ways to move forward in becoming the best omni-channel retailer that we can be. This journey demands that we enable change in most every part of our technology organization. Our culture, delivery model, technology selections, working arrangements and org structures are all levers we can pull to help us be more responsive. A key question that we continually ask ourselves is “how can we move faster”? Introducing change in a large enterprise can take a long time if we don’t challenge ourselves to be creative around constraints (like not enough “experts” to go around)....