I am part of the business intelligence team where we focus on processing and enriching the data coming from a variety of sources. I always wanted to work on a project where I could deal with lot of data. I believe processing data at scale hones your technical expertise. Target was an obvious choice for me because it provided me this opportunity to work with volumes of data, along with the robustness of Target’s enterprise BI intelligence platform.
At Target, we recognize that our competitive advantage in offering value to our guests hinges on our ability to leverage the full capability of our data assets. We build technical solutions to collect, manage and store data from a wide range of sources. The output is leveraged to drive Target’s important strategic objectives for creating compelling and differentiated experiences for our guests. Traditionally we used to have this data enrichment in Datastage and Teradata.
With the emergence of Big Data, we have been using a lot of tools available in the Big Data ecosystem such as Hive, Oozie, Sqoop or custom MapReduce programs to process data at scale. We have been trying to build a federated enterprise layer with a perfect blend of traditional and open source technologies. To add to that, we are also investing in the development of in-house tools to cater to business specific needs. This approach has provided opportunities for team members to apply fundamental computational techniques in order to solve real world problems. These tools are proving to be a great enabler for business to drive decisions.
There is a huge demand for real-time analytics and operational reporting, for which we rely on technologies like Kafka and Storm. Furthermore, we build data platforms by ingesting raw data from varied operational systems in order to explore different aspects of data. This was traditionally hindered either due to the lack of storage or processing.
Our team is technology agnostic. Real learning comes at the cost of occasional failures, which is well-accepted across the organization. This has resulted in a culture where team members are willing to experiment. There are several solutions that my team has helped build through such experiments. There is no bias shown towards any programming language or technology. Team members are encouraged to pick the right language (be it java, scala, python or R) that suits the need. All team members have access to technical training portals like Pluralsight, Datacamp, Safari online. These are proving to be good technical sources for team members to upskill.
Adoption of agile tools and practices have drastically improved our pace to implement solutions in production. In-house PaaS capabilities further add to our agility. Team members are able to focus more on building solutions rather than creating development environments. We use a gamut of tools to automate our infrastructure and code deployment viz., VM as a service, OpenStack, Chef, Jenkins, Drone, Ansible, Git, etc.
My technical journey at Target has helped me evolve as a professional. I started with working on traditional tools then progressed to solve complex new age business problems with latest technologies. In retrospect, these challenges have always proven to be great learning opportunities. For a person who is passionate about Open Source technologies and excited by the idea of building solutions at scale, Target is the place to be!