An interview with the company’s founder, Roz King.
R. King Data Consulting offers a decade-long, robust background in full-stack data engineering, data analytics, data science and data systems - but who is the person behind the company? Meet Roz King, the owner of R. King Data Consulting.
Hey Roz! Tell us a little about your background and your love for data.
As it previously says, I’ve been nerding out on data for about ten years in the realm data science, analytics and engineering. I spent time working on data-related projects at cutting-edge businesses like Education Analytics and research institutions like UC Davis and The University of Wisconsin, Madison.
Throughout my experience, I noticed that a of researchers and smaller businesses in general (like small startups) have data, but don’t know how to use it, or don’t have the capacity (i.e. funds) to hire those do know how to use it. Because we’re a small business with the data skills of a silicon valley tech company, we can bring a more complete skill set to the table, at competitive rates.
I also noticed in my experience that you can gain a unique perspective in approaching data when you’ve done projects in a lot of different domains. Individual fields are often siloed in their techniques, and you can gain a lot by looking at what people in other domains are doing. That’s another thing we bring to the table--a breadth of experience that fosters a fresh approach to data problems.
What’s the mission of R. King Data Consulting?
We firmly believe data can and should be used for the greater good, and that it should be accessible to all. We approach every problem with a hacker's mentality and a social activist's heart. We build powerful tools and uncover hidden information in vast data stores with an intersectional framework.
While we take clients of all kinds, we’re particularly passionate about social justice, and using data to further social justice causes, open access to information, and showing people how to access and use information—we hope to help people use data most efficiently in a way that makes a change.
Okay, for the person who doesn’t know much about data, what are some things you do?
So much! Our website has some of the more technical services we offer, but on a high level, we can help organizations make better effective use of their data and improve their data workflow. We can take you beyond spreadsheets, and help you incorporate best practices for organizing your data, store it securely, manage it safely, and back it up. All in a way that makes data analysis and data science workflows much more efficient.
Lately I’ve been doing a lot of work with making complex relational databases easier to access for a non-technical end user. For example, I built some custom software for a large research university that can pugs into almost any database and by passing a few small configuration files, a research group can spin up a user interface to the database aimed at anyone from research study coordinators and PIs to analysts and biostatisticians.
There’s a lot more engineering, systems, analytics stuff, but yeah - check out our website to learn more.
What is the difference between Data Science, Data Analysis and Data Systems?
From my point of view, Data Analysis is about understanding. Basically, it answers the question: how can we take data we have, and use it to understand something new about something. What can we learn from the data?
Data Science is about the practical use of data. Rather than using it to learn something new, we want to use that data as a tool itself. For example, how could you automate the process of identifying a sensor that needs to be re-calibrated? Or, how could you cut down on human error by having machines take over certain data cleaning tasks? With data science!
Data Systems is the infrastructure linking everything together - the system is where it all lives, how computers can access that info so people can make sense of it. It’s the platform. We build the link between all the different moving parts of a good data system and help ease communication between all those platforms. For example, we might build and maintain the compute servers that host R and Python computational environments for analysts in your org, and those connect to a relational database that we set up which also connects to a public facing application server where users can log on and access the applications that analysts build. And all of those pieces are set up to communicate with each other seamlessly.
Sweet - anything else?
I’m starting to offer trainings to organizations that want to build up internal technical skills--focusing on R and Python for now, I’ll can teach people in the organization a whole range of skills--from best practices in versioning code or common data munging patterns to techniques in high performance computing or efficient use of large databases. I'm really excited about expanding that part of R. King Data Consulting out right now.
Above all, I love working with clients large and small who want to use their data to effect change—change in their business, and change in the world. If you want to learn more about what we do, or just talk shop in general, please don’t hesitate to reach out.