What It Takes To Be An Excellent Data Processor?
Did you know that more data was produced in 2018 than in the previous 5,000 years of human history?
This clearly shows that data is both extremely simple, but incredibly complex. After all, it is just a piece of information, but we are aware of how powerful weapon information can be!
In this article, our Chief Sample Methodologist, Katerina Nikolova, reveals what it takes to be an effective data processor, sharing the challenges the data team faces daily.
Katerina, you started working as a Data Processor before you were promoted to Chief Sample Methodologist one year later. Can you elaborate on your beginnings? What was your first impression when you were introduced to this kind of data?
I started working as a data processor in March 2018. I remember that my first impression was in between excitement and confusion because I encountered something new and unknown to me at that point in time.
My biggest challenge at the beginning was dealing with the vast amount of data, and acquiring the necessary skills and knowledge to tackle big data. Moreover, I focused on training and other sources of learning in order to understand how to properly execute all the tasks that were delegated to me.
How does your regular working day go by?
Everyday is a story for itself. I start the day by reviewing my tasks, checking out which are the priority ones before I start implementing them. However, due to the dynamic pace of the job, there are so many cases when the priorities suddenly change. So, the data team needs to be prepared for every situation or obstacle that might emerge during the working day.
What are the necessary skills a Data Processor should have to be successful in this role?
When it comes to technical background skills required, I would emphasize: the analytical background in a quantitative field (e.g. statistics, economics, engineering or computer science), knowledge of MS office (especially MS Excel), and relevant experience with SQL (Structured Query Language), comfort with queries and interpreting complex queries, Python, R and Selenium.
In addition to the technical skills listed above, identifying process improvements, conducting ad hoc data analysis, and implementing data streams are crucial for respecting the given delivery dates.
Last, but not least, a data processor should be able to identify and correct problems in imperfect data, to understand where the issue is, and how it can be fixed.
Finally, I believe that the most important data processor skills are being a proactive worker, and a team player.
With so much data available in a click of a mouse, how do you decide where to get the data from?
When it comes to data collecting, we have our internal database from where we get our data. In case of specific task requirement when external parties need to get involved, we have the practice to rely on publicly available sources.
Why is data quality important nowadays?
Nowadays, a large amount of data is available at a single click. As a data provider, it is important to consciously differentiate quality from quantity.
Our company value proposition is that we offer centralized database with regularly updated data. Thus, on the long term, paying attention to data quality is crucial. Our clients depend on this factor for their research.
What is the main challenge when it comes to data processing?
That will be to find reliable data, and deal with the frequent changes and inconsistency of that data.
How do you handle data regulations?
We are one of the first companies that implemented the GDPR regulative. We can proudly say that all the samples and data we offer are GDPR compliant. In addition to that, the way we store our data is in accordance with the ISO 20252. It goes without saying that we always have in mind these regulations when gathering and processing the data.