Unlocking the power of data requires various disciplines to work together. In practice, aligning the interests of these disciplines towards a common (data-driven) goal can be challenging, because each discipline has its own idea about the buzzwords in the data domain. As Analytics Translator, I explain how modern data technology can add value to a business, and I ensure that each discipline has a voice in the process. Do you need help in getting value out of you data? Feel free to contact me!
The term ‘Data Science’ has been around since 2012, and at the time ‘Data Scientist’ was the hottest job around. Everybody was looking for that brilliant person with a PhD in a quantitative field, hoping that they could make the magic happen. Now, several years later, the field has matured and most people realize that it takes more than a smart brain to get value out of data. When integrating data-products into primary processes, several expertise are involved in creating a mature product. Examples include domain experts, the IT department, risk management professionals, ethical expert, data management people, and data scientists.
Working with data, analytics, algorithms, and statistics provides a number of unique challenges. For instance:
- Interpreting numbers can be difficult. After having the COVID-19 virus around for a while, we are all intimately acquainted with this.
- When quantifying aspects of your business with data, definitions have to be precise.
- Data quality is essential, because garbage in = garbage out.
- Algorithms can be complicated, and most people in a multidisciplinary team will not be able to understand the inner workings of an algorithm.
- Modern machine learning algorithms are inherently uncertain, so they will make mistakes.
- Spotting business opportunities for a data- or algorithm-driven application requires a basic knowledge of the data-domain, and this is typically not prevalent among the domain experts.
This is where I play an important role as Analytics Translator. My focus is on people and on creating business value, with a data-driven mindset. Additionally, I have an academic background in algorithms, and experience with production-grade data science and software engineering. As such, I speak the language of several different domains and am in a unique position to translate between them. Most of all though, I rely on my endless curiosity and my people skills to find what a ‘good’ product us, and then get it done.