Shared responsibilties
Some of the responsibilities mentioned above are shared responsibilities. For example, networking security should be aligned with your infrastructure employee. Meanwhile, the overall security of your data science solution should be aligned with the security officer. Hence, informing all stakeholders about your developed and deployed models is essential. Not only should outcomes be reported, but data lineage, training sets, or flag models should also be reported as sensitive when biased.
At Intercept, we can help you identify those responsibilities, ensuring all responsibilities are covered, or we will do it for you!
Are you interested in knowing more about security? An article on this topic will be released soon. Stay tuned for more content on Demystifying data science!
The toolbox of a Data Scientist
Intercept believes that to start a data science project, it comes in handy to have sufficient knowledge on:
- Programming Language;
- Data Science environment.
Knowing a programming language enables a data scientist to understand written code in multiple languages. It also influences your choice of data science platform. At Intercept, we use Python, a stable language with a solid user base. In addition, it has lots of machine learning functionalities and integrations with data science tools.
Several AI services available within the Microsoft Azure platform can be a building block in your AI practice. At Intercept, we focus primarily on Azure Machine Learning as the platform for your data science projects which serves Python, and for easy drag and drop environment of algorithms such as prediction, it has ML Studio built-in.
However, in the case of pre-built algorithms specific to a function, we can use other services like Azure Cognitive Services and Azure Bot Service
At Intercept, we believe it’s super important for data scientists to comprehensively understand the tools in their toolbox to tackle business challenges using data science as efficiently as possible. Don’t know where to start. We can tailor your toolbox based on your use case while guiding you through each step.
How does Intercept tackle Data Science use cases?
Following the DLM approach, Intercept tackles your Data Science project step by step. Together with our Data Scientist, we can guide you through your business requirements, translating them into a Data Design. This Data Design acts as the blueprint for your Data Science project. Schedule a meeting with us to identify what challenges you’d like to solve with Data Science.