The Data-Driven Pyramid

August 23, 2022

For many, a visual aid assists in creating a mindset of where you are going. We believe strongly in visual aids being essential to a transformation journey regardless of the industry. This is why we have created a data-driven pyramid. 

Literacy

We describe literacy as what is required for people to be able to participate in a conversation about data. In order for that to happen, there needs to be education across the organization to help individuals have a common language. Think of it as similar to individuals needing to be educated about financial information and how to read financial documents from the organization, in order to have an intelligent and progressive conversation. It is the same with data. Teams need to have a base-level understanding in order to participate in those conversations. This is something that is a requirement inside any organization that wants to make more data-led decisions.

Fluency

We describe fluency as the ability to understand and process data insights. Not everyone in your organization needs to have this capability, but it is helpful if this skill is inside the organization. This specialty goes beyond literacy and requires the team members to assemble, source, and process different information sources together that will lead to business insights. 

Data Translator

When you get to the data translator stage, these individuals can facilitate communication between data science teams with technical proficiency and business consumers of various data science project results. This is needed because data scientists and sometimes analysts don’t have the business understanding and need people that can translate between the business needs and the data requirements. If this role doesn’t exist in the organization (can be external or internal), it can often cause misalignment and can lead to data that doesn’t solve real business problems or give any insights. 

(Citizen) Data Analyst

Data Analysts are individuals who analyze data, but it is likely not their primary role. They fit into the category of “do-it-yourself data analytics”. They are learning about how to improve data across their organization but aren’t technically data scientists, with formal training. They are looking for insights to help them better lead the business. They may spend their time building dashboards and creating visualization tools – this could be in their department or more company-wide. Additionally, this role can be hired outside the organization. 

(Citizen) Data Scientists

Data Scientists are well trained. They use predictive modeling and other techniques to create intelligent models about the business. A lot of data scientists are programmatically strong and use these skills to take data and turn it into forward-thinking models. They use machine learning or AI to process an organization's data. This role can be either inside or outside the organization. As you may gather, this role needs a translator into the business insights and needs so that it produces models that are helpful to move the business forward. 

We hope this article is helpful in describing the different types of roles and needs that a business has as it enters its journey into a data-driven culture. For more information on educating your teams in data literacy OR assistance in augmenting your team schedule a no-obligation call with our team HERE. 

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