Top Takeaways:

1. When it comes to building an audience or brand, listen to what the community is asking for, find opportunities where you can add value, and focus on quality and consistency

2. Building a data-driven culture requires buy-in at every level of the organization, clear short-term goals and objectives, and a focus on both data literacy and governance

3. When companies hire for data analytics talent, soft skills (like communication and strategic thinking) and technical proficiency are equally valuable

4. AI shouldn’t be perceived as a threat to Data Analyst jobs, but rather a skill set that modern analysts can master to become more efficient and effective in their roles

Key Insights:

How do you think AI and tools like ChatGPT will impact the field of Data Analytics in the next few years? Should Analysts be worried about job security?

My take is that tools, like AI tools and Chat GPT, will have a significant impact on the field of data and analytics in the next few years. These technologies will automate many of the tasks that are currently performed by data analysts. This could lead to job losses for some, but it could also create new opportunities for others.

What would you consider some of the biggest keys to success when it comes to building a data-driven culture? Any common mistakes or pitfalls to avoid?

The first, and the most important key to success in a data-driven organization is the support that comes from the leadership team. Leaders need to create a culture that makes it known that they are willing to make decisions based on the data and the data story that they are considering. I also think data literacy is another important ingredient to success. Employees need to be able to understand and use data in a way where data literacy is a universal language within an organization. It is important for all employees within the organization to receive this training.