Let’s Talk About Data

Let’s talk about data ❗

🤖 With all the talk about Hyperautoatmion, AI, and generative AI, we need to talk about data.

💡The very core of these technologies is data!

💡Garbage in, garbage out is very relevant here.

🤖As you begin exploring these technologies, you must ensure you only throw technology into the mix after first looking at your data.

💸 These technologies are often used without due diligence, leading to failing projects and loss of time and money.

💸When you are not showing true ROI, executive leadership begins to question the use of the technologies because they are spending money on something that does not offer business value.

👉 Before you throw anything into the mix, ask yourself the following questions about your data:

✅ How is the quality of your data for AI?

✅ Do you have enough data to support the technology?

✅ Is your data siloed?

👉By asking yourself these questions, you can start to think about ways to fix the issues with your data:

✅If the quality of data needs to be better, think about ways to enhance the quality of your data.

✅How much data do you need to be successful? How much time will it take to gather the appropriate amount of data?

✅Is thedata is siloed, what do you need to adjust? Are there other systems you need to collect data from? Can they be connected?

💡Working through these questions and developing ways to overcome these situations will put you and your organization in a better place when implementing these different technologies.

🤔 Taking the time upfront to slow down to fix data issues will go a long way to ensure that the technologies you implement will succeed and provide the ROI in the long run.

👉You want to connect people, processes, and technology. 

👉If you want to learn more about CI or this topic can help you, let’s schedule a time to talk.