I passionately believe that we all need to take charge of our lives, careers, and businesses. To do this, we need to ensure that we constantly maintain a growth mindset, are open to new opportunities, and build the transferable skills that will help us achieve our goals.
It is not always easy to do this by ourselves and sometimes, we all need a pull or a push!
Over 25 years of coaching, consulting, and mentoring has reinforced the fact that any successful change is a result of personal change. I have worked with a truly diverse set of people and have delivered successful outcomes to clients in the United Kingdom, the European Union, Africa, and North America.
I would love to be working with you to help you achieve the goals and outcomes you have imagined for yourself.
I have been helping clients design, build, and deploy data platforms for many years. Initially on premise, but now in the cloud. This is a really good question. My immediate thought is, yes, there is value in this data. The more difficult one to answer is where and how? The obviously answer is monetisation i.e. what would people or organisations be willing to pay for this data. More importantly, is this my data (vs. customer data) to sell? The data may also represent your intellectual property or be your "secret sauce" so you might not necessarily want to sell it. It is then worth asking questions like "what would the impact on my organisation be if I did not have this data?" or "what would the impact on my organisation be if my competitors had this data?". Hopefully this has given you some ideas. Feel free to book in a call if you have any questions or would like to delve into the detail.
I have been helping clients design, build, and deploy data platforms for many years. Initially on premise, but now in the cloud. I think your choice of technology is less important than your chosen data architecture. I would focus on defining this data architecture first (i.e. to satisfy your requirements) and then looking at how the Azure, AWS, or GCP clouds could best satisfy your requirement. I would consider things like data ingestion, orchestration, modelling, and exploitation. The biggest challenges won't be technology, but thinkings like 1) how do you model the data to answer your questions and 2) how do you relate/join the various data sources. I hope this helps; feel free to pop in a call of you would like to delve into more detail or if you have any questions.