Earth Intelligence is centred around the collection and analysis of geospatial data and deriving insights using earth observation technologies. The data collected is regarding Earth's physical, biological, and human systems via high-resolution satellite imagery, aerial sensors, remote sensing etc. It provides geospatial analysis which involves analysing and interpreting data that has a geographical or spatial element, using tools like Geographic Information Systems (GIS), deriving insights that help in informed decision making. It is used by environmental groups and government agencies for environmental monitoring, resource management, disaster management, urban planning and understanding global changes.

Earth Intelligence

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ArcGIS

Google Earth Engine

I look to Ikigai, because a sense of purpose is the true definition of it. But when I talk to my juniors I don’t typically stay within the principles of Ikigai. I define three overlapping circles. In the first circle I ask them to identify what they’re good at. There are a lot of people of all ages who are not able to identify their strengths. The second circle is what you want to do. What you are good at and what you want to do are two different things, but they can overlap in certain cases. A lot of people think that if they’re good at something, they will love doing it. But we often discover that our interests are in some other area. The magic happens when both of them intersect. 

The third circle is very interesting, because it’s what the world wants. I have a daughter who's now working in financial services. When she was picking her major in college, I told her to make sure it was something she wanted to do, something she was good at, and also something that would allow her to flourish in her career. She was good at language arts, analytics, mathematics and statistics, so she picked up finance and accounting because that’s what the world wants.

As another example, one of the reasons I went from telecom to healthcare was that I wanted to contribute to a social cause. In one program where I built the largest private cloud, it was very close to my Ikigai because the program helped that specific health insurance company adhere to the Affordable Care Act (ACA). In terms of enrollment timelines and its societal impact, it helped a lot of uninsured people get health insurance. I could connect with that cause of helping people get their health benefits, which will help them access the medical procedures, facilities and care they need. Whatever program or project you are doing, regardless of the industry, you need to associate it with a cause that is very close to you. If you're working on an artificial intelligence program for a smart hub, then how can you make life simpler for people through that work?

Everyone has their own set of priorities, aspirations and passions in life. Leaders need to understand this and focus on their strength, especially passion, and create targeted space for growth for each individual. For example, not everyone is motivated by monetary or material rewards.

Once you understand the strengths and needs of an individual, you can structure growth opportunities based on this. For example, for young, ambitious employees who are hungry for financial and career growth, the reward of increased salary is a never ending game. It would be strategic to create space for growth that helps them develop their passion. This not only motivates the employee to work hard, but the job becomes more meaningful to them as per the saying “if one’s job is his or her hobby or passion, he or she is the happiest person on earth” -- turning "job" to "jobby".

I look to Ikigai, because a sense of purpose is the true definition of it. But when I talk to my juniors I don’t typically stay within the principles of Ikigai. I define three overlapping circles. In the first circle I ask them to identify what they’re good at. There are a lot of people of all ages who are not able to identify their strengths. The second circle is what you want to do. What you are good at and what you want to do are two different things, but they can overlap in certain cases. A lot of people think that if they’re good at something, they will love doing it. But we often discover that our interests are in some other area. The magic happens when both of them intersect. 

The third circle is very interesting, because it’s what the world wants. I have a daughter who&#39;s now working in financial services. When she was picking her major in college, I told her to make sure it was something she wanted to do, something she was good at, and also something that would allow her to flourish in her career. She was good at language arts, analytics, mathematics and statistics, so she picked up finance and accounting because that’s what the world wants.

As another example, one of the reasons I went from telecom to healthcare was that I wanted to contribute to a social cause. In one program where I built the largest private cloud, it was very close to my Ikigai because the program helped that specific health insurance company adhere to the Affordable Care Act (ACA). In terms of enrollment timelines and its societal impact, it helped a lot of uninsured people get health insurance. I could connect with that cause of helping people get their health benefits, which will help them access the medical procedures, facilities and care they need. Whatever program or project you are doing, regardless of the industry, you need to associate it with a cause that is very close to you. If you&#39;re working on an artificial intelligence program for a smart hub, then how can you make life simpler for people through that work?


How do you help your mentees develop a sense of purpose in their careers?

My research is on how you adapt to unexpected change. The most brutal form of unexpected change is kaleidoscopic change. And that's what we've gone through this last year. The role of the CIO in enterprise software has become the lifeline that's kept our economy alive and not just alive, but thriving. Legacy companies have been forced to make this transition to this digital world that we all live in now. These legacy companies have data that's in silos, in different formats. And then they look at these newer companies and see it's all digital and think, "Well, how on earth are we going to compete? What's going to happen when AI and edge come down? Are we going to have the right stuff there?" When you look at this whole Edge AI kind of area that's coming up, where operations and administration kind of become one, we're going to see a very different environment.

It&#39;s interesting that IT organizations running data warehouses for business reporting purposes have devoted significant effort to improving the quality and integrity of their data feeds. These efforts have generally produced mixed results. I think machine learning modeling activities have focused attention on the poor quality of data in large companies in ways that conventional warehousing teams were never able to achieve.

How are Machine Learning tools impacting organizations running data warehouses?

Best Earth Intelligence Reviews 2024 | Gartner Peer Insights

GEE is a powerfull cloud-based platform for planetary-scale environmental data analysus, providing access to a vast amount of satellite imagery and geospoatial data

Google

Using ArcGIS Earth Intelligence, concepts of geospatial data are presented professionally to the various solving processes. However, the absence of some of the collaboration tools diminishes the likelihood of transforming the application to a fully collaborative application.

Esri

Is a modern AI BI tool that helps extract high-quality information from a large datasets integrating BI and GIS.
Offers timetracking and billing.

HEAVY.AI

BlackSky

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Google Earth Engine

Google Earth Engine

ArcGIS

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