Cloud computing has revolutionized the ICT landscape and is a catalyst for digital transformation. But the adoption of Cloud GIS has been slow and GIS deployments on desktops and enterprise servers remain the norm. Will this change with the advent of big data analytics, IoT and AI?
The GeoBuiz 2018 Report presents a bright outlook for the geospatial industry and predicts a larger role for it in the Fourth Industrial Revolution. Geospatial is more aligned with ICT and Cloud, IoT, Big Data, Artificial Intelligence, and Blockchain are key technology drivers.
The remote sensing industry is growing exponentially with the proliferation of satellites, drones, big data analytics, and AR/VR as key drivers. Increasingly GIS experts and data analysts are expected to have relevant knowledge and skills in image processing and analysis.
Leaving the CEO position at an established company for a startup business felt like a setback. I soon realized that working for a startup has advantages and wrote about them in an earlier article. For a balanced view, I added the disadvantages that I have encountered.
The term GIS is losing some of its appeal to the buzz of geospatial, location intelligence, and spatial data science. Yet the popularity of these offshoots has increased the demand for GIS skills and capabilities, More people are becoming interested in learning GIS and the ArcGIS Lesson Gallery is an excellent school.
In May 2018, I received my Microsoft Professional Program Data Science Certificate. I thoroughly enjoyed going through the different units and now look forward to putting my new-found skills as a data scientist into practice. Allow me to share my experience, especially with those who want to follow my footsteps.
In two earlier articles on Power BI I showed how to connect to Google Analytics and how to create an ArcGIS Map visualization. I have now gone through the course Analyzing and Visualizing Data with Power BI, and will give you access to some of the interactive reports that I have built.
I just completed Essential Statistics for Data Analysis using Excel and I realized that statistics can be very enjoyable. Especially when you develop hands-on skills and are given practical examples with interesting data and insights. It inspired me to write this article on descriptive statistics, which uses some of Kenya’s open datasets. Have fun!
About 70% of Nairobi’s population uses matatus and buses to commute between home and work. Despite this, information on matatu/bus routes and stops remained scarce until the Digital Matatus project collected the field data in 2014. Let’s take a closer look at their GIS data and see whether we can put it to good use.
Kenya conducted its last population and housing census in 2009. Total population was initially estimated at 38.6 million, but this has now been revised to 37.7 million. Since population is a key factor in planning, let us review the census data with the aim of enhancing its dissemination and utilization.
GIS data editing is an arduous task that one rather assigns to junior and novice GIS staff. Such staff will use less efficient workflows and produce more errors. This presented a real dilemma. Now with ArcGIS Pro Tasks complicated workflows can be executed efficiently by a larger number of GIS staff.
Statement or question? Data science is in the news as a discipline that can solve business problems through big data. The fast-growing geospatial industry has been handling large volumes of spatial data for decades. Let’s look at both and find out how they can sustain each other’s growth.