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Data is the basis of everything. GIS tools are really there to unlock the value in the data. There's a lot of unrealized potential in combining datasets to get a better view of what's going on. For example, for many customers, it starts with geocoding an address. But what else can we know about that address? We can leverage demographics or mobile trace data to have a better understanding about the people who live or work at that address. Data mashups can yield some surprising value.
Make more maps. It may sound funny, but the more you illustrate the value of the proximity relationships between spatially relevant data, the more others will begin to understand the value of geospatial data and technology. You can produce reams and reams of tabular data and use spreadsheets; you can even try to use BI solutions to make wonderful charts and graphs, but there's nothing that can take the place of maps to understand spatial relationships
In my experience, accurate data instills greater confidence in those who do not 'speak GIS'. So check & double check before releasing any maps or reports. The more often people are second guessing the GIS department, the less likely they are to have confidence in us!
My CEO once exclaimed, "Steve, if I asked you what time it is, you would respond with a map!" I replied, "I would have to, because where you are affects what the local time is!"
My point is that we should not be afraid to play with the software, and understand the power and the limitations of what can be done. Offer solutions and explanations for questions that your management has not yet even thought to ask.
Also understand that the data you have is quite probably bad. Whether you got it from the government, a vendor or your own databases -- I'd guarantee there is something wrong somewhere and you need to build ways to ferret out those data problems.
Three advices: Learn some kind of programming or scripting that will help you in your daily job. Take a look at working with Raster. Make sure your data is easily accessible to your organisation for example via a webGIS like SSA.
Raster data is incorporated as part of the results in the GeoEnrichment datasets. We, for example, use raster data to calculate elevation profiles in our flood data. Let’s get more specific on new applications of LI. Also when you talk about geoenrichment and LI, when you says it’s incorporated what’s the end benefit of that?
One of the hardest things is to get people to think spatially, all data within an organisation focus on three areas: "People", "Location" and "Assets", you need to show the value that data, specifically spatial data, plays a critical role in the business data strategy. Understanding what spatial data you have using a central data management hub (LIM), orchestrating the data flows (LIM), showing spatial and non-spatial business data in a user friendly application such as SSA, will help you set a stranger understanding of your data portfolio (Currency, updates, metadata etc..)