Big data and more specifically large volumes of geospatial data shows no signs of slowing down. Finding ways to quickly navigate such data so that it can create real business value has become a challenge for many companies.

In the past, the use of geospatial (or map-related data) has enabled logistics companies to track trucks in transit; mining and construction companies to target sites for operations; hospitals and clinics to identify areas of high epidemic for contagious diseases; and municipal planners to observe, which streets and intersections carry the heaviest traffic and experience the most traffic jams.

SEE: Data center automation research report 2018: Despite growth in data, automation adoption remains slow (Tech Pro Research)

The need for geospatial data

Now the ante for using geospatial mapping data has been upped. Users want these maps to deliver more content, which puts pressure on non-IT professionals to learn how to augment geospatial data. It also imposes additional training so that they properly use the data integration tools to improve mapping content.

For example, surveyors are accustomed to taking their instruments into the field and charting significant points for a survey of a physical area. They then bring this point data back to the office, where a mapping specialist uses the collected data to compile drawings and maps. Now, new software enables the surveyor to do the surveying and map development work himself–but in order to do it, he has to be trained.

In government agencies, geospatial experts historically performed only map development. Now they are being asked to integrate additional information with the maps–such as how many crimes or how many traffic accidents occurred on the streets throughout a city. These experts know mapping but are unfamiliar with how to append other types of data to the maps to make the content more meaningful. They need to be trained.

It is small wonder that many big data and analytics experts cite company resistance as a major inhibitor of analytics and big data advancement.

SEE: IT training policy (Tech Pro Research)

Training Employees

Below are four ways that companies can lessen the resistance to additional big data training

1. Check the temperature

User acclimation to big data and analytics involves getting comfortable manipulating big data in new ways and generating results from that data–but it’s also about users feeling comfortable with their changing job responsibilites.In the government GIS (geographical information systems) world, Adam Carnow, an account executive for Esri , which provides commercial GIS systems, believes that this change begins with GIS managers.

“Many GIS managers have worked in the GIS area for many years,” said Carnow. “They have a background in geography and mapping. This is a background that doesn’t necessarily include much involvement with either the business at large or with IT, which is now a very important factor in maximally deploying GIS systems.”

So, if your users don’t have the background with the data content you now expect them to incorporate and manage in mapping functions sit down with them and their managers to develop a training plan. It is equally important to assure that trainees have the support that they need as both they and their jobs undergo transition.

2. Develop sound business cases that make sense to everyone

The business cases that extend geospatial big data must be impactive and obvious. For example, it was a grand success for senior management at a medical center to see which areas of the county had the most flu cases so that they could control a flu epidemic. But now they want to know more. Who lives in these areas? Is there a high concentration of elderly or young children? If they can find this information, they could reach out to individuals in these groups and provide them with preventive vaccines.

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3. Establish a base and build on it incrementally

You might start with a map, then add locations of your retail outlets, then append sales data to those individual outlets, and then later add customer demographics. By incrementing your big data story one chapter at a time, you build up content and make content more relevant. Best of all, you don’t overwhelm your staff by asking them to work with too much data at once.

4. Expect vendor help

Avoid vendors that drop geospatial software at the door, take the money, drive off–and leave all of the training to you. Training users is a big job.

“The acquisition of important geospatial skills is what we see most lacking in companies,” said Mike Hogan, sales director at Microdrones, which provides drones for mapping and aerial inspection. “Managing and integrating the data that you collect requires training and experience.”

With the right plane in place, training shouldn’t be a problem.

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