Farmers work hard to prep soil, plant the crop, tend the crop and harvest. For the row-crop farmer those are the basic chores that lead to success – with a lot of other details thrown in. And it’s those details that separate the high-yielding farmer from the average producer. Today those details are wrapped up in the data you collect, and managing that information will become more critical in the future.
As farmers ramp up their information collection, it will be important that their data integrity is solid too. What does that mean? Data integrity is the quality of the information you collect and store. Quality data is information you can rely on year after year.
During Trimble Dimensions Robert Wold, Trimble engineer, discussed the issue and offered four tips for making sure the data you collect is reliable for future decision-making.
1. Remove manual data plumbing
The days of taking a thumb drive out of a monitor in the tractor or combine should be ending. It’s a process few farmers do well, often leaving that stick in the machine until winter when it may be too late to act on the data. It’s also a manual step, which offers the chance for bringing in errors.
And any other manual way you enter data – say from a notebook – should be considered an issue. Manual steps in your process offer the chance for entering errors into the system. The more automatic data capture and storage you use the better off you’ll be. That does mean looking at cloud-based systems where monitors and other data collection tools simply upload information to a central system.
2. Standardize data dictionaries
That’s jargon of course. A data dictionary is just the listing of names for fields, equipment, crop protection products and other items you use on the farm. But those need to be standardized. When a farm worker enters a field and fires up the monitor to record a task, he or she can’t enter any old field name they come up with. Field names should be consistent across the board. As should equipment codes too.
If one person says Back 40 when entering a field name but your official name is Grimes Back 40 matching up the two files gets difficult, and requires time. Also, data can be lost. “We have seen situations where the field, farm and operation names don’t match from field to back office,” Wold says. “This can create data islands.” Those “islands” are pockets of information that float free and may have valuable information that should be in the master file, but nothing matches up.
3. Establish a single master data set
Your farm should have a master data set of field records. Cloud-based systems make this easier than ever since you can have a single master where information gets sent. If you look at #2 and standardize data entry the master is kept current in real-time as fieldwork is finished.
And with a single master you’re not translating data from one place to another. All records in one place help solve issues with duplication, which can be a challenge. Also with new systems available today, Wold explains it’s possible to provide limited access to trusted partners who can see the parts of the master data set they need to see.
Wold says this process of creating a single master system is getting easier as manufactures develop application program interface systems – or APIs – that make data sharing into a central system possible. There are even outside systems from soil test labs for instance, that can deliver results into your master data set if your system is set up for it.
These common interfaces will make building a robust master data set easier.
4. Remove as much duplication as possible
This can be a challenge. Duplicate records get generated, perhaps in one brand’s system you collect yield information and it’s stored there – for later translation into your master. Essentially removing duplication helps make sure the data you have is as accurate as possible.
Note that none of this is easy at first, but by following these steps it’s possible to boost the data integrity on your farm, and your confidence in the information you have stored. This will help with future decision-making.
(Source – http://farmindustrynews.com/data/4-tips-improved-farm-data-integrity)