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Fast-track network data migration: unlock all the benefits of using the NetStork Inventory System in a matter of days

By 12/01/2024Artykuł
NetStork_data_migration

Network inventory systems give you almost instant access to complete network information and allow you to use it on a large scale and streamline the work of many departments in your company.

However, purchasing and implementing a network inventory system is only the first step. It is only with good quality, up-to-date data that its full potential can be realized.

This is why it is crucial to, first, efficiently upload the data to the system, and second, make sure the data is up to date.
So how to efficiently transfer data into the network inventory system to start working with it as soon as possible?

Network inventory system implementation stages and costs

The implementation of a network inventory system consists of four major stages: license purchase, installation, user training, and data migration.

The total cost of implementing the system depends largely on how long each of these stages takes. While the first two (license purchase and installation) are a matter of a few days, and the costs are directly related to the price of the license itself, the next two (training and data migration) require more time and work.

The duration of migration directly impacts implementation costs. Beyond the expenses tied to data entry, there are additional losses linked to restricted access to network information, underutilization of system capabilities, and delays in network-related tasks. Minimizing migration time becomes imperative to mitigate these costs and optimize overall operational efficiency.

Uploading network data to the NetStork network inventory system

The network model in NetStork can be created manually (including network distribution and services), but data can be also migrated automatically – with the help of data loaders.

What data formats can be uploaded to NetStork?

Using the built-in tools, to NetStork, you can make imports from CSV formats for all objects in the program.

From DWG/DXF formats, you can perform data import for point objects on the map (service holes, poles, cabinets, buildings) and linear objects (route sections along with the piping profile, as well as pole sections). SHP, JPEG and GEOTIFF files can be loaded as map primers.

Can network data be uploaded from QGIS?

Data from QGIS can be uploaded as long as it can be saved in CSV format.

When loading multiple CSV files, does the order in which the files are added matter? E.g., loading the service pole before the route? Will NetStork arrange the files in the required order?

If you load file by file, the order should follow NetStork’s network modeling logic. This means that we load the service holes first, for example, and then the route sections. When we upload a complete set of network data, by uploading several files at once their order can be arranged in the loader.

Is it possible to import cable connections using the fiber number to fiber number pattern from the CSV file?

Yes, the CSV loader allows you to load fiber connections in couplers or on ODFs. However, before that, the couplers or ODFs on which you want to model the connections must exist in the system. There is also another option – loading the entire network at once – connections included.

Is it possible to create an import template? For example, we have 10 CSV packages with buildings (which cannot be merged in the excel file, because they will be uploaded at different times) where the attributes are named the same. Can a template be created so that the attributes don’t have to be mapped every time?

You can prepare an upload template and use it repeatedly. You can load data in arbitrary packages. You can also update data that has already been loaded, using the CSV loader.

Can you create arbitrary target tables for import?

The column names of the table to be imported can be any. You just need to map them with the corresponding columns in the tables on the program side.

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Importing address points to NetStork

Can adding range attributes be done through the input file? We can have different parameters in one geographic area.

Each address point or building can be connected to several different ranges. It is easier to do this directly in the NetStork application than in a CSV file.

Where can I find the address points in a range?

Address points can be downloaded for an area from the PRG (State Register of Boundaries) and then imported into NetStork.

How to report by address points such as those that were installed under the EU POPC project and connected outside of the project – is there a field that would allow to distinguish between address points?

Address points can be downloaded for an area from the PRG (State Register of Borders) and then imported into NetStork. Address points are objects in NetStork and they have their own attributes. Address points can be converted in NetStork into buildings or other objects that have addresses.

Importing data to netstork

Exporting data from NetStork

How to download an entire database from NetStork?

You can save the database to an XML file using the “Create backup” function. Or you can export the data directly to CSV files.

Do export files from Netstork have the same structure as import files? How can such a file be exported to get a good file pattern for import?

Exporting uses the same mechanism as importing, so the same file structure can be used.

Adding elements in NetStork

Adding elements in the NetStork system

Is there a limit to the number of elements per layer?

In the case of NetStork, the division into layers is a bit of an artificial division. Nevertheless, any number of elements can be loaded into the program.

Is it possible to attach a document, such as a PDF, to an object, e.g. a building?

Any documents/files can be added to any object. The program does not have any limits in this regard. You can also attach a web document link to an object.

You can read more about uploading data to the NetStork network inventory system in the article:

Data loaders – efficient data migration to a network inventory system