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Case study

CELINE

CELINE is an umbrella inventory management system that gathers data from Orange affiliates on their network infrastructure and presents it in a unified way. CELINE is used by GNOC (Global Network Operation Center), which is responsible for operating networks in various Orange affiliates. GNOC is using CELINE as a primary source of inventory-related data regarding the network infrastructure it maintains.

Problem definition and goal

CELINE was designed for GNOC (Global network operation center). GNOC is responsible for the maintenance of Orange affiliates network infrastructure. To achieve this goal, access to information about the network’s infrastructure is paramount.

The original approach for GNOC with regards to inventory management was to access whatever tools are available in the country for which they provide services. It was clear early on that working with different systems from huge inventory solutions like NetCracker to Excel spreadsheets was not efficient. Therefore, it was identified that there should be a single inventory solution for GNOC that integrates all data sources available. One could describe the situation as following:

Before CELINE

Before CELINE

After CELINE

After CELINE

Challenges

OBJECTIFY has been part of the CELINE project from the very beginning. Our first contribution to the project was to define the problem faced by the GNOC: accessing information scattered across many different data sources.

Soon it was clear that we would have many significant challenges to face:

Data diversity

The applications storing the network infrastructure data were hugely different from each other in terms of APIs, level of detail, and data models. Our goal was to create a unified view of the data for the user. From the user perspective, the representation of a server or router (as an example) should be the same independent, if the original data came from NMS’s (Network Management Systems), Excel Spreadsheets, or Inventory tool. 

Data synchronizations

It was not possible to replace all the tools used by Orange affiliates because they’re part of the day-to-day work of local engineers and integrated with other specific IT solutions.

Information instead of data

Even if the data from the various data sources will be in the same application, to provide real benefit, these data need to be correlated to each other, they need to be aggregated into user reports and accessible via standardized APIs for further automation and reporting tools.

Data quality assurance

It is common for inventory systems to have data that is out of date. The problem becomes even bigger when 3rd party companies, with no management authority (GNOC), need to initiate data cleaning or update stale data.
There are significant project management issues related to projects with so many participants but, this goes beyond the scope of this case-study.

Solutions

OBJECTIFY was active in the telecommunication inventory management domain long before this project. Through our experience, we gained valuable expertise without which we could never have delivered these solutions:

Data diversity

We have created an inventory data model starting with very generic terminology to more specific types. This model could be extended and can document any inventory situation we might encounter in the data sources, which were not even identified during that time. The result was “Common data model” that we have described and tested in detail.
Celine Map

Data synchronizations

We have created specialized data pumps to collect and transform data to the “Common data model” and send the aggregated view after each synchronization to a centralized inventory in Poland. These data pumps allow custom connections and transformations for each data source. All the downstream calculations, transformations, and algorithms are generic and independent of the data source.

Data quality assurance

We always need to make sure the data presented to the user is correct. We have implemented mechanisms to identify data inconsistencies like reference integrity and data invariants. We have also allowed users to override data coming from a source system while making sure that such corrections are consistently visible across the whole application (the original value from the data source and the corrected value by GNOC).  
CELINE Data Quality Assurance
CELINE

Information instead of data

Having the data does not mean that the user receives all the information they require. To solve this issue, we have put a lot of emphasis on search capabilities across all inventory objects and attributes. Part of the CELINE solution is integration with our own DMS tool that provides storage for unstructured data (work instructions, manuals, common problems, and solutions) and integrates this information into CELINE.

We have also designed and implemented many custom reports which are tailor-made for the daily information requirements of GNOC engineers. These reports allow an aggregated view of data from various sources.

CELINE facts

Project Age
5 years
Number of Countries
4
Number of data sources
14
Inventory objects
Close to 1 mil
Users
359
Domain
Telecommunication
Technologies
Java, Spring stack, PostgreSQL, Lucine index, Vue, Vuetify
Core competences
Data integration, Data modeling, High data volume processing, Microservices, Distributed applications

Orange Slovakia has chosen the CELINE platform as the core for its next inventory-related project, “Service impact analyzes” which you can check here.

See also

Case study

Dodes

Case study

SIA

Case study

DMS

Case study

Koderia