Every organization faces challenges that could be addressed if they were able to harness the full potential of the data within their grasp.&nbsp;In most organizations, there are sources of data that would create actionable insight if they were joined together in a common analytic context. Frank Blau, Data Architect and IT consultant at EBCONT points out that this situation is not abnormal, but that it should be addressed in an effective Data Architecture strategy. 
 
In today&#39;s data-driven world, organizations are inundated with large amounts of data flowing in from multiple&nbsp; sources. This creates a series of distinct problems that are commonly faced:

<ul>
	<li style="list-style-type:disc">Data is stored in different systems (for perhaps good reasons) that do not communicate with each other and cannot be used to uncover insights that their alignment would reveal.</li>
	<li style="list-style-type:disc">Data is arriving in such high velocity that it cannot be consumed effectively by business stakeholders</li>
	<li style="list-style-type:disc">Data arrives in different formats and structures, and more than one approach is needed to understand and consume them.</li>
</ul>

This is where modern data architecture steps in, offering a framework to bring together disparate data into a cohesive structure that can fuel analytics, business intelligence, and the power of (Gen)AI.

Data is not always in the most convenient location to deliver the insight that it may reveal. This may be due to regulatory or even good design principles. Being able to address the needs for holistic insight requires understanding the fundamental requirements driving those location choices and how best to enable the data to contribute to the desired analytic outcomes. Modern data architecture supports several approaches to dealing with these concerns:

Data Federation: the creation of virtual views across multiple sources of data to offer the user a unified perspective.

Data Modeling using Modelstorming:&nbsp;Rather than monolithic waterfall models, application of Agile techniques to data modeling, focused on process outcomes, can produce more adaptable and functional data models. Model storming is a collaborative process where cross-functional teams brainstorm and iterate on data models and analytical approaches. By bringing together diverse perspectives and expertise, organizations can uncover novel insights and innovation.

ETL and ELT processes: Both of these are processes for extracting, transforming and loading data from one system (typically transactional) for use in another system (typically analytic). The difference between them is where and when the transformation is occurring; In ETL it happens before you load the target system and in ELT it happens after.

Data Hubs: A data hub is a centralized repository designed to facilitate the storage, management, integration, and distribution of data from various sources. It serves as a central point in an organization&#39;s data architecture and allows for significant improvements over a data federation approach.&nbsp;

While delivery of a system-level data architecture model is still a core activity in the overall data management process, it has limitations that are exposed as teams begin to work with it&nbsp; in agile processes. When one team is working holistically to realize a product (the data model) over the entire architecture, and the developers are working on discrete stories, features and sprints, there is a mismatch in goals and activities that is not effective or productive. In order to accommodate this (necessary) evolution of the modeling process, we have embraced the iterative techniques of agile development in order to better align with these principles. Iterative processing involves a cyclical approach to data analysis, where insights inform subsequent iterations of data modeling and analysis. This iterative approach enables organizations to adapt to changing business requirements, refine their analytical models, and uncover deeper insights over time.

The process to deliver this goal is called modelstorming. This is a collaborative effort between the data architects, developers and importantly, the users of the data architecture. It is a workshop-based approach that strives to deliver a joint understanding between all relevant parties. These participants should be able to deliver the following inputs:

<ul>
	<li style="list-style-type:disc">Participate&nbsp; in discussions about&nbsp; business processes.</li>
	<li style="list-style-type:disc">Identify key elements of processes to be recorded and measured.</li>
	<li style="list-style-type:disc">Describe data related to the processes being discussed.</li>
	<li style="list-style-type:disc">Collaborate on a consensus for the goals and outcomes of the project</li>
</ul>

While there should still be well-considered system architecture and data management artifacts, the deliverables for the data modeling team will also be more discrete data models, sometimes just at the level of a single inter-application process, such as an API interface or message queue. These component artifacts should also be consistent in form and content with the broader data modelling deliverables. Examples of iterative modeling outputs include:

<ul>
	<li style="list-style-type:disc">Business Event and Modeling diagrams (also known as BEAM) that uncover and document discrete business processes and events.</li>
	<li style="list-style-type:disc">Hierarchy Charts to describe relationships between dimensional attributes</li>
	<li style="list-style-type:disc">An event matrix that describes the relationships between events and dimensions</li>
	<li style="list-style-type:disc">Data mart schemas that describe business-facing perspectives for consumption</li>
</ul>

 
From Silos to Synthesis: Conquering Data Fragmentation the Data Hub Pattern

Fragmented and Siloed Data One of the primary hurdles organizations face is the existence of data that may provide more insight when joined with other data in the broader landscape. Departments often store data in isolated systems, leading to fragmented information and inhibiting cross-functional insights. Silos can hinder collaboration, innovation, and ultimately, the ability to derive meaningful value from data. For example, one system such as a web platform may contain the analytics used to derive customer intent, while another ERP system may contain the transactional activity for your customers. Without synthesizing these disparate data sources, it is difficult to understand the quantitative relationship between intent and purchasing. In another example, there may be incoming data related to patient status that is generated by machines and sensors. Naturally this data is used operationally for the monitoring of patients, but if it is brought into a data architecture where it can be analysed across a broader population (with appropriate regulatory compliance), there may be opportunities to uncover treatment modalities that offer better outcomes for more patients.

Crafting the Data Lifecycle: Modeling, Extracting, and Transforming 
At the heart of modern data architecture lies data modeling. This involves designing a blueprint that defines how data is structured, stored, and accessed within the organization. A well-designed data model provides a common language for stakeholders and ensures consistency and accuracy in data interpretation. ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform) processes play a crucial role in data integration. These fundamental practices involve extracting data from various sources, transforming it into a consistent format, and loading it into a centralized repository or data lake. By automating these workflows, organizations can streamline data ingestion and preparation, enabling faster insights. 
 
Data federation has emerged as one solution to break down these silos. By creating virtual views of data across disparate sources, organizations can access and analyze information seamlessly. This approach fosters agility and flexibility, allowing for real-time insights without the need to physically consolidate data into a single repository, which can be a considerable time and cost savings. It should be noted that many popular tools such as PowerBI and Tableau, allow you to materialize this approach directly within the visualization tool, including transformations, aggregations and joining to multiple sources simultaneously. While this virtual approach can work well when your data is relatively co-located, the weakest link in your data chain will ultimately determine the quality and performance of the system, making this an approach that is often unsuitable for tasks such as building novel applications that should make use of such harmonized data.

Data Hub: The Centralized Nexus for Actionable&nbsp; Insights 
One emergent approach is the development of a data hub, where multiple services and repositories are combined into a single point of innovative interactions. &nbsp;This data hub serves as a centralized nexus for storing, managing, and accessing integrated data. It acts as a single source of actionable truth,&nbsp; providing a unified view of the organization&#39;s data assets, regardless of format or schema. While the data hub is not a replacement for a data warehouse, it may be delivered as a means to collect and conform complex source data that may be arriving in different formats, granularity and velocity.&nbsp; By leveraging a data hub&rsquo;s ability to deliver harmonized data at scale, organizations can simplify data management, improve data quality, and empower users with smart data mastering and self-service analytics capabilities.&nbsp; High-performance data hubs can also be deployed as a component in a hybrid architecture, offering a best-of-breed solution between the federated data, data mesh and data warehouse platforms.&nbsp;

EBCONT has demonstrated considerable success delivering data hub solutions across a broad range of markets, platforms and architectures. We offer the ability to collaborate on a deep dive analysis of how your business requirements can inform an intelligent decision about how this approach can fit into your data management strategy.

Driving Innovation: Iterative Modelstorming

Disconnected data and common data models

While there are often good reasons for an organization to separate data into different tiers of storage and access, many times these tiers and their artifacts become an impediment to a holistic analytic perspective. Understanding these processes and roles and creating a data management strategy is at the heart of an effective data architecture to mitigate this. Being able to understand the ways that data can become disconnected and how to bring it back into a performant conformed perspective would be a key deliverable of your architecture. Starting with collaborative data modeling or modelstorming, and adopting appropriate features like iterative processing, ETL/ELT and data hubs are fundamental building blocks for addressing these challenges.

Frank Blau explains: &ldquo;Bringing together a customer&#39;s disconnected data into a common data model and data access layer is crucial for analytics, business intelligence, and to harness the power of (Gen)AI. Data architecture is the practice of deciding how to build this data model, and with what tools. And that is what we at EBCONT can help.&rdquo;

And Gregor Sieber (Executive Vice President / Head of Consulting and Innovation at EBCONT) delves deeper into best practice :&rdquo;One of our customers in the finance and regulatory space faced the challenge of needing to access data stored in a large number of IT systems whenever they wanted to roll out a new web-based customer product, which created a lot of overhead and duplicated dependencies. As parts of the data were inconsistent, it was also a danger that the validation logic for this data would become inconsistent between the different customer products. By moving to a data hub approach, we were able to centralize the data mastering approach and provide a single, consistent, and scalable API for all new customer products. This has greatly accelerated the creation and roll-out of new products and improved the governance on a data and processing level, which is an essential advantage for organizations in the finance space.&rdquo;

For more information please contact <a href="mailto:gregor.sieber@ebcont.com" style="text-decoration:none">gregor.sieber@ebcont.com</a>.

Summary

Straddling the line between the ambitious visions we see in the media and the reality of delivering actionable data insights can feel like navigating a maze. EBCONT is here to tackle some of the hurdles you might face in today's IT world.
In this series, we're diving deep into the trenches, shedding light on the real-world challenges and presenting practical solutions. Whether it's taming unruly data sets or optimizing your IT infrastructure, EBCONT has a roadmap to guide you.

Unlocking Data Unity: Strategies to Tackle the Disconnect Dilemma

The &quot;Top Salary Satisfaction Austria 2024&quot; ranking presents an impressive selection of companies distinguished by outstanding salary satisfaction among their employees. The top ten reflect the diversity of the Austrian work landscape, with the intriguing observation that service, human resources, internet, and IT industries perform particularly well, placing multiple companies in top positions.

The results extend beyond a simple ranking, providing a detailed insight into various industries that reflect the diversity of the work environment in Germany and Austria. This breakdown allows both employees and companies to analyze and compare salary satisfaction in specific sectors systematically.

For job seekers, the ranking serves as a valuable resource to identify potential employers in their preferred sector who not only offer financial recognition but also provide a supportive work environment.

Psychology in the Workplace: Salary as a Key Factor for Increased Satisfaction and Productivity

For the &quot;Top Salary Satisfaction Ranking 2024,&quot; clear quantitative and qualitative selection criteria were used. Only companies in Germany and Austria with an existing kununu employer profile, at least 20 reviews (of which five were in the last twelve months) in relevant categories, and at least five listed job titles were considered. A total of 6,550 companies in Germany and 1,049 companies in Austria were selected.

Qualitative criteria required a score of at least 3.5 stars in relevant kununu categories, a salary position above average for at least 50 percent of the stated job titles, and a recommendation rate of at least 70 percent.

Johannes Litschauer, Managing Director of EBCONT, is delighted with the confirmation:

&quot;We are extremely proud to be among the top ten companies in Austria in the &#39;Top Salary Satisfaction Ranking 2024&#39; by kununu and the S&uuml;ddeutsche Zeitung. We see this as confirmation of our focus as an employee-oriented company that places particular emphasis on a positive work atmosphere and fairness in the workplace.&quot;

How was salary satisfaction determined?

Looking for attractive employers? The ,,Salary Satisfaction” ranking by the German SZ Institute in collaboration with kununu provides guidance on which companies truly impress their employees. kununu, in partnership with the Süddeutsche Zeitung (SZ), has identified the top companies in Germany and Austria with the "Top Salary Satisfaction 2024" ranking. We are proud to be among Austria's top 10!

Where also salary satisfaction matters! 
EBCONT in the Salary Satisfaction Ranking Top 10!

Artificial intelligence has become widely known in society since the emergence of ChatGPT at the latest and is on everyone&#39;s lips. From an IT consultant&rsquo;s point of view, a rising number of requests are mainly related to chatbot solutions, but we do try to show them the variety of different AI solutions. As a matter of fact, not every use case requires a generative approach. However, you could combine different strategies in order to get the best out of it.&nbsp;

A greater challenge arises, for example, from more complex structures in a service task that are stored in many different documents and requests. For example, I may have terms and conditions, specific instructions, questions about specifications or pricing, special requirements, all of which may be in different languages. In most conventional cases, you first have to spend a few hours screening the documents and summarizing the valuable and relevant findings. Accordingly, scaling is also limited, both in terms of time and content.

The &ldquo;traditional&rdquo; approach of a Machine-Learning-based solution would be the creation of a multi classifier in order to tag the requests accordingly. This already works well in many situations, but depends on a well-prepared and well-trained (and maybe even pre-labeled) training data set. The paradigm of Zero Shot Learning tries to break with that as prior training is not considered as mandatory anymore. However, when it comes to usable solutions for a business client, you will prefer a solution approach that is not too generic, but fitting to your specific needs.&nbsp;&nbsp;

For the implementation of enterprise solutions, LLM alone therefore only offers limited benefits, as previous examples will prove that have not been consistently integrated. Despite of recent studies showing that the bigger LLM could be more than just a stochastic parrot, leading to the situation in which the evidence is mounting that there is a basic understanding in these models (see &ldquo;Random Graph Theory&rdquo;), in terms of enterprise-ready solutions, you cannot rely on the randomness in connecting the dots. Hence, you will need a combination with semantic knowledge and hard facts.&nbsp;&nbsp;

Especially in the field of language processing with NLP and the now popular generative models, the methodology of so-called &quot;Retrieval Augmented Generation&quot; (RAG) promises to enrich the strengths of Large Language Models with fact-based knowledge and therefore deliver accurate results. This means a contextually relevant transfer of information. Despite existing for almost 5 years now, RAG technology (along with graphs) is one of the recent hot topics as it includes relevant sources that could be added to the response to a query. Hence, custom information will be integrated into a LLM without requiring another tedious retraining.

Another concern is to be found in privacy &amp; security, but also transparency. On the one hand, you would like to have a proper and clear evaluation of the quality of your output, but without revealing your company data. It is also necessary to clearly define what happens to your data and how it is processed and stored. This also requires a proper implementation of your RAG technology.

Diverse AI Solutions: Beyond Chatbots

There are a couple of platforms that might help you with solving all of these issues. Among the tools leveraging this technology, Squirro has emerged as a particularly notable application. Let&#39;s explore the multifaceted applications of RAG and take a closer look at how Squirro is making a difference.

Following out-of-the-box capabilities are provided by Squirro:

<ul>
	<li style="list-style-type:disc">Pre-Trained ML Models, ready to use</li>
	<li style="list-style-type:disc">Pre-Built Data Connectors for an easy data integration</li>
	<li style="list-style-type:disc">Pre-Built Chat and Analytics Dashboards</li>
	<li style="list-style-type:disc">An End-to-End Automation Workflow (also visualized)</li>
	<li style="list-style-type:disc">No-Code Configuration &amp; Integration</li>
	<li style="list-style-type:disc">Full Platform Observability</li>
	<li style="list-style-type:disc">Enterprise Security &amp; Access Control</li>
	<li style="list-style-type:disc">SaaS / Managed Service Options</li>
</ul>

From a technology perspective, Squirro is a preferred solution for RAG not only because of its ability to use company and external data at scale, but also because it respects enterprise grade security by using Access Control Lists, Encryption and ISO standards.

Generative AI generally plays its strength for an enhanced self-service as it offers users an accurate full-answer automation and enables AI conversations with website content. Responses are AI-formulated but with high quality, which is important in preventing escalation. Cost reduction is a vital part of the service automation process. All of these topics (and more) are covered by the Squirro platform with its easy-to-handle UI.&nbsp;

Once a project is created (either empty or by choosing from a template), one could select data sources, load and enrich data. The integration process is ensured by different connectors and with a few single clicks you will be able to create a proper connection. Possible data sources could be e.g. from web, social media, a Python SDK, but also data from Jira could be indexed. As Business Intelligence tools are included, too, we could use a bidirectional approach for using aggregated reporting data in a workflow as well.&nbsp;

Introducing Squirro - Out-of-the-Box Features for Enterprises

The AI studio offers training and publishing of machine learning models in terms of tagging, classification, entity extraction or trend detections.

Another mentioned advantage of Squirro is the convenient structure of creating automated pipelines, which minimizes &ldquo;forgetting&rdquo; important data preprocessing steps.

&nbsp;

As the output is created, results will also show relevant sources of how the response was processed. This overcomes LLM hallucination by providing the evidence. This built-in feature comes in very handy and is quickly adjustable.

One final feature I&rsquo;d really like to point out is the concept of communities used in Squirro. We could specify the interests of the users, whether they shall relate to clients, products, countries or a custom entity. Hence, the content will be personalized and optimized for each user.

So what are possible applications for this solution and who is to be targeted? The audience is broader than you think. For once, you could enhance your search engines not only based on keyword matching, but also on the context and nuance of the user&rsquo;s query. Content creation and summarization is a key element of these models. Let&rsquo;s also not forget Market Intelligence for businesses as vast amounts of data is available to provide insights and forecasts, making sense of discovering market trends and customer feedback.

But also Customer Support, Service Automation (think about support ticket systems and service desks!) are glad if an AI-based tool would help them classify their incoming work accordingly, as this lowers their effort of directing the question to the correspondent topic and person responsible. A detailed support by retrieving and synthesizing information is therefore possible on the fly, significantly improving user experience. As for SquirroGPT for Service Management, employees will have the ability to instantly find relevant information from a knowledge base using natural language.

Bigger companies with different departments would profit from an automated classification which reduces the resolution time (benchmarks of Squirro state over 95% accuracy in ticket attribution and reduction of resolution time by more than 30%).&nbsp; 
&nbsp;

<h3>Free Webinar Invitation: Explore Squirro for Service Insights 
 
To sum up, we are looking forward with confidence to the new challenges we could face with the help of tools like Squirro. In case of interest, I&rsquo;d be happy to also invite you to our webinar where I will show you the benefits of using Squirro for Service Insights. I&rsquo;d also like to recommend checking out the trial version to get a better overview.&nbsp; 
 
Event: Boost Your Service Management to New Heights with Generative AI 
19.03.2024, 09:00 CET - ONLINE 
Register now:&nbsp;<a href="https://www.eventbrite.at/e/free-webinar-boost-your-service-management-to-new-heights-with-genai-tickets-845617824677?aff=EBCONT">Click here</a> 
&nbsp;</h3>

<h3>Links:</h3>

<h3> 
<a href="https://www.ebcont.com/en/services/ai-big-data-and-search">AI, Big Data and Search</a></h3>

<h3><a href="https://squirro.com/service-insights">Automated Service Management With Generative AI</a></h3>

SquirroGPT: Next-Generation Service Management

In a world shaped by ChatGPT and artificial intelligence, businesses encounter complex challenges in handling service tasks. This article not only illustrates how companies can address these challenges but also introduces an innovative solution with RAG and SquirroGPT. Explore how Squirro not only masters complex structures in documents but also ensures data privacy and transparency.

How to automate your Service Management with RAG and SquirroGPT

With extensive BSI C5 Type II certification as well as comprehensive certifications according to ISO 27001, ISO 9001, ISAE 3402 Type II, IDW PH 9.860.1, and PCI DSS, plusserver meets the highest requirements for data and operational security. The recently sealed partnership with EBCONT enables companies to access a reliable European and secure cloud infrastructure and securely migrate and operate existing applications.

A standout feature of the provider is its dedicated 24/7 support available in both German and English. This additional support ensures that customers receive the best possible service at all times. 
The cooperation between plusserver and EBCONT is a significant step in offering top-notch and data-sovereign cloud solutions to German and European businesses that meet the highest security standards.

Korbinian Kreitner, Manager at plusserver, is enthusiastic about the new partnership with EBCONT: &quot;We are excited to expand our partner ecosystem with an established IT service company like EBCONT. The combination of our cloud platforms and EBCONT&#39;s application expertise is an exciting package for the digitalization of all businesses. &#39;Elastic on pluscloud&#39; is also a great kickstart to our collaboration and creates anticipation for the next joint projects.&quot;

Christopher Anderlik, Executive Vice President at EBCONT, adds: &quot;plusserver and EBCONT are united by the individual customer&#39;s desire for reliable, certified, and scalable enterprise cloud solutions on an independent, European, and data-sovereign cloud. This makes us perfect partners and, combined, the ideal solution for customers with special requirements.&quot;

We are pleased to announce that plusserver, one of the leading German cloud providers, is now a partner of EBCONT. plusserver operates four of its own data centers in Germany and stands for European sovereignty and data independence.


German cloud provider plusserver new partner of EBCONT


Communication Design

Styleguide

Prototyping

User Experience

Usability Design

Job Detail

Diversity, LGBTIQ, Diversity Charta, Diversität, Gleichberechtigung, Akzeptanz

Diversity Charta

Space to evolve and develop, diverse projects, flexible working hours and a state-of-the-art tech pack are only some of the EBCONT benefits that we agree on with each and every individual.

Benefits

AI and Data Science Services

Search and Semantics

Big Data

Durch unsere strategischen Partnerschaften bieten wir ein ausgewähltes Portfolio von KI Produkten an.

AI Products

Advisory Services

Agile Coaching

Business Analyse

Data Science

An orderly and planned path to digitisation is a great opportunity, also for your company. New markets can be tapped, new business models can be developed. At EBCONT, we accompany you on this journey in every phase and deliver a broad-based project management according to best practice in all phases of the project. We also support you in data analysis, counting on our in-house experts: Data Scientists and Data Engineers using modern techniques on a daily basis.

Digitisation

Lifecycle Management

Analysis, Consulting

Analytics & AI

Digital Content Apps & E-Learning Apps

Future-ready CMS and authoring

Success Stories

Tailored and Combined Software

Publishing & Media

The best IT project is only half as valuable without test planning, execution and analysis. At EBCONT, we provide an efficient test team of highly trained staff who help reduce costs and save time. We automate at all test levels, using established tools as well as tools from the open source community. Our testers recognize any emerging bottlenecks and do not stop at the user test, since not only the functionality test is crucial for our applications but also the validation of the usability and the orientation towards the desired target group.

Last, Performance, Security

Softwaretest

Test Automation

Testmanagement

Quality Assurance

Usability Testing

Cloud Computing

EBCONT accompanies you as a specialist in software development during your project, but even after that, in the course of system administration, we will provide you with tools and platforms for the maintenance of any required IT infrastructure and applications based on these. All this in close cooperation with a wide range of data processing centres and cloud providers. Valuable computing resources should be used sensibly through classic virtualization and the use of containers.

Dev Ops

Managed Services

Networking & Security

Office IT Management

Infrastructure, Operations

Database

For more than a decade, we have been the specialists when it comes to giving modern software a clear, safe and secure, and maintainable structure. Depending on the topic, we draw from a large pool of suitable technologies and frameworks. We assist you in the selection of the right database systems and are also experienced big data and data analytics pioneers where data management and analysis are concerned. By using proven technological platforms, we can also ensure the appropriate governance in the implementation of such projects. When you think of a new app, we offer a solution tailored for your requirements.

Enterprise Applications

Mobile Apps

Development

We aim to enhance the quality of your product. We focus on the essential matters and try to be consequent in every detail. Aesthetics, attractiveness and creating positive user experiences is very important to us in every project – no matter if its a “Business CRUD-application” or a mobile app. Our design developments are honest, unobtrusive and long-lived. Technologically we're up to date and looking for innovative solutions in order to make your content visually appealing and technically executed in the best way possible at the same time.

UX/UI, Design

EBCONT stellt ein Team von Expert:innen für Sie bereit, um KI und Big Data in Ihr Unternehmen zu bringen. Wir bauen auf langjährige Erfahrung über Branchen hinweg und bieten neben Services ein ausgewähltes Portfolio von Technologien an. Egal ob Datenanalyse, Erstellung von Machine Learning Modellen oder die Integration Ihrer Daten in einer Big Data Plattform um darauf neue Anwendungen aufzubauen - mit EBCONT haben Sie den richtigen Partner.

AI, Big Data and Search

Diese Veranstaltung bietet öffentlichen IT-Entscheidern eine Plattform zum Austausch über die Anwendung von Elastic im öffentlichen Sektor und den neuesten Entwicklungen in der Technologie. Experten und Community-Mitglieder werden informative Vorträge halten, in denen Kollegen ihre Herausforderungen und Lösungsansätze teilen.

Behördentag 2023

EBCONT is represented as an exhibitor at the Shift Conference for the first time

Shift Conference

Our publishing solutions at the 75th Frankfurt Book Fair

Frankfurt Book Fair

Scrum Master Logbook

Colleagues report

Job offers

Sustainability begins with the employees, goes through careful doing to e-mobility and IT.

Sustainability

Many nationalities, a clear focus on women, LGBTIQ+ activities and freedom for development make us what we are as a team.

Diversity

Privacy policy

"Customer Experiences in the Spotlight" is the new motto at EBCONT. For many years, companies like Schrack Seconet or KSV1870 have been working in partnership with our teams. The secret to success lies in sustainability and tailor-made solutions.

German cloud provider plusserver new partner of EBCONT

Ilse Merkinger-Boira

More articles

Gregor Sieber

Ilse Merkinger-Boira

Frederick Bednar