#Power BI platform

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Power BI Solution | Power BI Services

Power BI Solution is a highly effective tool that helps businesses make data-driven decisions. With its advanced analytics capabilities, this solution can transform raw data into actionable insights. Our Power BI Consulting services are designed to help businesses leverage the full potential of this solution and get the most out of their data. Our team of experts has years of experience in implementing and customizing Power BI solutions to suit the specific needs of businesses across various industries. With our help, businesses can unlock the full potential of Power BI and gain a competitive edge in today's data-driven world.

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Dynamics 365 ERP consulting offers businesses guidance and support in implementing, customizing, and optimizing Microsoft Dynamics 365 enterprise resource planning (ERP) software. With a focus on improving operational efficiency, financial management, and supply chain visibility, Dynamics 365 ERP consulting helps organizations streamline their business processes and make data-driven decisions. Services may include software selection, installation, training, ongoing support, and software integrations with other business systems.

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Business intelligence sits at the heart of success for data-heavy companies. SAT's Power BI developers provide tailored Power BI solutions that assist organizations in discovering insights buried within their data and improving data exploration capabilities.

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Feeling limited by data scattered across different systems?

Microsoft Dataverse, the data engine within Power Platform, can revolutionize your data management.

Delve into transformative role of Dataverse:

- Break Down Data Silos: Unify information from various sources, creating a single source of truth for your business. - Boost Data Governance: Implement robust security and compliance measures to ensure data integrity and trust. - Empower Your Teams: Enable non-technical users to build custom applications using secure, governed data. - Supercharge Your Workflows: Seamlessly integrate Dataverse with Power BI and Power Automate for powerful data visualizations and automated processes.

Unify your data, unlock new insights, and empower your entire organization.

Learn more about the power of Microsoft Dataverse in this insightful blog post here: https://power-fy.com/the-role-of-microsoft-dataverse-in-power-platform-unifying-business-data-for-better-insights/

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How Generative AI is Improving Business Forecast Accuracy

Reference : How Generative AI is Improving Business Forecast Accuracy - Medium

The age of digital transformation is upon us, and organizations are actively searching for inventive methods of outperforming rivals. One of the most revolutionary achievements in this regard is the inclusion of Generative AI into BI systems. Generative AI — a sub-category of AI that can create new data samples that are similar to a given set of data — is the revolutionary in forecasting and planning that BI uses. This article shows how generative AI is going to change the way we use business intelligence for forecasting and planning, its advantages, applications and ethical challenges.

The development of Business Intelligence

However, to start with the place of AI in BI forecasting and planning, it is important to comprehend the development of BI and its role in modern operation. Being a term that encompasses different tools, applications and methodologies, Business Intelligence enable an organization to gathering, analyzing and interpreting data to make the right decisions. Traditional BI platforms were mainly based on descriptive and diagnostic analytics with the focus on past performance and identifying prevailing trends.

Hence, with companies appreciating more and more the crucial role of predictive and prescriptive analytics for future success and competitive advantage, there is a heightened requirement for progressively complicated and competent BI tools. It is at this point where generative AI is brought into the equation, characterized by high-level capabilities capable of reshaping BI forecasting and planning strategies.

Through Generative AI in BI Forecasting and Planning, its capabilities can be utilized.

Enhanced Predictive Analytics

Generative AI uniquely increases the efficiency of predictive analytics through the use of complex data sets with advanced machine learning algorithms that factor out the accuracy of predictive models. It is true that unlike the traditional predictive analytics which mostly rely on predetermined algorithms and patterns, the power of AI is in its ability to create new data points and imaginary characters. This opens new opportunities for businesses to know the changing trends of the market better than their competitors and therefore become more efficient.

Generative AI is capable of identifying hidden patterns and subtle relationships contained in big and complex data sets which traditional BI tools fail to catch. Through the crunching of different variables and factors, generative AI can determine business’ insights into the market trends, customer behavior and possible threats and opportunities so that they can make decisions with aim of making the business to be successful.

Scenario Simulation

One of the further developments of AI generative technology is the scenario simulation which facilitates the forecasting and planning strategizing. Generative AI is capable of simulating multiple business scenarios due to its capability to generate synthetic datasets which are based on historical data. This way businesses are able to check and compare alternative strategies and their expected consequences allowing them to make wise decisions in the course of their planning process.

Realistic and accurate simulation by generative AI help to identify eccentric risks and probable openings, estimate the direction of different factors and see that business strategy is sturdy and responsive. This leads to increased agility and durability of enterprises, which allows them to follow quickly the rapidly flowing changes of market conditions and to grab new business opportunities.

Personalized Insights

The AI technologies also generates the personalized responses by analyzing the user’s behavior and inclination. Such an approach helps to uncover the most appropriate marketing and sales directions, which leads to great chances to increase among clients and their loyalty.

Revealing customer data, e.g. shopping history, browsing behavior and interaction with marketing campaigns, through sophisticated data analysis generative AI can find shortcomings and trends and craft personalized offers and recommendations for customers. It helps in planning and implementing marketing and sales strategies, thus it creates consumer engagement and sales growth.

Automating Routine Tasks

Generative AI might even be able to run the whole of the forecasting and planning activities, including data collection, processing and report writing. It gives BI professional additional spare time to focus more on strategic and analytical applications rather than spending it on simple data arrangement.

Generative AI in automation can help companies reduce routinary and time-consuming jobs and help them to grow in operations’ efficiency, cut down on operational costs and make their decision-making quicker. By doing this BI team productivity and performance will show up eventually allowing the team members to deliver more value to the organization.

Real-time Analytics

Generative AI does real-time analytics to keep tabs on the market updates and, consequently, helps a company to act in a timely manner, whenever there is a need for any market adjustments. However, this ability may be critically vital for industrial sectors that have very volatile markets such as retail, finance, and health care.

Thanks to real-time data analysis, generative AI brings business with a unique opportunity to spot and address emergent trends early, find new prospects, and stay informed about their key performance indicators in order to maximize performance and avoid losses on the spot. Technological advancement gives businesses a real edge of fast-decision making and flexibility, and it helps them to take the most of their opportunities.

Improved Data Quality

Generative AI has a great potential of boosting dat quality through detection and correction of such errors as clashing, inconsistency and outliers in data sets. As a result of this, forecasting will have a stronger fundament and would be more reliable and accurate, which minimizes the risk of making hasty decisions that are based on incomplete information.

Through enhancing data quality, generative AI gives to the businesses the opportunity to acquire better decisions thanks more to evidence and veracity, better shape the predictive models’ reliability and accuracy, as well as to enhance the efficiency of the forecasting and planning processes. This improves the accuracy and trustworthiness of the information promoted by BI which helps the businesses make informed decisions with vigour.

Ethical Considerations

Even if generative AI in BI can bring about positive outcomes in forecasting and planning, one should also think about AI ethic issues which might arise and hinder the implementation of this technology. Enterprises should pay special attention that AI models are trained and applied with data collected and used in accordance with the data ethical norms, privacy and compliance regulations established by the lawmakers.

Data Privacy and Security

The AI of the future relies on getting access to relevant and numerous data sets to create meaningful and valued outputs. Companies must have data privacy and security policies to be aware of threats of data misuse, unauthorized access and breaches. Those policies must ensure that only authorized personnel could access sensitive and confidential information of others.

Transparency and Accountability

Therefore, generative AI, which has complex machine learning algorithms to achieve their goals and yield outcomes that are sometimes difficult to decode is one of the advanced technologies of AI. The realm of ethics should include but not be limited to the notion of how the AI “black boxes” function, how decision making comes about, or how any possible biases are identified and dealt with.

Fairness and Bias

AI that is able to creatively could unwittingly therefore keep and amplify the current unfavorable and unfair indications, which is present in the training data for the model. Organizations should eliminate bias and identify mechanisms that can modulate the bias and promote equality. Thus, A.I. must generate unbiased and equitable information.

Conclusion

In the meantime, generative AI is making BI more efficient with imperative analytics, allowing to simulate with different scenarios, wherever applicable providing specific insights on an individual level, automating the routine tasks, availability of real-time analytics, increment in the quality of the data as well as securing the competitive advantage. However, businesses should indeed manage not only the operative questions, but also the ethical aspects confirming due performance when working with data in order to take the best from generative AI in BI.

The prominence of generative AI in today’s business sphere is unimaginable. Businesses always modernize and adapt to changing business environments. This calls for businesses to implement outputs of generative AI in their BI systems into lately. Through the inclusive implementation of the transforming impact of AI with the ethics keeping quiet, companies can become successful because of the cut-throat competition and the fast moving of businesses, in the business world.

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Steve Salvin, Founder & CEO of Aiimi – Interview Series

New Post has been published on https://thedigitalinsider.com/steve-salvin-founder-ceo-of-aiimi-interview-series/

Steve Salvin, Founder & CEO of Aiimi – Interview Series

Steve Salvin is the founder and CEO of Aiimi, an AI platform which has been quietly scaling since 2013. Having bootstrapped the company since launch, Steve has grown Aiimi to 8-figure revenues and their tech is used by the likes of the FCA, PwC, and the UK government.

Steve has been working in tech since the 80s (even studying AI at university) and is a serial entrepreneur. He’s a huge believer in building AI and technology that empowers users and gives them more control.

Aiimi’s tech allows companies to find and make sense of their data – bringing together what can be a sprawling mass of data, documents, and digital information – helping teams access information instantly.

You initially studied AI over 30 years ago, what were you studying and what initially attracted you to the field?

I studied Computation during my Bachelor of Science at the University of Manchester in 1987. It was a natural choice; following a fascination for computers that started when I was just a child. I remember the day I got one of my own at the age of 12 – I spent hours teaching myself to code in my room. Since my school didn’t teach computing, I went on to convince my teachers to effectively rearrange the timetable, so that I could fit in lessons at a nearby college that did. This paved the way for me to study Computation at university, where I even studied a module in AI all those years ago. My career has been in this field ever since. Ultimately, it’s my passion for computers that first led me here and which has kept me here.

Could you share the journey behind your first startup that deployed next-generation document management and workflow technology, and what your key takeaways from this experience were?

I founded my first startup in 1996, having been inspired by a project I was working on in my previous role at PwC. The project opened my eyes to the challenges waiting to be solved through enterprise content management, and more innovative workflow technology. And so I set up APS. We built next-generation content management tools and worked with the likes of HBOS and Bupa. We grew quickly and were a 20-strong team within just two years. I learned a lot in these early days as a first-time founder, but the key takeaway was don’t be afraid to make decisions – if it turns out to be a bad decision you can make another one. You have to keep moving in a fast-moving startup environment.

Could you share the genesis story behind Aiimi? 

After I sold APS, I worked for OpenText for a few years. But I found that I missed being in the driver’s seat and working closely with customers. Plus, my time in the industry up to this point had opened my eyes to a problem that wasn’t going away: the huge disconnect between transactional structured data and unstructured content within organisations.

It struck me how many businesses lacked insight into what data was being created, shared, and used across their teams, and how. The more data businesses accumulated and stored in different systems, the worse issues became. And, unable to find the information they needed to do their jobs, staff were being slowed down, doubling up on work, and making misguided decisions. This was the problem I set out to solve when I founded Aiimi in March 2007. Our mission is to help businesses find and make sense of their data, giving them the information they need to unlock efficiencies, spot opportunities, and de-risk their operations. Put simply, we connect people to insight.

Your technology is used by significant clients like the FCA, PwC, and the UK government. What makes Aiimi’s AI platform stand out to such high-profile clients?

We’re extremely proud that our customers choose to work with us as a homegrown British AI business. Our approach is what helps to set us apart. We’re not just a software vendor; we’re an experienced team of data, digital, and AI experts who thrive on understanding the precise details of the challenges our customers face. It’s our firm belief that technologies like AI should be used in an ethical way that gives users more, not less, control over their data. We also strongly believe there is no “one size fits all” approach to data management.

We invest a huge amount of time into getting to know our customers so that we can deploy the right technology solutions and tailor our services in line with the needs of individual organisations. And since we understand that these needs change over time, we continue to work closely alongside our customers to evolve our offering throughout our relationship with them.

Besides our industry-leading consulting services, the other thing that sets us apart is the cutting-edge technology that we’re able to offer our customers. Our continued investment in Aiimi’s IP, the Aiimi Insight Engine, alongside generative AI and emerging technologies, ensures that we’re able to serve the most novel use cases around, and solve even the thorniest of business challenges.

You’re a proponent of building AI that empowers users and gives them more control. Can you elaborate on how Aiimi’s tech achieves this and the impact it has on your clients’ operations?

At Aiimi, we believe that AI should give users more, not less, control over their data. AI should be a driver of data quality and brand-new insights that genuinely help businesses make their most important decisions with confidence. That’s why we build AI tools that help organisations see their entire data picture, automate data governance, and enable them to get to the answers they need. Since well-governed data is behind any secure and successful AI application, our tools also put the power in organisations’ hands to adopt models more widely in a safe and controlled way – when we can get an organisation’s trickiest, most complex unstructured data into the right format and of a quality that can be used by AI models, that’s where they can unlock real business value.

Our platform also gives authorised users full visibility into our AI-powered answers. We use fully explainable approaches to AI , so that users with permission to do so can use the platform’s interactive dashboards to look “under the hood” and see exactly what data models are working with, what insights they’ve gleaned, and how they arrived at them. This gives our customers a comprehensive understanding and audit trail for how their data has been used to inform decision making; a hugely important step in making AI-powered answers usable and safe for enterprises.

With the Aiimi Insight Engine, you aim to solve the problem of underutilized data within enterprises. Could you explain how the engine works and the kind of insights it has unearthed for businesses?

A typical enterprise uses hundreds of different systems to store data. The problem is that these systems quickly become outdated and often don’t speak the same language. As a result, the information within them is lost or forgotten about, and is impossible to find when employees need it. Recent Gartner research shows that 47% of digital workers struggle to find the information needed to effectively perform their jobs. The Aiimi Insight Engine addresses this disconnect by creating a data mesh layer on top of an organisation that connects these disparate sources.

The Aiimi Insight Engine discovers, enriches, and joins-up information so that it can be instantly accessed by those who need it – plus,brand-new insights are unlocked by combining previously disconnected datasets, like structured telemetry data and unstructured customer call transcripts. This helps teams realise efficiencies, and glean the insights needed to solve business challenges and spot opportunities. At the same time, the tool pinpoints and secures sensitive information, helping organisations de-risk their operations. Naturally, the data insights and possible use cases vary hugely from one organisation to the next. This is why we work closely alongside our customers, to help each one get the best out of the Aiimi Insight Engine.

Our recent work with a Government department offers a good example. Their team of analysts needed to access accurate information summaries from data from multiple sources, to supply timely and precise briefings to the government and public. They typically used open-source data, like trusted news outlets and websites. But with this volume of data ever-increasing, finding, retrieving, and collating all this information had become increasingly difficult. They required an AI-powered solution to streamline this process and enable them to create these briefings more efficiently and effectively. They chose the Aiimi Insight Engine for its ability to intelligently process large datasets – in this case, those news sources and websites – to find relevant information, before transforming this data into a consumable set of insights using secure Generative AI and Extractive AI models. With the help of our technology, they were able to increase their efficiency and enable more effective decision-making.

The risks of ‘shadow’ AI can be substantial for businesses. Could you define what shadow AI is and discuss the risks associated with it?

‘Shadow AI’ refers to when employees bolt AI tools (like ChatGPT) onto their work systems for the sake of ease and efficiency, without their employer knowing or consenting to the technology. Employees may have good intentions. But shadow AI can pose serious data security risks.

Firstly, employees may be feeding AI models sensitive information without realising – and there’s no guarantee this data won’t find its way into the public domain. Generative AI tools that haven’t been vetted by IT leaders may also be unreliable and produce inaccurate results, particularly if used for inappropriate use cases. Inaccurate results that appear to be incredibly convincing to users, known as ‘hallucinations’, often go undetected. And the consequences of poor decisions that follow have the potential to be hugely costly for companies.

To avoid shadow AI, it’s important to educate teams on what safe and ethical AI practice looks like, and provide clear guidance on which AI tools can and can’t be used securely at work. I would advise avoiding public large language models altogether when it comes to your corporate data. Instead, invest in safe, reliable and robust AI tools that enable workers to do their jobs effectively and efficiently. This way, staff won’t need to resort to unauthorised, potentially insecure tools in the first place.

Implementing enterprise AI safely and securely is critical. What steps does Aiimi take to ensure the security and integrity of its AI solutions?

Security is baked into the Aiimi Insight Engine and all of our technology. Our built-in AI & Data Governance toolkit gives our customers complete control, so they know exactly where their personal or sensitive data lives (and can remediate any issues) and how our AI platform operates in their business. They can also “track and trace” every user interaction with their AI system and auto-verify the sources used for AI-generated answers with full traceability and data lineage. Because we use a range of AI models, each auto-selected by our enterprise AI platform for their reliability, security, and cost to perform a given task, we can tightly control factors like security, speed, and cost based on individual customer requirements. For example, ensuring AI models chosen are used in line with ISO 8000, or that they consider NCSC guidance, GDS, and/or DevSecOps principles.

Looking ahead, what future developments in AI and data management are you most excited about, and how is Aiimi preparing to integrate these advancements into its offerings?

The possibilities for AI-driven data insights are endless – particularly for organisations that get the fundamentals of data governance, data quality, and information retrieval right. At the moment, we are focusing on exploring the best use cases for GenAI in business and developing our product roadmap accordingly. For example, we’re helping customers identify where the most value can be realised from AI- such as by turning unstructured data into structured formats that can then be fed into BI reporting to support downstream decision-making. This is a great first use case for businesses just getting started with AI. It provides tangible benefits and has a fast, clear ROI. We’re also supporting our existing customers to take their next steps with AI and ensuring they get  the most out of the ever-evolving tech.

We are planning to expand our headcount over the coming year, too. We look forward to welcoming new members to our diverse and inclusive Aiimi community. This strengthened team will enable us to continue to grow, innovate, and enhance our offering in line with our customers’ evolving needs.

Thank you for the great interview, readers who wish to learn more should visit Aiimi.

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Unleash the potential of Microsoft Power Platform with us. We offer customized solutions, seamless integration, and dedicated support for your business needs.

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[PowerBi][PowerAutomate] Enviar notificación de una DAX Query

Las alertas en Power Bi son una herramienta que nos permite hacer envío de un correo o notificación de celular en caso de que un número realice una condición. Son muy útiles, pero se quedan cortas.

Si quisieramos conocer más que un número que llega con una regla, sino fijamente estar informado de uno o más números y porque no una pequeña tabla de valores, solo podríamos hacerlo con una suscripción. Muchas opciones que no llegan a algo tan simple como prender la PC y ver por Teams como van X valores bajo diversas condiciones.

En este artículo veremos como configurar envio de correo o mensaje de Teams del resultado de una consulta DAX en Power Automate.

Para poder consultar un modelo semántico de datos de Power Bi Service necesitamos tener acceso al dataset. Podemos realizarlo de diversas maneras puesto que en realidad es un request que nos probee la Power Bi Rest API.

https://learn.microsoft.com/en-us/rest/api/power-bi/datasets/execute-queries-in-group

Si bien nosotros vamos a realizarlo por Power Automate, tranquilamente podría ser una Azure Function u otro servicio que nos permita realizar tiros a la API.

Lo primero que vamos a hacer es probar que nuestra consulta devuelva el dato esperado. Para ello podemos utilizar DAX Studio que nos permite ejecutar consulta contra modelos semánticos tabulares. Si tenemos nuestro dataset en capacidad dedicada, podríamos conectarlo directamente. Si estamos usando PRO, podemos abrir PowerBi Desktop de nuestro modelo original (pbix) y conectarlo a DAX Studio.

En mi caso estoy buscando que todas las mañanas se me informe como van las ventas de este año actual. Entonces veo a ejecutar una medida que traiga una sola fila y una sola columna según un filtro en el formato deseado. La consulta DAX se vería algo así:

EVALUATE SUMMARIZE( FILTER('Orders', RELATED('Tablecalendar'[Year])= YEAR(NOW())) , "Venta", FORMAT( SUM(Orders[Sales]), "#,0.00") )

Voy a sumar las ventas de mi tabla de hecho y filtrarlas por la columna de la tabla calendario relacionada contra el año de la fecha actual, especificando el formato de separador de miles y dos decimales.

Conociendo mi valor, puedo abrir Power Automate y crear un flujo que sea calendarizado/recurrente.

Vamos a buscar la acción "Run a query against a dataset". Este cumple la misma función del enlace de API antes mencionado. Para interpretar su resultado de tabla vamos a realizar una acción que crea un csv a partir de una tabla. Así tendremos una tabla y su salida para delimitar que queremos enviar en notificación.

El paso de consulta a PowerBi nos permite ver las áreas de trabajo, sus datasets y un espacio para pegar la consulta. Para la creación de la tabla solo pedirle la primera fila porque espero un único valor

NOTA: En caso de querer construir una tabla más compleja, puede asesorarse en la doc o el foro de Power Automate.

Finalmente, podemos enviar por correo o en un mensaje de Teams a un grupo o canal de manera que informemos a quienes pertine sobre las ventas. Solo debemos agregar al cuerpo el "Output" que sería la salida dinámica de Create CSV table.

De este modo podemos alertarnos o notificarnos cualquier resultado de un modelo de datos a partir de una consulta DAX.

NOTA: todos los componentes usados en power automate NO son premium. Podemos construirlos con la versión free de office 365.

Espero que esto les sea de utilidad para informarse por el medio deseado los números deseados sin depender del correo o de la notificación de la app.

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Discover the Power of Data-driven Insights with Expert Power BI Consulting Services. Our BI solutions and services in India cater to businesses of all sizes, helping them harness the true potential of their data. As one of the top BI companies in India, we provide comprehensive BI solutions that leverage advanced tools and technologies to drive informed decision-making and empower your organization to stay ahead of the competition.

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How To Make Effective Power BI Dashboards?

The key to making the best Power BI dashboard revolves around the thought of what would the intended user need. All the other practices are support activities for this thought. And one last tip- Stop Thinking and start practicing. Is Microsoft Power BI the solution you are looking for? If the answer is yes, then you are looking at the perfect Power BI implementation partner. Just go through our various use cases. 

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"Part-1: Introduction to Integrating External Applications with Dynamics 365 for Operations: Step-by-Step Guide"

Welcome to our latest tutorial, where we'll guide you through the process of creating a new service method in Dynamics 365 for Operations and exposing it for external application usage. In this comprehensive tutorial, we'll demonstrate how to seamlessly integrate external applications with your Dynamics 365 environment, ensuring smooth data exchange and enhanced functionality.

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Discover how our team's deep expertise in Microsoft Azure can help you build, deploy, and manage modern web apps, AI solutions, data services, and more

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Was ist die Power Platform?

Die Power Platform ist eine leistungsstarke Lösung für Unternehmen, die datengesteuert agieren möchten. Die Integration von Power Apps, Power Automate, Power BI und Power Virtual Agents bietet vielfältige Möglichkeiten, um Geschäftsprozesse zu optimieren und den Erfolg zu steigern.

Die Firma Network4you (Systemhaus München) GmbH hat sich seit vielen Jahren im Bereich Informationstechnologie und Microsoft-Beratungsdiensten als Microsoft Gold Partner ausgezeichnet und hilft Ihnen dabei, von allen Vorteilen und technologischen Lösungen dieses renommierten Unternehmens zu profitieren, um die Leistung Ihres Unternehmens zu verbessern.

Einleitung

Die Power Platform ist eine Suite von Anwendungen, die es Unternehmen ermöglicht, datengesteuert zu agieren. Durch die Integration von Power Apps, Power Automate, Power BI und Power Virtual Agents bietet diese Plattform vielfältige Möglichkeiten, um den vollen Nutzen aus Daten zu ziehen.

Was ist die Power Platform?

Die Power Platform ist eine von Microsoft entwickelte Lösung, die verschiedene Tools umfasst, um die Datenverarbeitung und -analyse in Unternehmen zu erleichtern. Die Kernkomponenten sind Power Apps, Power Automate, Power BI und Power Virtual Agents.

Vorteile der Power Platform für Unternehmen

Die Power Platform bringt zahlreiche Vorteile mit sich, darunter die Steigerung der Effizienz durch Automatisierung von Arbeitsabläufen und die Möglichkeit, Daten in Echtzeit zu visualisieren und zu analysieren.

Power Apps: Maßgeschneiderte Anwendungen erstellen

Power Apps ermöglichen es Unternehmen, maßgeschneiderte Anwendungen ohne umfassende Programmierkenntnisse zu erstellen. Beispiele für den Einsatz reichen von einfachen Formularen bis zu komplexen Anwendungen für verschiedene Branchen.

Power Automate: Automatisierung von Arbeitsabläufen

Durch Power Automate können Unternehmen Arbeitsabläufe automatisieren, um Zeit zu sparen und Fehler zu minimieren. Die Integration mit anderen Geschäftsanwendungen erleichtert die nahtlose Kommunikation zwischen verschiedenen Systemen.