Andreas Koblischke
data culture evangelist
datenkultur Evangelist
Hamburg, Germany
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I have been creating analyses and dashboards for business users with Microsoft analytics products since the last millennium already. 2006 I came across Dynamics BC (Formerly known as Navision) and became well known for my strong capabilities of creating analytics solutions for end customers as well as for Microsoft partners. In the following years I extended my knowledge to Dynamics development, data warehousing, data analytics and Power BI. Since the launch of Microsoft Fabric in April 2023, my team and I have been working every day to define the optimal path for analytics and AI solutions with Microsoft Fabric. Microsoft provides every week new functionality, and I love to learn how to use it and where it could be a good fit in our offerings. I regularly publish articles on my beloved topics and am often invited as a speaker.
Bereits seit dem letzten Jahrtausend erstelle ich Analysen und Dashboards für Business User mit Microsoft Analytics Produkten. 2006 stieß ich auf Dynamics BC (ehemals Navision) und machte mir mit der Erstellung von Analyselösungen sowohl für Endkunden als auch für Microsoft-Partner einen Namen. In den folgenden Jahren erweiterte ich mein Wissen um Dynamics Entwicklung, Data Warehousing, Data Analytics und Power BI. Seit dem Start von Microsoft Fabric im April 2023 arbeiten mein Team und ich jeden Tag daran, den optimalen Pfad für Analytics und AI-Lösungen mit Microsoft Fabric zu definieren. Microsoft stellt jede Woche neue Funktionen zur Verfügung, und ich liebe es zu lernen, wie man sie einsetzt und wo sie gut in unser Angebot passen könnten. Ich veröffentliche regelmäßig Artikel über meine Lieblingsthemen und werde oft als Redner eingeladen.
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How to generate a forecast using Microsoft Fabric Data Science
Fabric is the Microsoft one-stop-shop for data analytics. It allows prepare your data for analytics purposes. It also provides the capability of building enterprise level artificial intelligence solutions.
In this session, I will show how this is achivable using Microsoft Fabric. You see how we take data from Dynamics BC SaaS, clean the data in a Jupyter notebook using Python, train a model, deliver the predicted data to the Fabric internal data lake called OneLake and visualize the forecast in Power BI.
My goal is to make you understand the necessary steps to start with your first AI model using Microsoft Fabric.
What is Microsoft Fabric and what is it capable of?
Microsoft Fabric puts all of Microsoft's data offerings in a bag and puts a price tag on it. If you ask various data experts: It is a lot of stuff in there. It is a bit of overwhelming. What is Data Factory? Why is there data warehousing as well data lakehousing? What is the difference? What is a data flow? What is a data pipeline? What is a Jupyter notebook? And when to use what? What is the meaning of data lake centered? What about AI functionalities? What is real-time analytics capable of and what on earth is data activator meant to do for us?
I agree: It is a lot! We sometimes find a couple of ways to archive the same goal but let me assure you it comes with a reason: Think big, start small. Let me explain you, how to grow into Microsoft Fabric.
How to analyse Dynamics BC with Microsoft Fabric
Fabric is the Microsoft one-stop-shop for data analytics. How to use it for advanced analytics with Dynamics BC SaaS? How to transfer data to the Fabric data lake? How to transform the data for perfect analytics? How to build a data model and visualize your data? What about professional development capabilities like continuous integration (CI) or continuous deployment (CD)? How to visualize the end-to-end dataflow? What about documentation?
I’ll show you how all this can be done in Microsoft Fabric. You will see how you can archive a fully SaaS enterprise business intelligence solution für Dynamics Business Central SaaS based exclusively on Microsoft products.
Microsoft Fabric - Warehouse, Lakehouse, Kusto, Dataset - A comparison
Data is key to digitalisation, data is key to AI. Microsoft Fabric is the data one-stop-shop for customers.
In Microsoft Fabric, there are four different ways to deliver data to Power BI. In this session, you will understand what the four ways are and how they work. But most importantly, you will understand when to use what. I will show you all four systems in small showcases and provide you with a comprehensive comparison between all four solutions as the key takeaway for you.
Boost your sales by data driven customers
Digitalization is not a technical necessity but a change of thinking. What If decision makers can get complex insights in a pretty comprehensible format? What if decision makers can always trust the figures? What if decision makers can get his data whenever they need it? They can decide faster and better. The outcome: Increasing customer success and increasing investment in digitalization. To achieve this, customers need to change their data use behavior. Instead of get data and find anomalies, see anomalies first and investigate the related data only. Data grows exponential. Time consuming bottom-up analysis will not be an option soon anymore. Keep your customer successful. I explain how to encourage a customer to become data driven.
How to achieve fast and reliable Power BI reports on complex data
Power BI on complex data sources like an EPR system is a difficult task. Power Query delivers a nice set of functionality, but using it on millions of rows is not a comfortable way to denormalize your data. But this is a necessary task to create simple star schema data models. It is even harder to achieve a fast Power BI report if you need more than one complex data source. Bad data quality is often another challenge you have to face. I will show you a way to archive fast and reliable enterprise level Power BI reports.
Andreas Koblischke
data culture evangelist
Hamburg, Germany
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