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Using Microsoft Fabric’s Lakehouse Data and prompt flow in Azure Machine Learning Service to create RAG applications | Microsoft Fabric Blog | Microsoft Fabric
Using Microsoft Fabric’s Lakehouse Data and prompt flow in Azure Machine Learning Service to create RAG applications | Microsoft Fabric Blog | Microsoft Fabric
Microsoft Fabric’s Lakehouse helps us better unified management of enterprise-level data environments. In the process of transforming to AI, we cannot do without the assistance of these enterprise data. In my previous blog, I mentioned how to build RAG applications based on data in the Microsoft Fabric environment. In this post, I will introduce how … <p class="link-more"><a href="https://blog.fabric.microsoft.com/en-us/blog/using-microsoft-fabrics-lakehouse-data-and-prompt-flow-in-azure-machine-learning-service-to-create-rag-applications/" class="more-link">Continue reading<span class="screen-reader-text"> “Using Microsoft Fabric’s Lakehouse Data and prompt flow in Azure Machine Learning Service to create RAG applications”</span></a>
·blog.fabric.microsoft.com·
Using Microsoft Fabric’s Lakehouse Data and prompt flow in Azure Machine Learning Service to create RAG applications | Microsoft Fabric Blog | Microsoft Fabric
Why One Person Can't Do Everything In Data
Why One Person Can't Do Everything In Data
No one person can perform every data-related task in an organization. Here's a way to explain role classification by skill set.
Data roles are often the first subject I discuss when building data literacy
This communication becomes a survival tactic if you are one of a few data folks in an organization
Here’s an analogy that stresses differences between data roles and elucidates the broad ecosystem needs for data development:
It is impossible for one person to build a college dorm, populate it, manage it, work with the students, tell their stories, and research the impact.
·nightingaledvs.com·
Why One Person Can't Do Everything In Data
Incremental Refresh in Power BI, Part 2; Best Practice; Do NOT Publish Data Model Changes from Power BI Desktop - BI Insight
Incremental Refresh in Power BI, Part 2; Best Practice; Do NOT Publish Data Model Changes from Power BI Desktop - BI Insight
In a previous post, I shared a comprehensive guide on implementing Incremental Data Refresh in Power BI Desktop. We covered essential concepts such as truncation and load versus incremental load, understanding historical and incremental ranges, and the significant benefits of adopting incremental refresh for large tables. If you missed that post, I highly recommend giving … Continue reading Incremental Refresh in Power BI, Part 2; Best Practice; Do NOT Publish Data Model Changes from Power BI Desktop
·biinsight.com·
Incremental Refresh in Power BI, Part 2; Best Practice; Do NOT Publish Data Model Changes from Power BI Desktop - BI Insight
Fabric Notebook Concurrency Explained — Advancing Analytics
Fabric Notebook Concurrency Explained — Advancing Analytics
If you keep up with the latest developments in the data space, you will probably know that Microsoft Fabric has now reached general availability. One of the trickiest things we’ve had to come to terms with is how concurrency works and how to run multiple notebooks at once without errors.
·advancinganalytics.co.uk·
Fabric Notebook Concurrency Explained — Advancing Analytics
Lakehouse vs Data Warehouse vs Real-Time Analytics/KQL Database: Deep Dive into Use Cases, Differences, and Architecture Designs | Microsoft Fabric Blog | Microsoft Fabric
Lakehouse vs Data Warehouse vs Real-Time Analytics/KQL Database: Deep Dive into Use Cases, Differences, and Architecture Designs | Microsoft Fabric Blog | Microsoft Fabric
With the general availability of Microsoft Fabric this past Ignite, there are a lot of questions centered around the functionality of each component but more importantly, what architecture designs and solutions are best for analytics in Fabric. Specifically, how your data estate for analytics data warehousing/reporting will change or differ from existing designs and how to choose the right path moving forward. This article will be focused on helping you understand the differences between the Data Warehouse and Data Lakehouse, Fabric solution designs, warehouse/lakehouse use cases, and to get the best of both Data Warehouse and Data Lakehouse.
·blog.fabric.microsoft.com·
Lakehouse vs Data Warehouse vs Real-Time Analytics/KQL Database: Deep Dive into Use Cases, Differences, and Architecture Designs | Microsoft Fabric Blog | Microsoft Fabric
Prebuilt Azure AI services in Fabric | Microsoft Fabric Blog | Microsoft Fabric
Prebuilt Azure AI services in Fabric | Microsoft Fabric Blog | Microsoft Fabric
During the recent Ignite 2023 event, we announced the public preview of prebuilt AI services in Fabric. This integration with Azure AI services, formerly known as Azure Cognitive Services, allows for easy enhancement of data with prebuilt AI models without any prerequisites.  Using AI services in Fabric has never been easier! In the past, you … <p class="link-more"><a href="https://blog.fabric.microsoft.com/en-us/blog/prebuilt-azure-ai-services-in-fabric-2/" class="more-link">Continue reading<span class="screen-reader-text"> “Prebuilt Azure AI services in Fabric”</span></a>
·blog.fabric.microsoft.com·
Prebuilt Azure AI services in Fabric | Microsoft Fabric Blog | Microsoft Fabric
Microsoft Fabric December 2023 Update | Microsoft Fabric Blog | Microsoft Fabric
Microsoft Fabric December 2023 Update | Microsoft Fabric Blog | Microsoft Fabric
Welcome to the December 2023 update. We have lots of features this month including More styling options for column and bar charts, calculating distinct counts in Power BI running reports on KQL Databases, Changes to workspace retention settings in Fabric and Power BI, and many more.
·blog.fabric.microsoft.com·
Microsoft Fabric December 2023 Update | Microsoft Fabric Blog | Microsoft Fabric
Using Microsoft Fabric’s Lakehouse Data and prompt flow in Azure Machine Learning Service to create RAG applications | Microsoft Fabric Blog | Microsoft Fabric
Using Microsoft Fabric’s Lakehouse Data and prompt flow in Azure Machine Learning Service to create RAG applications | Microsoft Fabric Blog | Microsoft Fabric
Microsoft Fabric’s Lakehouse helps us better unified management of enterprise-level data environments. In the process of transforming to AI, we cannot do without the assistance of these enterprise data. In my previous blog, I mentioned how to build RAG applications based on data in the Microsoft Fabric environment. In this post, I will introduce how … <p class="link-more"><a href="https://blog.fabric.microsoft.com/en-us/blog/using-microsoft-fabrics-lakehouse-data-and-prompt-flow-in-azure-machine-learning-service-to-create-rag-applications/" class="more-link">Continue reading<span class="screen-reader-text"> “Using Microsoft Fabric’s Lakehouse Data and prompt flow in Azure Machine Learning Service to create RAG applications”</span></a>
·blog.fabric.microsoft.com·
Using Microsoft Fabric’s Lakehouse Data and prompt flow in Azure Machine Learning Service to create RAG applications | Microsoft Fabric Blog | Microsoft Fabric
Power BI Templates – Data Meerkat
Power BI Templates – Data Meerkat
".pbit" files are well-known in the Power BI world. But this is not the only type of "template" we can encounter. It depends on the scenario we are trying to fulfill.
·datameerkat.com·
Power BI Templates – Data Meerkat
Using join functions in DAX - SQLBI
Using join functions in DAX - SQLBI
This article describes the practical uses of NATURALLEFTOUTERJOIN and NATURALINNERJOIN in DAX. These functions are not commonly used in DAX because they do
·sqlbi.com·
Using join functions in DAX - SQLBI
Power BI implementation planning: BI tactical planning - Power BI
Power BI implementation planning: BI tactical planning - Power BI
This article helps you to identify your business intelligence objectives and form actionable plans to achieve incremental progress toward your strategic BI goals.
When you identify objectives, also consider how you can objectively evaluate and measure their impact. It's critical that you accurately describe the (potential) return on investment (ROI) for BI initiatives in order to attain sufficient executive support and resources. You can assess this impact together with your measures of success for your BI strategy.
First, identify your adoption objectives. These objectives can address many areas, but typically describe the actions you'll take to improve overall organizational adoption and data culture.
Define organizational readiness As described in the previous sections, the objectives you identify must be achievable. You should assess your organizational readiness to evaluate how prepared the organization is to achieve the objectives you've identified. Assess organizational readiness by considering the factors described in the following sections.
Here are some examples of obstacles. System migrations and other ongoing technical initiatives Business processes and planning, like fiscal year budgets Business mergers and restructuring Availability of stakeholders Availability of resources, including the available time of central team members Skills of central team members and business users Communication and change management activities to adequately inform and prepare business users about
Assess the necessary skills and knowledge
Improving the skills and competences of internal teams is particularly important when you migrate to Fabric or Power BI from other technologies. Don't rely exclusively on external consultants for these migrations. Ensure that internal team members have sufficient time and resources to upskill, so they'll work effectively with the new tools and processes.
Define and measure success
Step 3: Periodically revise the plan The business and technology context of your organization regularly changes. As such, you should periodically reevaluate and reassess your BI strategy and tactical planning. The goal is to keep them relevant and useful for your organization. In step 3 of tactical planning, you take practical steps to iteratively reevaluate and reassess planning. Prepare iterative planning and anticipate change To ensure BI and business strategic alignment, you should establish continuous improvement cycles. These cycles should be influenced by the success criteria (your KPIs or OKRs) and the feedback that you regularly collect to evaluate progress. We recommend that you conduct tactical planning at regular intervals with evaluation and assessment, as depicted in the following diagram
Schedule business alignment meetings:
Review feedback and requests: Feedback and requests from the user community is valuable input to reevaluate your BI strategy. Consider setting up a communication hub, possibly with channels like office hours, or feedback forms to collect feedback.
A BI strategy is a plan to implement, use, and manage data and analytics. You define your BI strategy by starting with BI strategic planning
To work toward your BI goals, the working team defines specific objectives by doing tactical planning
This process shifts the focus from strategic planning to tactical planning.
start, we recommend that you first address time-sensitive, quick-win, and high-impact objectives.
successful implementation of your BI strategy is more likely when you aim for an evolution instead of a revolution from your current state. Evolution implies that you strive for gradual change over time. Small but consistent, sustained progress is better than an abundance of change that risks disruption to ongoing activities.
curating this backlog for your implementation objectives, consider the following points. Justify the prioritization of the initiative or solution. Approximate the effort involved, if possible. Outline the anticipated scope.
·learn.microsoft.com·
Power BI implementation planning: BI tactical planning - Power BI
Power BI December 2023 Feature Summary
Power BI December 2023 Feature Summary
Welcome to the Power BI December 2023 update. We’ve got a lot of great features this month. Here are some key highlights: Learn how you can skill up and get ready for the upcoming Fabric Analytics Engineer certification with the Cloud Skills Challenge. Join us at the first annual Microsoft Fabric Community Conference (Mar 26-28 2024)  We’ve made lots of improvement for reporting, for example there are many more options for styling your column and bar charts. If you are a fan of our PowerPoint add-in, you’ll be happy to know we’ve made it easier to find and insert Power BI content into your PowerPoint presentations. Developers can now handle with git merge conflicts directly in the workspace.
·powerbi.microsoft.com·
Power BI December 2023 Feature Summary
The future of customer understanding through Microsoft Fabric
The future of customer understanding through Microsoft Fabric
In the many conversations I had over the past years, it is a returning topic to talk about complexity of bringing your CRM and ERP data together to create a 360-degree customer view. While doing bu…
·data-marc.com·
The future of customer understanding through Microsoft Fabric
What’s new: Power Apps November 2023 Feature Update
What’s new: Power Apps November 2023 Feature Update
Welcome to the Power Apps monthly feature update! We will use this blog to share a summary of product, community, and learning updates from throughout the month so you can access it in one easy place. We’ve got a great set of updates across for our makers, security and monitor improvements, and updates to model driven apps for end users.
·powerapps.microsoft.com·
What’s new: Power Apps November 2023 Feature Update
Fabric Python Helper Functions
Fabric Python Helper Functions
Since Fabric went GA I’ve moved the small amount of stuff that we had running in Azure Synapse into Fabric notebooks. (Sadly a large amount of our data estate is still sat on prem with SSIS&#…
·dobbsondata.co.uk·
Fabric Python Helper Functions
Quick Tips: Find Power BI Desktop Local Port Number with Model Explorer - BI Insight
Quick Tips: Find Power BI Desktop Local Port Number with Model Explorer - BI Insight
In March 2018, I wrote a blogpost called Four Different Ways to Find Your Power BI Desktop Local Port Number. Last week, Zoe Doughlas from Microsoft left a comment reminding me of a fifth method to get the port which encouraged me to write this quick tip. Thanks to Zoe! As the name suggests, the … Continue reading Quick Tips: Find Power BI Desktop Local Port Number with Model Explorer
·biinsight.com·
Quick Tips: Find Power BI Desktop Local Port Number with Model Explorer - BI Insight
Read data from Delta Lake tables with the DeltaLake.Table M function | Microsoft Fabric Blog | Microsoft Fabric
Read data from Delta Lake tables with the DeltaLake.Table M function | Microsoft Fabric Blog | Microsoft Fabric
We’re happy to announce a new function in Power Query’s M language for reading data from Delta Lake tables: the DeltaLake.Table function. This function is now available in Power Query in Power BI Desktop and in Dataflows Gen1 and Gen2 and replaces the need to use community-developed solutions like this one by Gerhard Brueckl. Let’s … <p class="link-more"><a href="https://blog.fabric.microsoft.com/en-us/blog/read-data-from-delta-lake-tables-with-the-deltalake-table-m-function/" class="more-link">Continue reading<span class="screen-reader-text"> “Read data from Delta Lake tables with the DeltaLake.Table M function”</span></a>
·blog.fabric.microsoft.com·
Read data from Delta Lake tables with the DeltaLake.Table M function | Microsoft Fabric Blog | Microsoft Fabric
Create charts using Vega in Microsoft Fabric Notebook - Phil Seamark on DAX
Create charts using Vega in Microsoft Fabric Notebook - Phil Seamark on DAX
I recently needed to generate a quick visual inside a Microsoft Fabric notebook. After a little internet searching, I found there are many good quality charting libraries in Python, however it was going to take too long to figure out how to create a very specific type of chart. This is where Vega came to … Continue reading Create charts using Vega in Microsoft Fabric Notebook
·dax.tips·
Create charts using Vega in Microsoft Fabric Notebook - Phil Seamark on DAX
Preparing a data model for Sankey Charts in Power BI - SQLBI
Preparing a data model for Sankey Charts in Power BI - SQLBI
This article describes how to correctly shape a data model and prepare data to use a Sankey Chart as a funnel, considering events related to a customer (con
·sqlbi.com·
Preparing a data model for Sankey Charts in Power BI - SQLBI