Dax studio 2 16 2

Author: w | 2025-04-25

★★★★☆ (4.4 / 3410 reviews)

download fortinet vpn client

DAX Studio 2.16.2. Date released: (one year ago) Download. DAX Studio 2.16.1. Date released: (2 years ago) Download. DAX Studio 2.16.0. Date released: (2 years ago) Download. DAX Studio 2.15.0. Date released: (2 years ago) Download. DAX Studio 2.14.1. DAX Studio 3.0.6. Date released: (one year ago) Download. DAX Studio 3.0.5. Date released: (2 years ago) Download. DAX Studio 3.0.4. Date released: (2 years ago) Download. DAX Studio 3.0.3. Date released: (2 years ago) Download. DAX Studio 3.0.2.

record screen with vlc

Silent Installation of DAX Studio (2.) - ManageEngine

Amount of time required to refresh the visuals in the report, that might be due to the number and complexity of the visuals included in a single page.If a query requires a large amount of time, it is possible to review the complete DAX query with a double-click on that specific line. The entire DAX syntax is copied into the DAX Studio editor. You may run the query again using the Run button. It is better to clear the cache before running the query when working on performance optimization.Capturing DAX queries generated by interaction with slicersIt can be useful to capture the queries generated by the interaction with one or more slicers. You can pay attention to the StartTime of the last query captured by DAX Studio, or you can clear the query list by clicking the Clear All button.In Power BI Desktop, click the item “Europe” in the Continent slicer. DAX Studio displays the new queries generated by the interaction with the slicer.In this case, the slowest query is caused by an issue in the Customers measure, which is the only measure used in the query highlighted in yellow in the previous screenshot. This is the initial definition of Customers:Customers := CALCULATE ( DISTINCTCOUNT ( Sales[CustomerKey] ), FILTER ( Sales, Sales[Quantity] > 0 ))By replacing the measure in the Power BI model with a more optimized version, the main performance issue of the DAX model is resolved. Here is our suggestion:Customers := CALCULATE ( DISTINCTCOUNT ( Sales[CustomerKey] ), Sales[Quantity] > 0)By repeating this cycle from the beginning, it is possible to carry on this performance improvement of DAX queries by fixing a single measure. Keep in mind, the order of the queries for the same report might be different from one execution to the next – especially if the Duration changes. In the following example, we see that for that same query that used to run in over 2 seconds, the Duration is now down to 20 milliseconds.The time required to refresh the Power BI page examined so far is now mainly impacted by the number of visuals displayed in the same page. Each of these visuals generates a DAX query, and there are no queries taking more than 20 milliseconds to run. Further improvements to the DAX measures are no longer possible – the only possible optimization left would be to reduce the number of visuals in the DAX page, thus generating a smaller number of DAX queries.ConclusionsWhen dealing with performance issues in Power BI, it is useful to understand whether the problem is caused by the DAX code in the data model, or by the number and/or complexity of the visuals included in a report page. The

convert xml to pdf

Download free Dax Studio 2. - FreeDownloadManager.org

DAX Studio is a great external tool to write, execute and analyze DAX queries in Power BI. A user now has the ability to not only analyze data using DAX but also export data from the Power BI report to SQL tables and CSV files. In this tutorial, we will be learning how to export data from the Power BI report to the SQL server to perform analysis using SQL. This feature is great to use when we have the PBI report but we can’t access the data source directly in SSMS to perform analysis on the data. Follow the instructions to export data from the Power BI report to SQL server to perform analysis using SQL I. Download DAX Studio version 2.13 To begin with the process, you first need to have the latest version of DAX studio as this feature is not available in the older versions. Open PBIX file II. In order to connect DAX studio to Power BI, open your Power BI file. III. Connect DAX Studio with PBI Report Now open DAX Studio and in Data Source settings select PBI/SSDT Model option. In the dropdown menu, you‘ll be able to see the report you opened in the previous step. Select the desired report from the dropdown. Connect to the report. IV. Exporting Data to SSMS To Analyse Data Using SQL From the main stage, navigate to the toolbar and select the Advanced menu. Select Export Data option. In Export Data Wizard, select SQL Tables. V.

Writing DAX Queries - DAX Studio

Skip to content Navigation Menu GitHub Copilot Write better code with AI Security Find and fix vulnerabilities Actions Automate any workflow Codespaces Instant dev environments Issues Plan and track work Code Review Manage code changes Discussions Collaborate outside of code Code Search Find more, search less Explore Learning Pathways Events & Webinars Ebooks & Whitepapers Customer Stories Partners Executive Insights GitHub Sponsors Fund open source developers The ReadME Project GitHub community articles Enterprise platform AI-powered developer platform Pricing Provide feedback Saved searches Use saved searches to filter your results more quickly //voltron/discussions_fragments/discussion_layout;ref_cta:Sign up;ref_loc:header logged out"}"> Sign up Notifications You must be signed in to change notification settings Fork 149 Star 728 Code Issues 149 Pull requests Discussions Actions Projects Wiki Security Insights Hi all,Does anyone know if Dax Studio v. 2.17.3 is compatible with SSAS 2022 and, as a consequence, with level 1600?Thanks a lot.Best Regards,Matteo You must be logged in to vote It's pretty hard to say. v2.17.3 was released a year before SSAS 2022. If it does not work the simplest solution would be to just use the latest release of DAX Studio. You must be logged in to vote 0 replies 2 participants This discussion was converted from issue #1182 on September 27, 2023 09:47. Heading Bold Italic " data-analytics-event="{"category":"comment_box","action":"QUOTE","label":null}" aria-labelledby="tooltip-a75f23d2-8d64-4e02-a612-6aaf6111cca5" type="button" data-view-component="true" class="Button Button--iconOnly Button--invisible Button--medium"> Quote Code Link Numbered list Unordered list Task list Attach files Mention Reference Menu Heading Bold Italic Quote Code Link Numbered list Unordered list Task list Attach files Mention Reference Select a reply Loading Create a new saved reply 👍 1 reacted with thumbs up emoji 👎 1 reacted with thumbs down emoji 😄 1 reacted with laugh emoji 🎉 1 reacted with hooray emoji 😕 1 reacted with confused emoji ❤️ 1 reacted with heart emoji 🚀 1 reacted with rocket emoji 👀 1 reacted with eyes emoji. DAX Studio 2.16.2. Date released: (one year ago) Download. DAX Studio 2.16.1. Date released: (2 years ago) Download. DAX Studio 2.16.0. Date released: (2 years ago) Download. DAX Studio 2.15.0. Date released: (2 years ago) Download. DAX Studio 2.14.1.

DAX Studio Support Formation DAX

Preparing the Power BI reportEvery page in a Power BI report usually creates one or more DAX queries to populate its visuals. . When you switch to a different page, new queries might be sent to the engine. Moreover, changing the selection of a slicer also generates new queries. However, Power BI also uses a cache system to avoid sending the same DAX query multiple times. Therefore, it is useful to make sure that the cache is empty in order to capture all the queries generated for a single page of a report.For example, consider the following report that is made up of a single page.When the report is opened, the DAX queries are immediately generated and sent to the engine. There is not enough time to open DAX Studio and activate the trace to capture all the DAX queries: some of these queries will already be executed.To avoid this problem and to make sure that all the queries can be captured in DAX Studio, the Power BI file should contain an empty page. Thus, you should create a new empty page and save the PBIX file ensuring that it is the current active page of the report.This way, the next time you open the PBIX file, the empty page will be displayed and no queries will be sent to the engine until you click on another page.Once the file is ready, close Power BI Desktop. Then, reopen Power BI Desktop and open the file that you prepared in the previous step. The empty page should appear in the report. The next step involves connecting to Power BI from DAX Studio.Connecting DAX Studio to Power BI to capture queriesKeeping Power BI Desktop open with the empty page selected, open DAX Studio and select the PBI / SSDT Model that is open.Click on the All Queries button in the Traces section of the ribbon.Make sure that you see the message, “Query Trace Started” in the Output pane.Switch to the All Queries result pane. There should be an empty list at this time. You can see that the Start button is not an available option, indicating that the trace is already running.DAX Studio is now ready to capture all the DAX queries generated by Power BI reports.Capturing DAX queries from the active page of your reportKeeping DAX Studio open, switch to the Power BI Desktop window and select the page of the report that displays the data.This simple report generates many queries, which are captured and displayed in the All Queries pane in DAX Studio.The Duration column measures the time spent resolving each query, in milliseconds. If there is a significant discrepancy between the sum of all DAX queries durations and the

แนวทางการใช้ DAX Studio ในการตรวจสอบและเรียนรู้ DAX

DAX Query ExplorerThe most powerful and intuitive way to visualize and analyze DAX query execution plans. DAX Query Explorer transforms complex query plans into interactive, visual flowcharts that make understanding query execution simple and efficient.FeaturesInteractive Visualization: Transform text-based DAX query plans into interactive, visual flowchartsFlexible Input Formats: Support for both plain text query plans and JSON format exported from DAX StudioNode Type Differentiation: Distinct visual representations for different operation types:Spool Physical Operations (SpoolPhyOp)Iteration Physical Operations (IterPhyOp)Lookup Physical Operations (LookupPhyOp)Scalar Logical Operations (ScaLogOp)Relational Logical Operations (RelLogOp)Collapsible Nodes: Simplify complex plans by collapsing nodes to focus on specific parts of the executionSmart Layout: Automatic node positioning and edge routing for optimal readabilityPlan Sharing: Share query plans with colleagues via unique URLsResponsive Design: Works seamlessly on both desktop and mobile devicesGetting StartedVisit DAX Query ExplorerPaste your DAX query plan into the editor:Either paste the plain text query planOr paste the JSON output exported from DAX StudioClick "Parse Query Plan" to generate the visual representationExplore the execution plan through the interactive visualizationUsageViewing Query PlansThe interface is split into two main sections:Left: Code editor for inputting DAX query plans (accepts both text and JSON formats)Right: Interactive flowchart visualizationInput FormatsDAX Query Explorer supports two input formats:Plain Text: The standard text output of a DAX query planJSON Format: The JSON export from DAX Studio, containing both physical and logical query plan rowsNode InformationEach node in the visualization contains important information about the operation:Operation type and nameNumber of records processedKey columns and value columnsAdditional operation-specific detailsSharing PlansClick the "Share Plan" button in the top right cornerA unique URL will be generated and copied to your clipboardShare the URL with others to let them view the same query planWhy DAX Query Explorer?Understanding DAX query plans is crucial for optimizing Power BI and Analysis Services performance. DAX Query Explorer makes this process intuitive by:Converting complex text-based plans into clear visual representationsHighlighting relationships between operationsMaking it easy to identify bottlenecks and optimization opportunitiesFacilitating collaboration through plan sharingContributingWe welcome contributions! Please feel free to submit issues and pull requests.

DAX Studio 3.2.1 Download for Windows / Old Versions Page 2

In Power BI Lecture 9: Optimizing Power BI Development with the Analyst Hub Lecture 10: Mastering Iterating Functions in Power BI Lecture 11: Insights to Advanced Power BI Concepts Lecture 12: Advanced DAX Concepts To Master In Power BI – Review Chapter 5: Improving UX & Data Storytelling Lecture 1: Must Read: Additional Content Lecture 2: Adaptive Design: Data Storytelling Facts Lecture 3: Y-Axis Unification in Data Visualization Lecture 4: Optimizing Visuals with Field Parameters and Slicers Lecture 5: Enhancing Table Visuals for Clearer Data Presentation Lecture 6: Optimizing Tables and Pie Charts for Clarity Lecture 7: Chart Refinements and Managing Empty Data Views Lecture 8: Enhancing Bar Charts with Switch Functions Lecture 9: Enhancing Data Visualization with Deneb and Conditional Formatting Lecture 10: Enhancing UX with Dynamic Buttons and Custom Markers Lecture 11: Enhancing UX with Quadrant Highlighting & Interactive Headers Lecture 12: Interactive Headers and Dynamic Narratives in Data Visualization Lecture 13: Improving UX & Data Storytelling – Review Lecture 14: Elevating Data Narratives: Merging Design & DAX for Enhanced UX Chapter 6: Advanced Data Storytelling Features In Power BI Lecture 1: Must Read: Additional Content Lecture 2: Data Storytelling: Did you know? Lecture 3: Advanced Features Introduction Lecture 4: Mastering Element Grouping & Bookmarks Lecture 5: Exploring Dynamic Visualization Strategies Lecture 6: Implementing Interactive Notification Systems Lecture 7: Enhancing Reports with Advanced Filters Lecture 8: Designing Intuitive Reports in Power BI Lecture 9: Advanced Data Storytelling Features In Power BI – Review Lecture 10: Mastering the Art of Power BI Storytelling Chapter 7: Offset: Making DAX Time Intelligence Disappear Lecture 1: Must Read: Additional Content Lecture 2: Intriguing DAX Facts Lecture 3: The four key problems in learning DAX Lecture 4: OFFSETS as the magic solution Lecture 5: Previous period with and without OFFSET Lecture 6: Year to date and cumulative total with and without OFFSET Lecture 7: Moving averages with and without OFFSET Lecture 8: Networkdays: Business days vs. all days Lecture 9: Performance: OFFSET vs. standard time intelligence Lecture 10: Making DAX Time Intelligence Disappear – Review Lecture 11: Unraveling the Magic of DAX Offsets Chapter 8: High Level Analytics with Power BI Lecture 1: Must Read: Additional Content Lecture 2: High-level Analytics in Power BI Facts Lecture 3: Resouces Lecture 4: Insights to high-Level Analytics with Power BI Lecture 5: Understanding Key Measures in Power BI Lecture 6: Analytical Techniques and Formula Patterns Lecture 7: Keys to Effective Power BI Implementation Lecture 8: The Power of Visualization in Reports Lecture 9: High Level Analytics with Power BI – Review Lecture 10: Mastering Advanced Analytics in Power BI Chapter 9: Course Assignment – Advanced Skills for Power BI Users Lecture 1: Download Dataset Chapter 10: Additional Resources – Complimentary guides for your data career Lecture 1: 2024 Data Career Guide – Enterprise DNA Instructors Enterprise DNA Future-Proof Your Career: Master Data Skills | Upskill in AIRating Distribution1 stars: 2 votes2 stars: 0 votes3 stars: 2 votes4 stars: 3 votes5 stars: 9 votesFrequently Asked QuestionsHow long

DAX Tools - DAX Studio 8 – Format DAX - YouTube

I am working to solve mass balance equations for 4 connected chemical process control units for a continuous operation. The resulting one dimensional coupled and (non-coupled) Partial Differential Equations are aimed to be solved using Method of Lines with finite difference method. One process unit includes a coupled PDE. The general form of the equations follows convection – diffusion format (see attached pdf)The code uses the pdepe solver and is attached alongwith, for the following equations (refer pdf attached).The results from both the approaches differ significantly towards the end iterations. Could anyone suggest me what am I missing or any restriction on the solution approach? I am not sure how the second derivative is approximated at the first discrete as well. Thank you for all your help.tspan = linspace(0,20,2000); [T,Y] = ode15s(@(t,y) numericalprimertubular(t,y,x,n),tspan,y0);myCB = Y(:,n+1:(2*n)-10);myCC = Y(:,2*n+1:(3*n)-10);myCD = Y(:,3*n+1:(4*n)-10); Using the pdepe solver for the same examplesol = pdepe(0,@pdex2pde,@pdex2ic,@pdex2bc,z,t); CA = sol(:,:,1); CB = sol(:,:,2); CC = sol(:,:,3); CD = sol(:,:,4);function definitions:function DyDt = numericalprimertubular(t,y,x,n)xhalf(1:n-1)=(x(1:n-1)+x(2:n))/2;DuDx(1) = (u(1)-1)*(vel/Dax); DvDx(1) = (v(1)-1)*(vel/Dax);DcDx(1) = (c(1)-0)*(vel/Dax);DdDx(1) = (d(1)-0)*(vel/Dax);D2uDx2(1) = 1.0/(xhalf(1)-x(1))*(u(2)-u(1))/(x(2)-x(1)); D2vDx2(1) = 1.0/(xhalf(1)-x(1))*(v(2)-v(1))/(x(2)-x(1)); D2cDx2(1) = 1.0/(xhalf(1)-x(1))*(c(2)-c(1))/(x(2)-x(1));D2dDx2(1) = 1.0/(xhalf(1)-x(1))*(d(2)-d(1))/(x(2)-x(1)); DuDx(i) = ((x(i)-x(i-1))/(x(i+1)-x(i))*(u(i+1)-u(i))+(x(i+1)-x(i))/(x(i)-x(i-1))*(u(i)-u(i-1)))/(x(i+1)-x(i-1)); D2uDx2(i) = (xhalf(i)*(u(i+1)-u(i))/(x(i+1)-x(i))-xhalf(i-1)*(u(i)-u(i-1))/(x(i)-x(i-1)))/(xhalf(i)-xhalf(i-1)); DvDx(i) = ((x(i)-x(i-1))/(x(i+1)-x(i))*(v(i+1)-v(i))+(x(i+1)-x(i))/(x(i)-x(i-1))*(v(i)-v(i-1)))/(x(i+1)-x(i-1)); D2vDx2(i) = (xhalf(i)*(v(i+1)-v(i))/(x(i+1)-x(i))-xhalf(i-1)*(v(i)-v(i-1))/(x(i)-x(i-1)))/(xhalf(i)-xhalf(i-1)); DcDx(i) = ((x(i)-x(i-1))/(x(i+1)-x(i))*(c(i+1)-c(i))+(x(i+1)-x(i))/(x(i)-x(i-1))*(c(i)-c(i-1)))/(x(i+1)-x(i-1)); D2cDx2(i) = (xhalf(i)*(c(i+1)-c(i))/(x(i+1)-x(i))-xhalf(i-1)*(c(i)-c(i-1))/(x(i)-x(i-1)))/(xhalf(i)-xhalf(i-1)); DdDx(i) = ((x(i)-x(i-1))/(x(i+1)-x(i))*(d(i+1)-d(i))+(x(i+1)-x(i))/(x(i)-x(i-1))*(d(i)-d(i-1)))/(x(i+1)-x(i-1)); D2dDx2(i) = (xhalf(i)*(d(i+1)-d(i))/(x(i+1)-x(i))-xhalf(i-1)*(d(i)-d(i-1))/(x(i)-x(i-1)))/(xhalf(i)-xhalf(i-1)); DuDt(i) = Dax*D2uDx2(i) - vel*DuDx(i) - k1*u(i)*v(i); DvDt(i) = Dax*D2vDx2(i) - vel*DvDx(i) - k1*u(i)*v(i)-k2*v(i)*c(i); DcDt(i) = Dax*D2cDx2(i) - vel*DcDx(i) + k1*u(i)*v(i) - k2*v(i)*c(i); DdDt(i) = Dax*D2dDx2(i) - vel*DdDx(i) + k2*v(i)*c(i);DyDt = [DuDt;DvDt;DcDt;DdDt];function [c,f,s] = pdex2pde(z,t,C,dCdz)s = [-vz*dCdz(1)-k1*C(1)*C(2);-vz*dCdz(2)-k1*C(1)*C(2)-k2*C(2)*C(3);-vz*dCdz(3)+k1*C(1)*C(2)-k2*C(2)*C(3);-vz*dCdz(4)+ k2*C(2)*C(3)];function [pl,ql,pr,qr] = pdex2bc(zl,Cl,zr,Cr,t)pl = [Cl(1)-Cin(1);Cl(2)-Cin(2);Cl(3)-Cin(3);Cl(4)-Cin(4)];qr = [1/Dz;1/Dz;1/Dz;1/Dz];function C0 = pdex2ic(z); Accepted Answer Edited: Torsten on 13 Jan 2022 For the pdepe version, better usefunction [pl,ql,pr,qr] = pdex2bc(zl,Cl,zr,Cr,t) pl = [Cl(1)-Cin(1);Cl(2)-Cin(2);Cl(3)-Cin(3);Cl(4)-Cin(4)];I adopted the method-of-lines version:tspan = linspace(0,20,2000); [T,Y] = ode15s(@(t,y) numericalprimertubular(t,y,x,n),tspan,y0);plot(x.',[myCA(:,100),myCA(:,500),myCA(:,1000),myCA(:,1500),myCA(:,2000)])plot(x.',[myCB(:,100),myCB(:,500),myCB(:,1000),myCB(:,1500),myCB(:,2000)])plot(x.',[myCC(:,100),myCC(:,500),myCC(:,1000),myCC(:,1500),myCC(:,2000)])plot(x.',[myCD(:,100),myCD(:,500),myCD(:,1000),myCD(:,1500),myCD(:,2000)])function DyDt = numericalprimertubular(t,y,x,n)xhalf(1:n-1)=(x(1:n-1)+x(2:n))/2;DuDx(1) = (u(1)-1)*(vel/Dax); DvDx(1) = (v(1)-1)*(vel/Dax);DcDx(1) = (c(1)-0)*(vel/Dax);DdDx(1) = (d(1)-0)*(vel/Dax);D2uDx2(1) = ((u(2)-u(1))/(x(2)-x(1))-DuDx(1))/((x(2)-x(1))/2);D2vDx2(1) = ((v(2)-v(1))/(x(2)-x(1))-DvDx(1))/((x(2)-x(1))/2);D2cDx2(1) = ((c(2)-c(1))/(x(2)-x(1))-DcDx(1))/((x(2)-x(1))/2);D2dDx2(1) = ((d(2)-d(1))/(x(2)-x(1))-DdDx(1))/((x(2)-x(1))/2); DuDx(i) = (u(i)-u(i-1))/(x(i)-x(i-1)); D2uDx2(i) = (xhalf(i)*(u(i+1)-u(i))/(x(i+1)-x(i))-xhalf(i-1)*(u(i)-u(i-1))/(x(i)-x(i-1)))/(xhalf(i)-xhalf(i-1)); DvDx(i) = (v(i)-v(i-1))/(x(i)-x(i-1)); D2vDx2(i) = (xhalf(i)*(v(i+1)-v(i))/(x(i+1)-x(i))-xhalf(i-1)*(v(i)-v(i-1))/(x(i)-x(i-1)))/(xhalf(i)-xhalf(i-1)); DcDx(i) = (c(i)-c(i-1))/(x(i)-x(i-1)); D2cDx2(i) = (xhalf(i)*(c(i+1)-c(i))/(x(i+1)-x(i))-xhalf(i-1)*(c(i)-c(i-1))/(x(i)-x(i-1)))/(xhalf(i)-xhalf(i-1)); DdDx(i) = (d(i)-d(i-1))/(x(i)-x(i-1)); D2dDx2(i) = (xhalf(i)*(d(i+1)-d(i))/(x(i+1)-x(i))-xhalf(i-1)*(d(i)-d(i-1))/(x(i)-x(i-1)))/(xhalf(i)-xhalf(i-1));D2uDx2(n) = -(u(n)-u(n-1))/(x(n)-x(n-1))/((x(n)-x(n-1))/2);D2vDx2(n) = -(v(n)-v(n-1))/(x(n)-x(n-1))/((x(n)-x(n-1))/2);D2cDx2(n) = -(c(n)-c(n-1))/(x(n)-x(n-1))/((x(n)-x(n-1))/2);D2dDx2(n) = -(d(n)-d(n-1))/(x(n)-x(n-1))/((x(n)-x(n-1))/2); DuDt(i) = Dax*D2uDx2(i) - vel*DuDx(i) - k1*u(i)*v(i); DvDt(i) = Dax*D2vDx2(i) - vel*DvDx(i) - k1*u(i)*v(i) - k2*v(i)*c(i); DcDt(i) = Dax*D2cDx2(i) - vel*DcDx(i) + k1*u(i)*v(i) - k2*v(i)*c(i); DdDt(i) = Dax*D2dDx2(i) - vel*DdDx(i) + k2*v(i)*c(i);DyDt = [DuDt;DvDt;DcDt;DdDt]; More Answers (0) See Also Categories Community Treasure Hunt Find the treasures in MATLAB Central and discover how the community can help you! Start Hunting! An Error Occurred Unable to complete the action because of changes made to the page. Reload the page to see its updated state.. DAX Studio 2.16.2. Date released: (one year ago) Download. DAX Studio 2.16.1. Date released: (2 years ago) Download. DAX Studio 2.16.0. Date released: (2 years ago) Download. DAX Studio 2.15.0. Date released: (2 years ago) Download. DAX Studio 2.14.1. DAX Studio 3.0.6. Date released: (one year ago) Download. DAX Studio 3.0.5. Date released: (2 years ago) Download. DAX Studio 3.0.4. Date released: (2 years ago) Download. DAX Studio 3.0.3. Date released: (2 years ago) Download. DAX Studio 3.0.2.

open source convert pdf to word

EQ Studios - Studio 2 (16 desks), Victoria Street

Power of DAX to tell compelling narratives. Unleash dynamic drill-through interactions and contextual tooltips that engage users on a personal level. Apply conditional formatting with precision, guiding attention to critical data points. Through intricate design themes, you’ll craft a visual journey that resonates with your audience, enhancing UX and fostering a professional, consistent look and feel.Equip yourself with the expertise to predict outcomes, detect outliers, and structure effective data models that facilitate intuitive insights. Learn to construct analytical solutions that leave an indelible mark on data consumers. We’ll empower you to master matrix conditional formatting, turning your visuals into dynamic storytellers that captivate and enlighten.By the end of “DAX Pro: Advanced Skills for Power BI Users,” you’ll be armed with an arsenal of advanced DAX techniques, seamlessly integrated with design principles that bring your data to life. As you embark on this transformative learning journey, you’ll not only elevate your skills but also your capacity to shape data into a compelling narrative that drives action. Join us and become a DAX Pro, revolutionizing data storytelling and user experience in the world of Power BI.Don’t miss out on this unparalleled opportunity to propel your Power BI skills to new heights. Enroll now and embark on a journey that will redefine the way you approach data, insights, and the art of communication. Course Curriculum Chapter 1: Introduction Lecture 1: Learning Tips From Enterprise DNA Lecture 2: Course Resources Lecture 3: Microsoft Power BI user-interface updates to be aware of Lecture 4: Course Overview – Let's get started! Lecture 5: Power BI: Did you know? Chapter 2: Power BI Analytical Techniques Lecture 1: Advanced Techniques: Interesting Power BI Facts Lecture 2: Segmenting Success: Classification for Targeted Engagement Lecture 3: Detecting Anomalies: Uncover Unusual Patterns in Your Data Lecture 4: Mastering Cluster Analysis for Actionable Intelligence Lecture 5: Spotting Outliers: Enhancing Data Quality through Detection Techniques Lecture 6: Unlocking Opportunities: Exploring Cross-Sell Insights Using Power BI Lecture 7: Enhance Decision-Making with Advanced Pattern Recognition Lecture 8: Advanced Power BI Analytical Techniques – Review Lecture 9: Your Feedback Matters! Lecture 10: Insights to Advanced Power BI Techniques Chapter 3: Deep Dive to Advanced Techniques Lecture 1: Advanced Power BI: Key Facts You Must Know Lecture 2: Predictive Insights:Threshold Triggers & Breaches Lecture 3: Beyond Basics: Unleashing Power with Secondary Table Logic Lecture 4: Mastering Impact: Applying the Pareto Rule to Data Analysis Lecture 5: Strategy: Analyzing Customer Attrition Patterns Lecture 6: Climbing the Ranks: Building Dynamic Ranked Lists with Precision Lecture 7: Deep Dive to Advanced Techniques – Review Lecture 8: Navigating Advanced Power BI Techniques Chapter 4: Advanced DAX Concepts To Master In Power BI Lecture 1: Must Read: Additional Content Lecture 2: Intriguing Facts on Power BI and DAX Techniques Lecture 3: Section Resource Lecture 4: Mastering DAX's Calculate Function Lecture 5: Harnessing Variables and Calculate Table in DAX Lecture 6: Exploring Virtual Tables in DAX Lecture 7: Diving Deeper into Virtual Tables and Top Customers Lecture 8: Harnessing Virtual Tables and TopN

2 Peter 2:16 - Bible.com

DAX Pro: Advanced Skills for Power BI Users, available at $64.99, has an average rating of 3.8, with 83 lectures, 7 quizzes, based on 16 reviews, and has 210 subscribers.Enroll Now You will learn about Master advanced DAX formulas for insightful data analysis. Combine DAX patterns to solve diverse analytical challenges. Apply conditional formatting for focused data visualization. Craft compelling narratives through DAX-powered data storytelling. Implement dynamic drill-through interactions for deeper insights. Design visually engaging reports with consistent themes. Predict outcomes and detect outliers using strategic DAX techniques. Construct intuitive data models for powerful analytical solutions. This course is ideal for individuals who are Intermediate Power BI users looking to advance their skills. or Data analysts and business professionals seeking to master DAX. or Users with prior DAX knowledge wanting to deepen their expertise. or Anyone looking to unlock the full potential of Power BI's capabilities. It is particularly useful for Intermediate Power BI users looking to advance their skills. or Data analysts and business professionals seeking to master DAX. or Users with prior DAX knowledge wanting to deepen their expertise. or Anyone looking to unlock the full potential of Power BI's capabilities.Enroll now: DAX Pro: Advanced Skills for Power BI UsersSummaryTitle: DAX Pro: Advanced Skills for Power BI UsersPrice: $64.99Average Rating: 3.8Number of Lectures: 83Number of Quizzes: 7Number of Published Lectures: 83Number of Published Quizzes: 7Number of Curriculum Items: 91Number of Published Curriculum Objects: 91Original Price: $129.99Quality Status: approvedStatus: LiveWhat You Will LearnMaster advanced DAX formulas for insightful data analysis.Combine DAX patterns to solve diverse analytical challenges.Apply conditional formatting for focused data visualization.Craft compelling narratives through DAX-powered data storytelling.Implement dynamic drill-through interactions for deeper insights.Design visually engaging reports with consistent themes.Predict outcomes and detect outliers using strategic DAX techniques.Construct intuitive data models for powerful analytical solutions.Who Should AttendIntermediate Power BI users looking to advance their skills.Data analysts and business professionals seeking to master DAX.Users with prior DAX knowledge wanting to deepen their expertise.Anyone looking to unlock the full potential of Power BI's capabilities.Target AudiencesIntermediate Power BI users looking to advance their skills.Data analysts and business professionals seeking to master DAX.Users with prior DAX knowledge wanting to deepen their expertise.Anyone looking to unlock the full potential of Power BI's capabilities.Unlock the full potential of Power BI with our comprehensive Udemy course, “DAX Pro: Advanced Skills for Power BI Users.” Designed for seasoned Power BI enthusiasts, this course delves deep into the intricate world of Data Analysis Expressions (DAX) and strategic design integration. Elevate your analytical prowess and revolutionize the way you communicate insights.In this immersive journey, you’ll explore the synergy between DAX and design components, creating a seamless blend of technical excellence and captivating visual narratives. Starting with a solid foundation, we’ll guide you through advanced DAX formula combinations, enabling you to craft intricate calculations that reveal hidden insights. Delve into DAX patterns to tackle diverse analytical challenges, and explore a spectrum of beginner to advanced DAX functions.Discover the art of data storytelling as we walk you through harnessing the. DAX Studio 2.16.2. Date released: (one year ago) Download. DAX Studio 2.16.1. Date released: (2 years ago) Download. DAX Studio 2.16.0. Date released: (2 years ago) Download. DAX Studio 2.15.0. Date released: (2 years ago) Download. DAX Studio 2.14.1.

DAX Tools - DAX Studio 1 – Introduction - YouTube

Flag. That's a plus, and when you look closely at your data, you realize that the Hosts table contains two-letter country or region codes. Great. You need to create a new field in the Hosts table to store the flag URLs. In an earlier tutorial you used DAX to concatenate two fields, and we'll do the same for the flag URLs. In Power Pivot, select the empty column that has the title Add Column in the Hosts table. In the formula bar, type the following DAX formula (or you can copy and paste it into the formula column). It looks long, but most of it is the URL we want to use from the CIA Factbook.=REPLACE(" code])) In that DAX function you did a few things, all in one line. First, the DAX function REPLACE replaces text in a given text string, so by using that function you replaced the part of the URL that referenced France's flag (fr) with the appropriate two-letter code for each country or region. The number 82 tells the REPLACE function to begin the replacement 82 characters into the string. The 2 that follows tells REPLACE how many characters to replace. Next, you may have noticed that the URL is case-sensitive (you tested that first, of course) and our two-letter codes are uppercase, so we had to convert them to lowercase as we inserted them into the URL using the DAX function LOWER. Rename the column with the flag URLs to FlagURL. Your Power Pivot screen now looks like the following screen. Return to Excel and select the PivotTable in Sheet1. In PivotTable Fields, select ALL. You see the FlagURL field you added is available, as shown in the following screen. Notes: In some instances, the Alpha-2 code used by the CIA.gov World Factbook site

Comments

User8810

Amount of time required to refresh the visuals in the report, that might be due to the number and complexity of the visuals included in a single page.If a query requires a large amount of time, it is possible to review the complete DAX query with a double-click on that specific line. The entire DAX syntax is copied into the DAX Studio editor. You may run the query again using the Run button. It is better to clear the cache before running the query when working on performance optimization.Capturing DAX queries generated by interaction with slicersIt can be useful to capture the queries generated by the interaction with one or more slicers. You can pay attention to the StartTime of the last query captured by DAX Studio, or you can clear the query list by clicking the Clear All button.In Power BI Desktop, click the item “Europe” in the Continent slicer. DAX Studio displays the new queries generated by the interaction with the slicer.In this case, the slowest query is caused by an issue in the Customers measure, which is the only measure used in the query highlighted in yellow in the previous screenshot. This is the initial definition of Customers:Customers := CALCULATE ( DISTINCTCOUNT ( Sales[CustomerKey] ), FILTER ( Sales, Sales[Quantity] > 0 ))By replacing the measure in the Power BI model with a more optimized version, the main performance issue of the DAX model is resolved. Here is our suggestion:Customers := CALCULATE ( DISTINCTCOUNT ( Sales[CustomerKey] ), Sales[Quantity] > 0)By repeating this cycle from the beginning, it is possible to carry on this performance improvement of DAX queries by fixing a single measure. Keep in mind, the order of the queries for the same report might be different from one execution to the next – especially if the Duration changes. In the following example, we see that for that same query that used to run in over 2 seconds, the Duration is now down to 20 milliseconds.The time required to refresh the Power BI page examined so far is now mainly impacted by the number of visuals displayed in the same page. Each of these visuals generates a DAX query, and there are no queries taking more than 20 milliseconds to run. Further improvements to the DAX measures are no longer possible – the only possible optimization left would be to reduce the number of visuals in the DAX page, thus generating a smaller number of DAX queries.ConclusionsWhen dealing with performance issues in Power BI, it is useful to understand whether the problem is caused by the DAX code in the data model, or by the number and/or complexity of the visuals included in a report page. The

2025-04-03
User6635

DAX Studio is a great external tool to write, execute and analyze DAX queries in Power BI. A user now has the ability to not only analyze data using DAX but also export data from the Power BI report to SQL tables and CSV files. In this tutorial, we will be learning how to export data from the Power BI report to the SQL server to perform analysis using SQL. This feature is great to use when we have the PBI report but we can’t access the data source directly in SSMS to perform analysis on the data. Follow the instructions to export data from the Power BI report to SQL server to perform analysis using SQL I. Download DAX Studio version 2.13 To begin with the process, you first need to have the latest version of DAX studio as this feature is not available in the older versions. Open PBIX file II. In order to connect DAX studio to Power BI, open your Power BI file. III. Connect DAX Studio with PBI Report Now open DAX Studio and in Data Source settings select PBI/SSDT Model option. In the dropdown menu, you‘ll be able to see the report you opened in the previous step. Select the desired report from the dropdown. Connect to the report. IV. Exporting Data to SSMS To Analyse Data Using SQL From the main stage, navigate to the toolbar and select the Advanced menu. Select Export Data option. In Export Data Wizard, select SQL Tables. V.

2025-04-04
User1789

Preparing the Power BI reportEvery page in a Power BI report usually creates one or more DAX queries to populate its visuals. . When you switch to a different page, new queries might be sent to the engine. Moreover, changing the selection of a slicer also generates new queries. However, Power BI also uses a cache system to avoid sending the same DAX query multiple times. Therefore, it is useful to make sure that the cache is empty in order to capture all the queries generated for a single page of a report.For example, consider the following report that is made up of a single page.When the report is opened, the DAX queries are immediately generated and sent to the engine. There is not enough time to open DAX Studio and activate the trace to capture all the DAX queries: some of these queries will already be executed.To avoid this problem and to make sure that all the queries can be captured in DAX Studio, the Power BI file should contain an empty page. Thus, you should create a new empty page and save the PBIX file ensuring that it is the current active page of the report.This way, the next time you open the PBIX file, the empty page will be displayed and no queries will be sent to the engine until you click on another page.Once the file is ready, close Power BI Desktop. Then, reopen Power BI Desktop and open the file that you prepared in the previous step. The empty page should appear in the report. The next step involves connecting to Power BI from DAX Studio.Connecting DAX Studio to Power BI to capture queriesKeeping Power BI Desktop open with the empty page selected, open DAX Studio and select the PBI / SSDT Model that is open.Click on the All Queries button in the Traces section of the ribbon.Make sure that you see the message, “Query Trace Started” in the Output pane.Switch to the All Queries result pane. There should be an empty list at this time. You can see that the Start button is not an available option, indicating that the trace is already running.DAX Studio is now ready to capture all the DAX queries generated by Power BI reports.Capturing DAX queries from the active page of your reportKeeping DAX Studio open, switch to the Power BI Desktop window and select the page of the report that displays the data.This simple report generates many queries, which are captured and displayed in the All Queries pane in DAX Studio.The Duration column measures the time spent resolving each query, in milliseconds. If there is a significant discrepancy between the sum of all DAX queries durations and the

2025-04-23
User2992

DAX Query ExplorerThe most powerful and intuitive way to visualize and analyze DAX query execution plans. DAX Query Explorer transforms complex query plans into interactive, visual flowcharts that make understanding query execution simple and efficient.FeaturesInteractive Visualization: Transform text-based DAX query plans into interactive, visual flowchartsFlexible Input Formats: Support for both plain text query plans and JSON format exported from DAX StudioNode Type Differentiation: Distinct visual representations for different operation types:Spool Physical Operations (SpoolPhyOp)Iteration Physical Operations (IterPhyOp)Lookup Physical Operations (LookupPhyOp)Scalar Logical Operations (ScaLogOp)Relational Logical Operations (RelLogOp)Collapsible Nodes: Simplify complex plans by collapsing nodes to focus on specific parts of the executionSmart Layout: Automatic node positioning and edge routing for optimal readabilityPlan Sharing: Share query plans with colleagues via unique URLsResponsive Design: Works seamlessly on both desktop and mobile devicesGetting StartedVisit DAX Query ExplorerPaste your DAX query plan into the editor:Either paste the plain text query planOr paste the JSON output exported from DAX StudioClick "Parse Query Plan" to generate the visual representationExplore the execution plan through the interactive visualizationUsageViewing Query PlansThe interface is split into two main sections:Left: Code editor for inputting DAX query plans (accepts both text and JSON formats)Right: Interactive flowchart visualizationInput FormatsDAX Query Explorer supports two input formats:Plain Text: The standard text output of a DAX query planJSON Format: The JSON export from DAX Studio, containing both physical and logical query plan rowsNode InformationEach node in the visualization contains important information about the operation:Operation type and nameNumber of records processedKey columns and value columnsAdditional operation-specific detailsSharing PlansClick the "Share Plan" button in the top right cornerA unique URL will be generated and copied to your clipboardShare the URL with others to let them view the same query planWhy DAX Query Explorer?Understanding DAX query plans is crucial for optimizing Power BI and Analysis Services performance. DAX Query Explorer makes this process intuitive by:Converting complex text-based plans into clear visual representationsHighlighting relationships between operationsMaking it easy to identify bottlenecks and optimization opportunitiesFacilitating collaboration through plan sharingContributingWe welcome contributions! Please feel free to submit issues and pull requests.

2025-03-29
User8084

I am working to solve mass balance equations for 4 connected chemical process control units for a continuous operation. The resulting one dimensional coupled and (non-coupled) Partial Differential Equations are aimed to be solved using Method of Lines with finite difference method. One process unit includes a coupled PDE. The general form of the equations follows convection – diffusion format (see attached pdf)The code uses the pdepe solver and is attached alongwith, for the following equations (refer pdf attached).The results from both the approaches differ significantly towards the end iterations. Could anyone suggest me what am I missing or any restriction on the solution approach? I am not sure how the second derivative is approximated at the first discrete as well. Thank you for all your help.tspan = linspace(0,20,2000); [T,Y] = ode15s(@(t,y) numericalprimertubular(t,y,x,n),tspan,y0);myCB = Y(:,n+1:(2*n)-10);myCC = Y(:,2*n+1:(3*n)-10);myCD = Y(:,3*n+1:(4*n)-10); Using the pdepe solver for the same examplesol = pdepe(0,@pdex2pde,@pdex2ic,@pdex2bc,z,t); CA = sol(:,:,1); CB = sol(:,:,2); CC = sol(:,:,3); CD = sol(:,:,4);function definitions:function DyDt = numericalprimertubular(t,y,x,n)xhalf(1:n-1)=(x(1:n-1)+x(2:n))/2;DuDx(1) = (u(1)-1)*(vel/Dax); DvDx(1) = (v(1)-1)*(vel/Dax);DcDx(1) = (c(1)-0)*(vel/Dax);DdDx(1) = (d(1)-0)*(vel/Dax);D2uDx2(1) = 1.0/(xhalf(1)-x(1))*(u(2)-u(1))/(x(2)-x(1)); D2vDx2(1) = 1.0/(xhalf(1)-x(1))*(v(2)-v(1))/(x(2)-x(1)); D2cDx2(1) = 1.0/(xhalf(1)-x(1))*(c(2)-c(1))/(x(2)-x(1));D2dDx2(1) = 1.0/(xhalf(1)-x(1))*(d(2)-d(1))/(x(2)-x(1)); DuDx(i) = ((x(i)-x(i-1))/(x(i+1)-x(i))*(u(i+1)-u(i))+(x(i+1)-x(i))/(x(i)-x(i-1))*(u(i)-u(i-1)))/(x(i+1)-x(i-1)); D2uDx2(i) = (xhalf(i)*(u(i+1)-u(i))/(x(i+1)-x(i))-xhalf(i-1)*(u(i)-u(i-1))/(x(i)-x(i-1)))/(xhalf(i)-xhalf(i-1)); DvDx(i) = ((x(i)-x(i-1))/(x(i+1)-x(i))*(v(i+1)-v(i))+(x(i+1)-x(i))/(x(i)-x(i-1))*(v(i)-v(i-1)))/(x(i+1)-x(i-1)); D2vDx2(i) = (xhalf(i)*(v(i+1)-v(i))/(x(i+1)-x(i))-xhalf(i-1)*(v(i)-v(i-1))/(x(i)-x(i-1)))/(xhalf(i)-xhalf(i-1)); DcDx(i) = ((x(i)-x(i-1))/(x(i+1)-x(i))*(c(i+1)-c(i))+(x(i+1)-x(i))/(x(i)-x(i-1))*(c(i)-c(i-1)))/(x(i+1)-x(i-1)); D2cDx2(i) = (xhalf(i)*(c(i+1)-c(i))/(x(i+1)-x(i))-xhalf(i-1)*(c(i)-c(i-1))/(x(i)-x(i-1)))/(xhalf(i)-xhalf(i-1)); DdDx(i) = ((x(i)-x(i-1))/(x(i+1)-x(i))*(d(i+1)-d(i))+(x(i+1)-x(i))/(x(i)-x(i-1))*(d(i)-d(i-1)))/(x(i+1)-x(i-1)); D2dDx2(i) = (xhalf(i)*(d(i+1)-d(i))/(x(i+1)-x(i))-xhalf(i-1)*(d(i)-d(i-1))/(x(i)-x(i-1)))/(xhalf(i)-xhalf(i-1)); DuDt(i) = Dax*D2uDx2(i) - vel*DuDx(i) - k1*u(i)*v(i); DvDt(i) = Dax*D2vDx2(i) - vel*DvDx(i) - k1*u(i)*v(i)-k2*v(i)*c(i); DcDt(i) = Dax*D2cDx2(i) - vel*DcDx(i) + k1*u(i)*v(i) - k2*v(i)*c(i); DdDt(i) = Dax*D2dDx2(i) - vel*DdDx(i) + k2*v(i)*c(i);DyDt = [DuDt;DvDt;DcDt;DdDt];function [c,f,s] = pdex2pde(z,t,C,dCdz)s = [-vz*dCdz(1)-k1*C(1)*C(2);-vz*dCdz(2)-k1*C(1)*C(2)-k2*C(2)*C(3);-vz*dCdz(3)+k1*C(1)*C(2)-k2*C(2)*C(3);-vz*dCdz(4)+ k2*C(2)*C(3)];function [pl,ql,pr,qr] = pdex2bc(zl,Cl,zr,Cr,t)pl = [Cl(1)-Cin(1);Cl(2)-Cin(2);Cl(3)-Cin(3);Cl(4)-Cin(4)];qr = [1/Dz;1/Dz;1/Dz;1/Dz];function C0 = pdex2ic(z); Accepted Answer Edited: Torsten on 13 Jan 2022 For the pdepe version, better usefunction [pl,ql,pr,qr] = pdex2bc(zl,Cl,zr,Cr,t) pl = [Cl(1)-Cin(1);Cl(2)-Cin(2);Cl(3)-Cin(3);Cl(4)-Cin(4)];I adopted the method-of-lines version:tspan = linspace(0,20,2000); [T,Y] = ode15s(@(t,y) numericalprimertubular(t,y,x,n),tspan,y0);plot(x.',[myCA(:,100),myCA(:,500),myCA(:,1000),myCA(:,1500),myCA(:,2000)])plot(x.',[myCB(:,100),myCB(:,500),myCB(:,1000),myCB(:,1500),myCB(:,2000)])plot(x.',[myCC(:,100),myCC(:,500),myCC(:,1000),myCC(:,1500),myCC(:,2000)])plot(x.',[myCD(:,100),myCD(:,500),myCD(:,1000),myCD(:,1500),myCD(:,2000)])function DyDt = numericalprimertubular(t,y,x,n)xhalf(1:n-1)=(x(1:n-1)+x(2:n))/2;DuDx(1) = (u(1)-1)*(vel/Dax); DvDx(1) = (v(1)-1)*(vel/Dax);DcDx(1) = (c(1)-0)*(vel/Dax);DdDx(1) = (d(1)-0)*(vel/Dax);D2uDx2(1) = ((u(2)-u(1))/(x(2)-x(1))-DuDx(1))/((x(2)-x(1))/2);D2vDx2(1) = ((v(2)-v(1))/(x(2)-x(1))-DvDx(1))/((x(2)-x(1))/2);D2cDx2(1) = ((c(2)-c(1))/(x(2)-x(1))-DcDx(1))/((x(2)-x(1))/2);D2dDx2(1) = ((d(2)-d(1))/(x(2)-x(1))-DdDx(1))/((x(2)-x(1))/2); DuDx(i) = (u(i)-u(i-1))/(x(i)-x(i-1)); D2uDx2(i) = (xhalf(i)*(u(i+1)-u(i))/(x(i+1)-x(i))-xhalf(i-1)*(u(i)-u(i-1))/(x(i)-x(i-1)))/(xhalf(i)-xhalf(i-1)); DvDx(i) = (v(i)-v(i-1))/(x(i)-x(i-1)); D2vDx2(i) = (xhalf(i)*(v(i+1)-v(i))/(x(i+1)-x(i))-xhalf(i-1)*(v(i)-v(i-1))/(x(i)-x(i-1)))/(xhalf(i)-xhalf(i-1)); DcDx(i) = (c(i)-c(i-1))/(x(i)-x(i-1)); D2cDx2(i) = (xhalf(i)*(c(i+1)-c(i))/(x(i+1)-x(i))-xhalf(i-1)*(c(i)-c(i-1))/(x(i)-x(i-1)))/(xhalf(i)-xhalf(i-1)); DdDx(i) = (d(i)-d(i-1))/(x(i)-x(i-1)); D2dDx2(i) = (xhalf(i)*(d(i+1)-d(i))/(x(i+1)-x(i))-xhalf(i-1)*(d(i)-d(i-1))/(x(i)-x(i-1)))/(xhalf(i)-xhalf(i-1));D2uDx2(n) = -(u(n)-u(n-1))/(x(n)-x(n-1))/((x(n)-x(n-1))/2);D2vDx2(n) = -(v(n)-v(n-1))/(x(n)-x(n-1))/((x(n)-x(n-1))/2);D2cDx2(n) = -(c(n)-c(n-1))/(x(n)-x(n-1))/((x(n)-x(n-1))/2);D2dDx2(n) = -(d(n)-d(n-1))/(x(n)-x(n-1))/((x(n)-x(n-1))/2); DuDt(i) = Dax*D2uDx2(i) - vel*DuDx(i) - k1*u(i)*v(i); DvDt(i) = Dax*D2vDx2(i) - vel*DvDx(i) - k1*u(i)*v(i) - k2*v(i)*c(i); DcDt(i) = Dax*D2cDx2(i) - vel*DcDx(i) + k1*u(i)*v(i) - k2*v(i)*c(i); DdDt(i) = Dax*D2dDx2(i) - vel*DdDx(i) + k2*v(i)*c(i);DyDt = [DuDt;DvDt;DcDt;DdDt]; More Answers (0) See Also Categories Community Treasure Hunt Find the treasures in MATLAB Central and discover how the community can help you! Start Hunting! An Error Occurred Unable to complete the action because of changes made to the page. Reload the page to see its updated state.

2025-04-22
User9534

Power of DAX to tell compelling narratives. Unleash dynamic drill-through interactions and contextual tooltips that engage users on a personal level. Apply conditional formatting with precision, guiding attention to critical data points. Through intricate design themes, you’ll craft a visual journey that resonates with your audience, enhancing UX and fostering a professional, consistent look and feel.Equip yourself with the expertise to predict outcomes, detect outliers, and structure effective data models that facilitate intuitive insights. Learn to construct analytical solutions that leave an indelible mark on data consumers. We’ll empower you to master matrix conditional formatting, turning your visuals into dynamic storytellers that captivate and enlighten.By the end of “DAX Pro: Advanced Skills for Power BI Users,” you’ll be armed with an arsenal of advanced DAX techniques, seamlessly integrated with design principles that bring your data to life. As you embark on this transformative learning journey, you’ll not only elevate your skills but also your capacity to shape data into a compelling narrative that drives action. Join us and become a DAX Pro, revolutionizing data storytelling and user experience in the world of Power BI.Don’t miss out on this unparalleled opportunity to propel your Power BI skills to new heights. Enroll now and embark on a journey that will redefine the way you approach data, insights, and the art of communication. Course Curriculum Chapter 1: Introduction Lecture 1: Learning Tips From Enterprise DNA Lecture 2: Course Resources Lecture 3: Microsoft Power BI user-interface updates to be aware of Lecture 4: Course Overview – Let's get started! Lecture 5: Power BI: Did you know? Chapter 2: Power BI Analytical Techniques Lecture 1: Advanced Techniques: Interesting Power BI Facts Lecture 2: Segmenting Success: Classification for Targeted Engagement Lecture 3: Detecting Anomalies: Uncover Unusual Patterns in Your Data Lecture 4: Mastering Cluster Analysis for Actionable Intelligence Lecture 5: Spotting Outliers: Enhancing Data Quality through Detection Techniques Lecture 6: Unlocking Opportunities: Exploring Cross-Sell Insights Using Power BI Lecture 7: Enhance Decision-Making with Advanced Pattern Recognition Lecture 8: Advanced Power BI Analytical Techniques – Review Lecture 9: Your Feedback Matters! Lecture 10: Insights to Advanced Power BI Techniques Chapter 3: Deep Dive to Advanced Techniques Lecture 1: Advanced Power BI: Key Facts You Must Know Lecture 2: Predictive Insights:Threshold Triggers & Breaches Lecture 3: Beyond Basics: Unleashing Power with Secondary Table Logic Lecture 4: Mastering Impact: Applying the Pareto Rule to Data Analysis Lecture 5: Strategy: Analyzing Customer Attrition Patterns Lecture 6: Climbing the Ranks: Building Dynamic Ranked Lists with Precision Lecture 7: Deep Dive to Advanced Techniques – Review Lecture 8: Navigating Advanced Power BI Techniques Chapter 4: Advanced DAX Concepts To Master In Power BI Lecture 1: Must Read: Additional Content Lecture 2: Intriguing Facts on Power BI and DAX Techniques Lecture 3: Section Resource Lecture 4: Mastering DAX's Calculate Function Lecture 5: Harnessing Variables and Calculate Table in DAX Lecture 6: Exploring Virtual Tables in DAX Lecture 7: Diving Deeper into Virtual Tables and Top Customers Lecture 8: Harnessing Virtual Tables and TopN

2025-04-07

Add Comment