INTRODUCTION In the ever-evolving world of mobile and web development, a visually appealing and functional landing page plays a pivotal role in capturing user attention. Flutter, Google’s UI toolkit, empowers…
Read MoreINTRODUCTION In the world of modern web development, creating reusable, modular components are key to building scalable and maintainable applications. Angular’s Standalone Components are a game-changer, empowering developers to build…
Read More1.Introduction Hugging Face provides a repository of numerous pretrained models for various use cases, which are open source. It functions similarly to GitHub, allowing users to access and use these…
Read More1.Introduction In OutSystems, handling document text extraction is not available as a built-in feature. Developers often need to process PDF, DOCX, and TXT files to extract text content for indexing,…
Read MoreGetting Started with ALM Toolkit for Power BI INTRODUCTION There are several ways to replace the flooring in your kitchen, but if you were on a budget and had to choose between modifying the existing kitchen floor or building an entirely new house, the only difference being the kitchen floor, you would probably choose the first option. When making changes to a Power BI Dataset, you can have a similar experience. When making changes to large, complex datasets, you can either republish entire Datasets or modify the existing dataset and push only the differences up to the Power BI Service. In this blog, we will explore a tool called ALM Toolkit that makes this possible. We will cover what ALM Toolkit does, why it’s important for shared datasets, and how to use it to make changes to your Power BI Datasets. The ALM Toolkit (Application Lifecycle Management Toolkit) is a popular external tool designed to assist Power BI users with the management and deployment of datasets, particularly in scenarios that involve version control, comparing datasets, and merging changes. It’s widely used in scenarios where complex Power BI models require continuous updates, and teams need a robust method for tracking changes and automating deployment processes. Key features of the ALM Toolkit include: Dataset Comparison: It allows users to compare two Power BI datasets or models. This is particularly useful in development and production environments, where you want to ensure changes between different versions of datasets are accurately reflected. Schema and Model Deployment: ALM Toolkit provides the ability to deploy model changes from one environment (such as development) to another (like production). You can selectively apply schema changes, avoiding the need to redeploy entire datasets. Version Control Integration: By integrating with source control platforms like Azure DevOps and Git, it helps track and manage changes over time, making collaboration easier in team-based development environments. Merging Changes: In scenarios where multiple developers are working on the same Power BI model, ALM Toolkit facilitates the merging of their changes, ensuring no loss of work or conflicting updates. Advanced Scripting Support: It offers support for advanced scripting, which can help automate repetitive tasks such as deployments or version control. Handling Power BI Premium Features: It works well with Power BI Premium and Power BI Embedded, particularly for larger datasets and more complex models, ensuring smooth handling of advanced features. It’s a useful tool for managing Power BI projects, especially when working with deployment pipelines and multiple environments, making it easier to handle model lifecycle, development, and changes efficiently. Why we need to do / Cause of the issue ALM Toolkit for Power BI is a third-party tool that modifies the model files for Power BI Datasets, Template, and BIM files and allows for changes to be made to existing Datasets published in Power BI Service on Premium or Premium Per User (PPU) workspaces. This means transferring the model and data from your desktop to Power BI Service. You can update the model and kick off a refresh in Power BI Service, meaning less attended time, less watching to make sure your large datasets publish to Power BI Service, less strain on your PC, and moving on to the next task a few minutes quicker. This is especially important when working with enterprise datasets and Power BI Deployment Pipelines. These large datasets can take 10 minutes or more to deploy with Power BI Desktop, but ALM Toolkit can merge changes in under a minute using the same dataset, all while having minimal strains on your PC memory and CPU. How do we solve To get started with ALM Toolkit for Power BI, you will need the following: ALM Toolkit for Power BI – available for free here Power BI Desktop 1. A Power BI Pro License and a Workspace…
Read MorePlease use the below query to generate the script and run accordingly. Public Synonym: ——————– select ‘create or replace public synonym ‘||table_name||’ for ‘||owner||’.’||table_name||’;’ from dba_tables where owner=’QA’; …
Read MorePlease run the below and do the export again. create index SYS.IMPDP_STATS_1 ON SYS.IMPDP_STATS (c5,type,c1,c2,c3,c4,statid,version);
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Read MoreFixing Node Not Ready in Kubernetes Introduction/Issue: One day, while working on our Kubernetes cluster, we noticed that one of the nodes went into a NotReady state. This caused some…
Read MoreIntroduction: – User experience (UX) plays a crucial role in modern web applications. A smooth and intuitive interface keeps users engaged and improves usability. One common challenge in Oracle APEX…
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