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OVERVIEW DIAD is a one-day, hands-on workshop for business analysts, covering the breadth of Power BI capabilities. The course focuses on five practical Labs and at the end of the day, attendees will better understand how to: Connect and transform data from a variety of data sources. Define business rules and KPIs. Explore data with powerful interactive visuals. Build stunning reports. Share their dashboards with their team business partners and publish them to the web. The course content is managed by the Power BI engineering team at Microsoft. There is no exam associated with the course. COURSE BENEFITS: Learn how to clean, transform, and load data from various sources Create and manage a data model in Power BI consisting of multiple tables connected with relationships Build Measures and other calculations in the DAX language to plot in reports Manage and share report assets to the Power BI Service WHO IS THE COURSE FOR? Data Analysts and Management Consultants with little or no experience of Power BI who wish to upgrade their knowledge to include Business Intelligence Analysts looking for a quick introduction to Power BI who don’t have the time for the full three day PL-300 course Marketers in data-intensive organisations who need new tools to build visually appealing, dynamic charts for their stakeholders to use LAB OUTLINE Lab 1 Accessing & Preparing The Data Load data from Excel and CSV sources Manipulate the data to prepare it for reporting Prepare tables in Power Query and load them into the data model Lab 2 Data Modelling And Exploration Create a range of different charts Highlight and cross-filter Create new groups and hierarchies Add new measures to the model Lab 3 Data Visualization Add conditional formatting to a report Add logos to a filter Import a custom visual Apply a custom theme Add bookmarks to the report to tell a story Lab 4 Publishing A Report And Creating A Dashboard Create a Workspace in the Power BI Service Publish a report to the Service Create a Dashboard and pin visuals to it Generate and view insights Lab 5 Collaboration Share a Dashboard Access a Dashboard on a Mobile Device

Duration 4 Days 24 CPD hours This course is intended for This course is designed for data scientists with existing knowledge of Python and machine learning frameworks like Scikit-Learn, PyTorch, and Tensorflow, who want to build and operate machine learning solutions in the cloud. Overview Learn how to operate machine learning solutions at cloud scale using Azure Machine Learning. This course teaches you to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring in Microsoft Azure. Learn how to operate machine learning solutions at cloud scale using Azure Machine Learning. This course teaches you to leverage your existing knowledge of Python and machine learning to manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring with Azure Machine Learning and MLflow. Prerequisites Creating cloud resources in Microsoft Azure. Using Python to explore and visualize data. Training and validating machine learning models using common frameworks like Scikit-Learn, PyTorch, and TensorFlow. Working with containers AI-900T00: Microsoft Azure AI Fundamentals is recommended, or the equivalent experience. 1 - Design a data ingestion strategy for machine learning projects Identify your data source and format Choose how to serve data to machine learning workflows Design a data ingestion solution 2 - Design a machine learning model training solution Identify machine learning tasks Choose a service to train a machine learning model Decide between compute options 3 - Design a model deployment solution Understand how model will be consumed Decide on real-time or batch deployment 4 - Design a machine learning operations solution Explore an MLOps architecture Design for monitoring Design for retraining 5 - Explore Azure Machine Learning workspace resources and assets Create an Azure Machine Learning workspace Identify Azure Machine Learning resources Identify Azure Machine Learning assets Train models in the workspace 6 - Explore developer tools for workspace interaction Explore the studio Explore the Python SDK Explore the CLI 7 - Make data available in Azure Machine Learning Understand URIs Create a datastore Create a data asset 8 - Work with compute targets in Azure Machine Learning Choose the appropriate compute target Create and use a compute instance Create and use a compute cluster 9 - Work with environments in Azure Machine Learning Understand environments Explore and use curated environments Create and use custom environments 10 - Find the best classification model with Automated Machine Learning Preprocess data and configure featurization Run an Automated Machine Learning experiment Evaluate and compare models 11 - Track model training in Jupyter notebooks with MLflow Configure MLflow for model tracking in notebooks Train and track models in notebooks 12 - Run a training script as a command job in Azure Machine Learning Convert a notebook to a script Run a script as a command job Use parameters in a command job 13 - Track model training with MLflow in jobs Track metrics with MLflow View metrics and evaluate models 14 - Perform hyperparameter tuning with Azure Machine Learning Define a search space Configure a sampling method Configure early termination Use a sweep job for hyperparameter tuning 15 - Run pipelines in Azure Machine Learning Create components Create a pipeline Run a pipeline job 16 - Register an MLflow model in Azure Machine Learning Log models with MLflow Understand the MLflow model format Register an MLflow model 17 - Create and explore the Responsible AI dashboard for a model in Azure Machine Learning Understand Responsible AI Create the Responsible AI dashboard Evaluate the Responsible AI dashboard 18 - Deploy a model to a managed online endpoint Explore managed online endpoints Deploy your MLflow model to a managed online endpoint Deploy a model to a managed online endpoint Test managed online endpoints 19 - Deploy a model to a batch endpoint Understand and create batch endpoints Deploy your MLflow model to a batch endpoint Deploy a custom model to a batch endpoint Invoke and troubleshoot batch endpoints

Advanced Kibana training course description This training course is aimed at users who already have some experience with Kibana, who are looking to further their knowledge. What will you learn Lens Timelion Maps Custom Visualisations with Vega Canvas Filters and Controls Drilldown and Dashboards KQSL and ElasticQueries Scripted and RunTime Fields Alerts and Alarms Advanced Kibana training course details Who will benefit: Users who already have some experience with Kibana, who are looking to further their knowledge. Prerequisites: None Duration 1 day Advanced Kibana training course contents Topics Lens Visualisation types (tables,bars,charts) Category breakdown Adding multiple metrics Using formulas in metrics Labels Adding reference layer Limitations Visualise Library Timeseries, Metrics Different types of aggregations Maps GeoMapping Heat Maps Using ES index as data source Visualisation, tool tips Custom Visualisations with Vega Introduction to vega scripting Canvas Widgets and Texts Elasticsearch SQL Canvas Expressions Filters and Controls Dropdown filters Ad-hoc filters Searchbar filters Drilldown Dashboards Linking one dashboard to another KQSL and ElasticQueries Bool Query AND/OR Phrase Part match vs keyword search Wildcard search Scripted and RunTime Fields Creating ad-hoc calculated fields using scripts Performance issues Alerts and Alarms Query Based Formatting output Connector types(email,index,teams etc)

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Duration 2 Days 12 CPD hours Overview What is JIRA Software? Managing agile projects using JIRA Software Managing project backlog Managing iterations / sprints Managing releases / versions Managing project components Managing security Managing fields and screens Managing custom issue types Viewing various burn-down/burn-up reports This course introduces students to JIRA Software which is one of the most popular agile project management tool. Agile methods help in accelerating the delivery of initial business value. Continuous planning and feedback ensures that value is maximized throughout the development process. JIRA Software lets you manage project backlog, plan and execute sprints, and manage releases. It also lets you view useful reports, such as, velocity, various burndown / burn-up charts. Navigating JIRA Connecting to JIRA Software JIRA Account System Dashboard Sidebars Global Sidebar Search Help Dashboards Projects Boards Issues Project Sidebar Summary Managing Projects What is a Project? What is a Project (Contd.)? Backlog Sprints Versions / Releases Issues What is Component? Project Name and Key Project Key Format Editing Project Key Caveats Editing Project Key Deleting Project Summary Managing Versions What is Version What is Version (Contd.)? Merging Versions Other Version Options Version Fields What is Version? Summary Managing Issues Issues What are Epics? Epics ? Types Creating a new Epic What is a Story? Creating a Story Story Estimation Tasks Sub-tasks Summary Managing Sprints Sprints What is typically done in Sprint Planning? Velocity Agile Board Sprint Naming Convention Sprint Execution Summary Search & Using JQL Search Search Types JQL JQL Examples Sharing search result Save Search and Reuse in a Board Summary Working with JIRA Dashboards and Reports What is a JIRA Dashboard? Creating a JIRA Dashboard Choosing a Dashboard Layout What is a Gadget? Gadgets Available Out-of-the-box Adding a Gadget to a Dashboard Adding a Gadget to a Dashboard (Example Calendar Gadget) Moving a Gadget Removing a Gadget from a Dashboard Viewing Dashboard as a Wallboard Deleting a Dashboard JIRA Reports Generating a JIRA Report Generating a JIRA Report (Example ? Burndown Chart) Viewing the Burndown Chart Report Categories Available Out-of-the-box Agile Reports Issue Analysis Reports Forecast & Management Reports For further details ? Summary Jira Agile Common Jira Software boards Scrum Agility Kanban Scrum vs. Kanban Scrumban History of Kanban Kanban for software teams Kanban boards Kanban boards (Contd.) Kanban cards The benefits of Kanban Planning flexibility Shortened time cycles Fewer bottlenecks Visual metrics Continuous Delivery Kanban ? Kanban backlog Summary Miscellaneous Issue Features Voting Watching an Issue Adding/Removing Labels Linking Issues Linking Issue (Contd.) Commenting on Issue Attaching a File to an Issue Attaching a File to an Issue (Contd.) Cloning (Copying) an Issue Cloning (Copying) an Issue (Contd.) Cloning (copying) an Issue (Contd.) Viewing an Issue?s Change History Viewing an Issue's Change History (Contd. Summary Managing Fields & Screens (OPTIONAL: TIME PERMITTING) Fields OOB Fields Custom Fields Field Type Screens Summary

Duration 2 Days 12 CPD hours Overview Identify and configure basic functions of Tableau. Connect to data sources, import data into Tableau, and save Tableau files Create views and customize data in visualizations. Manage, sort, and group data. Save and share data sources and workbooks. Filter data in views. Customize visualizations with annotations, highlights, and advanced features. Create and enhance dashboards in Tableau. Create and enhance stories in Tableau As technology progresses and becomes more interwoven with our businesses and lives, more and more data is collected about business and personal activities. This era of "big data" has exploded due to the rise of cloud computing, which provides an abundance of computational power and storage, allowing organizations of all sorts to capture and store data. Leveraging that data effectively can provide timely insights and competitive advantage. The creation of data-backed visualizations is a key way data scientists, or any professional, can explore, analyze, and report insights and trends from data. Tableau© software is designed for this purpose. Tableau was built to connect to a wide range of data sources and allows users to quickly create visualizations of connected data to gain insights, show trends, and create reports. Tableau's data connection capabilities and visualization features go far beyond those that can be found in spreadsheets, allowing users to create compelling and interactive worksheets, dashboards, and stories that bring data to life and turn data into thoughtful action. Prerequisites To ensure your success in this course, you should have experience managing data with Microsoft© Excel© or Google Sheets?. Lesson 1: Tableau Fundamentals Topic A: Overview of Tableau Topic B: Navigate and Configure Tableau Lesson 2: Connecting to and Preparing Data Topic A: Connect to Data Topic B: Build a Data Model Topic C: Save Workbook Files Topic D: Prepare Data for Analysis Lesson 3: Exploring Data Topic A: Create Views Topic B: Customize Data in Visualizations Lesson 4: Managing, Sorting, and Grouping Data Topic A: Adjust Fields Topic B: Sort Data Topic C: Group Data Lesson 5: Saving, Publishing, and Sharing Data Topic A: Save Data Sources Topic B: Publish Data Sources and Visualizations Topic C: Share Workbooks for Collaboration Lesson 6: Filtering Data Topic A: Configure Worksheet Filters Topic B: Apply Advanced Filter Options Topic C: Create Interactive Filters Lesson 7: Customizing Visualizations Topic A: Format and Annotate Views Topic B: Emphasize Data in Visualizations Topic C: Create Animated Workbooks Topic D: Best Practices for Visual Design Lesson 8: Creating Dashboards in Tableau Topic A: Create Dashboards Topic B: Enhance Dashboards with Actions Topic C: Create Mobile Dashboards Lesson 9: Creating Stories in Tableau Topic A: Create Stories Topic B: Enhance Stories with Tooltips

Product Management is the strategic nerve centre of successful business ventures. This course explores the full lifecycle of product development — from idea to execution — focusing on how to manage teams, define priorities, and align offerings with business goals. It blends insight, structure, and decision-making logic into a streamlined learning experience that speaks to aspiring and current professionals looking to shape market-ready products with clarity and intent. Without dipping into gimmicks, this course covers the fine art of keeping things simple while moving projects forward in fast-paced environments. Whether you're defining features or navigating shifting demands, you'll get to know how great product managers think, communicate, and keep calm under pressure — all with a dash of logic, some solid frameworks, and the occasional well-placed spreadsheet. Our Product Management course includes modules on: Product Classification Product Plan Product Life Cycle Pricing Strategy Brand Portfolio Analysis So if you're ready to get a head start in your Product Management career, enrol in this updated course. Meet the Endorsement The Quality Licence Scheme has been designed specifically to recognise high-quality courses. This Product Management course materials are recognised by Quality Licence Scheme (QLS). This ensures the deep research and quality resource allocation behind the development phase of the course. In addition, the QLS certificate enriches your CV and recognises your quality study on the relevant subject. Meet the Accreditation CPD Quality Standards (CPD QS) accreditation assure the Product Management course training and learning activities are relevant, reliable, and upto date. Expert Support Dedicated tutor support and 24/7 customer support are available to all students with this premium quality course. Key Benefits Learning materials of the Design course contain engaging voiceover and visual elements for your comfort. Get 24/7 access to all content for a full year. Each of our students gets full tutor support on weekdays (Monday to Friday) This 10-module Product Management course includes a range of audio, guides, resources, and quizzes to help you kick-start your career. Course Curriculum: Module 01: Introduction to Product Management In this module, you will learn the importance and impact of product management. You will also get informed about the job responsibilities of a product manager. Module 02: Product Classification Products are organised for a variety of purposes which are known as classification. In this module, you will learn the classification of products. You will learn about the product categories and their subcategories. Module 03: Developing the Product Plan In this module, you will learn the steps of developing a plan for product management. We will also give you insightful ideas about creating an effective planning process. Module 04: New Product Development In this module, you will learn all the activities for developing a new product. We will also give you ideas about prototype testing before launching a new product. Module 05: Levels of a Product and Product Life Cycle In this module, you will learn the different levels of a product. We will introduce you to different stages of a product life cycle. Module 06: Product Pricing Strategy This module will teach you the effective strategy and tactics needed for setting product prices. We will also give you ideas that work on how you can initiate price changes. Module 07: Product and Brand Portfolio Analysis In this module, you will learn the process of brand equity management. We will also elaborate on the advantages of brand building. Module 08: Channels Management In this module, you will learn the process of Channel management. We will also introduce different types of channels to you. Module 09: Basics of Marketing for Products In this module, you will learn about the marketing mix for your products. Also, we will elaborate on the four core Ps and three additional Ps of the marketing mix. Module 10: Financial Analysis for Product Management In this module, you will learn the process of necessary financial calculations for product management. We will also delve deep and provide insightful information for effective sales and profitability analysis. Course Assessment To simplify the procedure of evaluation and accreditation for learners, we provide an automated assessment system. Upon completion of an online module, you will immediately be given access to a specifically crafted MCQ test. The results will be evaluated instantly, and the score will be displayed for your perusal. For each test, the pass mark will be set to 60%. When all tests have been successfully passed, you will be able to order a certificate endorsed by the Quality Licence Scheme. Certificate of Achievement Endorsed Certificate of Achievement from the Quality Licence Scheme After successfully completing the Product Management course, learners will be able to order an endorsed certificate as proof of their achievement. Hardcopy of this certificate of achievement endorsed by the Quality Licence Scheme can be ordered and received straight to your home by post, by paying Within the UK: £69 International: £69 + £10 (postal charge) = £79 CPD Accredited Certification from One Education After successfully completing this Product Management course, you will qualify for the CPD accredited certificate from One Education. Certification is available in both PDF & hardcopy format, which can be received by paying - PDF Certificate: £9 Hardcopy Certificate (within the UK): £15 Hardcopy Certificate (international): £15 + £10 (postal charge) = £25 CPD 120 CPD hours / points Accredited by CPD Quality Standards Who is this course for? This Product Management course is designed to enhance your expertise and boost your CV. Learn key skills and gain a certificate of achievement to prove your newly-acquired knowledge. Requirements No formal requirements -anyone interested to learn about Product Management can enrol and start learning. Career path This Product Management course certificate will enrich your CV and increase your probability of getting hired or promoted. This course will help you to pursue a career in Project Management Digital Project Management Construction Management Process Engineering Product Development Program Management

Business Intelligence: In-House Training Business Intelligence (BI) refers to a set of technology-based techniques, applications, and practices used to aggregate, analyze, and present business data. BI practices provide historical and current views of vast amounts of data and generate predictions for business operations. The purpose of Business Intelligence is the support of better business decision making. This course provides an overview of the technology and application of BI and how it can be used to improve corporate performance. What you will Learn You will learn how to: Specify a data warehouse schema Identify the data and visualization to be used for data mining and Business Intelligence Design a Business Intelligence user interface Getting Started Introductions Agenda Expectations Foundation Concepts The challenge of decision making What is Business Intelligence? The Business Intelligence value proposition Business Intelligence taxonomy Business Intelligence management issues Sources of Business Intelligence Data warehousing Data and information Information architecture Defining the data warehouse and its relationships Facts and dimensions Modeling, meta-modeling, and schemas Alternate architectures Building the data warehouse Extracting Transforming Loading Setting up the data and relationships Dimensions and the Fact Table Implementing many-to-many relationships in data warehouse Data marts Online Analytical Processing (OLAP) What is OLAP? OLAP and OLTP OLAP functionality Multi-dimensions Thinking in more than two dimensions What are the possibilities? OLAP architecture Cubism Tools OLAP variations - MOLAP, ROLAP, HOLAP BI using SOA Applications of Business Intelligence Applying BI through OLAP Enterprise Resource Planning and CRM Business Intelligence and financial information Business Intelligence User Interfaces and Presentations Data access Push-pull data access Types of decision support systems Designing the front end Presentation formats Dashboards Types of dashboards Common dashboard features Briefing books and scorecards Querying and Reporting Reporting emphasis Retrofitting Talking back Key Performance Indicators Report Definition and Visualization Typical reporting environment Forms of visualization Unconstrained views Data mining What is in the mine? Applications for data mining Data mining architecture Cross Industry Standard Process for Data Mining (CISP-DM) Data mining techniques Validation The Business Intelligence User Experience The business analyst role Business analysis and data analysis Five-step approach Cultural impact Identifying questions Gathering information Understand the goals The strategic Business Intelligence cycle Focus of Business Intelligence Design for the user Iterate the access Iterative solution development process Review and validation questions Basic approaches Building ad-hoc queries Building on-demand self-service reports Closed loop Business Intelligence Coming attractions - future of Business Intelligence Best practices in Business Intelligence

Business Intelligence Business Intelligence (BI) refers to a set of technology-based techniques, applications, and practices used to aggregate, analyze, and present business data. BI practices provide historical and current views of vast amounts of data and generate predictions for business operations. The purpose of Business Intelligence is the support of better business decision making. This course provides an overview of the technology and application of BI and how it can be used to improve corporate performance. What you will Learn You will learn how to: Specify a data warehouse schema Identify the data and visualization to be used for data mining and Business Intelligence Design a Business Intelligence user interface Getting Started Introductions Agenda Expectations Foundation Concepts The challenge of decision making What is Business Intelligence? The Business Intelligence value proposition Business Intelligence taxonomy Business Intelligence management issues Sources of Business Intelligence Data warehousing Data and information Information architecture Defining the data warehouse and its relationships Facts and dimensions Modeling, meta-modeling, and schemas Alternate architectures Building the data warehouse Extracting Transforming Loading Setting up the data and relationships Dimensions and the Fact Table Implementing many-to-many relationships in data warehouse Data marts Online Analytical Processing (OLAP) What is OLAP? OLAP and OLTP OLAP functionality Multi-dimensions Thinking in more than two dimensions What are the possibilities? OLAP architecture Cubism Tools OLAP variations - MOLAP, ROLAP, HOLAP BI using SOA Applications of Business Intelligence Applying BI through OLAP Enterprise Resource Planning and CRM Business Intelligence and financial information Business Intelligence User Interfaces and Presentations Data access Push-pull data access Types of decision support systems Designing the front end Presentation formats Dashboards Types of dashboards Common dashboard features Briefing books and scorecards Querying and Reporting Reporting emphasis Retrofitting Talking back Key Performance Indicators Report Definition and Visualization Typical reporting environment Forms of visualization Unconstrained views Data mining What is in the mine? Applications for data mining Data mining architecture Cross Industry Standard Process for Data Mining (CISP-DM) Data mining techniques Validation The Business Intelligence User Experience The business analyst role Business analysis and data analysis Five-step approach Cultural impact Identifying questions Gathering information Understand the goals The strategic Business Intelligence cycle Focus of Business Intelligence Design for the user Iterate the access Iterative solution development process Review and validation questions Basic approaches Building ad-hoc queries Building on-demand self-service reports Closed loop Business Intelligence Coming attractions - future of Business Intelligence Best practices in Business Intelligence

Duration 1 Days 6 CPD hours This course is intended for Candidates for this exam are users who aspire to improve productivity by automating business processes, analyzing data to produce business insights, and acting more effectively by creating simple app experiences. Overview After completing this course, you will be able to: Describe Microsoft Power Platform components Describe Microsoft Dataverse and connectors Describe cross-cloud scenarios across M365, Dynamics 365, Microsoft Azure and 3rd party services Identify benefits and capabilities of Microsoft Power Platform Identify the basic functionality and business value Microsoft Power Platform components Implement simple solutions with Power Apps, Power Automate, and Power BI Learn the business value and product capabilities of Microsoft Power Platform. Create simple Power Apps, connect data with Dataverse, build a Power BI Dashboard, and automate processes with Power Automate. Module 1: Introduction to Microsoft Power Platform Identify when to use each Microsoft Power Platform component application to create business solution Learn the value of using Microsoft Power Platform to create business solutions Learn the components and features of Microsoft Power Platform Module 2: Introduction to Microsoft Dataverse Microsoft Dataverse Overview Module 3: Get Started with Power Apps Introduction to Power Apps How to build a canvas app How to build a model-driven app Module 4: Get Started with Power Automate Power Automate Overview How to Build an Automated Solution Module 5: Get Started with Power BI Power BI Overview How to Build a Simple Dashboard Module 6: Introduction to Power Virtual Agents Power Virtual Agents overview Additional course details: Nexus Humans PL-900T00 Microsoft Power Platform Fundamentals training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward. This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts. Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success. While we feel this is the best course for the PL-900T00 Microsoft Power Platform Fundamentals course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you. Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.