1099 Courses

Duration 2 Days 12 CPD hours This course is intended for This course is intended for business users who have been using Power BI to build analytic solutions and are ready to take advantage of the power and flexibility that DAX provides. Learning DAX is a very common 'next step' for experienced Power BI users. Overview At course completion, you should be able to describe DAX syntax, data types, and errors use DAX to create calculated columns, measures, and tables explain how DAX calculations are evaluated, along with the differences between row context and filter context configure and use Time Intelligence to perform common time-based calculations, for example to-date calculations, year-over-year analysis, moving averages, etc. create calculated columns and measures that use data from multiple tables in the data model write measures that handle error conditions gracefully use DAX to enhance the Power BI user experience use DAX Studio to connect to a Power BI data model and execute simple queries Welcome to Introduction to DAX for Power BI. This two-day instructor-led course is intended for business users who have been using Power BI and want to use DAX to create custom calculations in their data models. In this class, you will be introduced to using Data Analysis Expressions (DAX), which is the expression language that is used to create custom calculations in the Power BI Data model. The course covers some of the theoretical underpinnings of the data model and the DAX language, but the emphasis is on using DAX to solve common business problems. You will learn how to write your own calculated columns, measures, and tables, how to visualize the way Power BI computes DAX calculations, and how to troubleshoot custom code. MODULE 1: GETTING STARTED WITH DAX INTRODUCTION TODAX CREATING OBJECTS WITHDAX CONTEXT AND RULES OF EVALUATION VARIABLES,COMMENTS,AND TESTING MODULE 2: PERFORMING BASIC CALCULATIONS GETTING STARTED IMPLICIT MEASURES ADDING QUICK MEASURES WORKING WITH DAX DATA TYPES . DOING BASIC MATH USING LOGIC IN YOUR CALCULATIONS USING THE IF() FUNCTION NESTED IF() USING THE SWITCH() FUNCTION ADVANCED SWITCH() LOGICAL OPERATORS & FUNCTIONS: ||, OR(), &&, AND(), NOT() AGGREGATING AND SUMMARIZING DATA THE SUM() FUNCTION MODULE 3: WORKING WITH CONTEXT IN THE DATA MODEL CONTEXT DEFINED DATA MODELING BASICS INTRODUCTION TO DIMENSIONAL MODELING RELATIONSHIPS AND THEIR EFFECT ON THE EVALUATION CONTEXT GETTING DATA FROM OTHER TABLES USING RELATED() AND RELATEDTABLE LOOKING UP DATA WITHOUT USING RELATIONSHIPS MODIFYING THE CONTEXT USING CALCULATE() MODULE 4: PERFORMING MORE ADVANCED CALCULATIONS THE DAX ITERATOR FUNCTIONS USING TABLE MANIPULATION FUNCTIONS MODULE 5: WORKING WITH TIME PERFORMING DATE CALCULATIONS WORKING WITH DATE TABLES GENERATING A DATE TABLE WITH THE CALENDAR() FUNCTION DEFINING CUSTOM OPERATING PERIODS YTD, QTD, AND MTD CALCULATIONS CUSTOM TO-DATE CALCULATIONS FINDING YEAR-OVER-YEAR CHANGE FINDING MOVING AVERAGES MODULE 6: ENHANCING THE USER EXPERIENCE CONTROLLING VISIBILITYOF YOUR MEASURES USING WHAT-IF PARAMETERS ADDING BANDING USING DAX TO PROVIDE ROW-LEVEL SECURITY

Duration 3 Days 18 CPD hours This course is intended for The audience for this course are data professionals and business intelligence professionals who want to learn how to accurately perform data analysis using Power BI. This course is also targeted toward those individuals who develop reports that visualize data from the data platform technologies that exist on both in the cloud and on-premises. This course covers the various methods and best practices that are in line with business and technical requirements for modeling, visualizing, and analyzing data with Power BI. The course will show how to access and process data from a range of data sources including both relational and non-relational sources. Finally, this course will also discuss how to manage and deploy reports and dashboards for sharing and content distribution. Prerequisites Understanding core data concepts. Knowledge of working with relational data in the cloud. Knowledge of working with non-relational data in the cloud. Knowledge of data analysis and visualization concepts. DP-900T00 Microsoft Azure Data Fundamentals is recommended 1 - Discover data analysis Overview of data analysis Roles in data Tasks of a data analyst 2 - Get started building with Power BI Use Power BI Building blocks of Power BI Tour and use the Power BI service 3 - Get data in Power BI Get data from files Get data from relational data sources Create dynamic reports with parameters Get data from a NoSQL database Get data from online services Select a storage mode Get data from Azure Analysis Services Fix performance issues Resolve data import errors 4 - Clean, transform, and load data in Power BI Shape the initial data Simplify the data structure Evaluate and change column data types Combine multiple tables into a single table Profile data in Power BI Use Advanced Editor to modify M code 5 - Design a semantic model in Power BI Work with tables Create a date table Work with dimensions Define data granularity Work with relationships and cardinality Resolve modeling challenges 6 - Add measures to Power BI Desktop models Create simple measures Create compound measures Create quick measures Compare calculated columns with measures 7 - Add calculated tables and columns to Power BI Desktop models Create calculated columns Learn about row context Choose a technique to add a column 8 - Use DAX time intelligence functions in Power BI Desktop models Use DAX time intelligence functions Additional time intelligence calculations 9 - Optimize a model for performance in Power BI Review performance of measures, relationships, and visuals Use variables to improve performance and troubleshooting Reduce cardinality Optimize DirectQuery models with table level storage Create and manage aggregations 10 - Design Power BI reports Design the analytical report layout Design visually appealing reports Report objects Select report visuals Select report visuals to suit the report layout Format and configure visualizations Work with key performance indicators 11 - Configure Power BI report filters Apply filters to the report structure Apply filters with slicers Design reports with advanced filtering techniques Consumption-time filtering Select report filter techniques Case study - Configure report filters based on feedback 12 - Enhance Power BI report designs for the user experience Design reports to show details Design reports to highlight values Design reports that behave like apps Work with bookmarks Design reports for navigation Work with visual headers Design reports with built-in assistance Tune report performance Optimize reports for mobile use 13 - Perform analytics in Power BI Explore statistical summary Identify outliers with Power BI visuals Group and bin data for analysis Apply clustering techniques Conduct time series analysis Use the Analyze feature Create what-if parameters Use specialized visuals 14 - Create and manage workspaces in Power BI Distribute a report or dashboard Monitor usage and performance Recommend a development life cycle strategy Troubleshoot data by viewing its lineage Configure data protection 15 - Manage semantic models in Power BI Use a Power BI gateway to connect to on-premises data sources Configure a semantic model scheduled refresh Configure incremental refresh settings Manage and promote semantic models Troubleshoot service connectivity Boost performance with query caching (Premium) 16 - Create dashboards in Power BI Configure data alerts Explore data by asking questions Review Quick insights Add a dashboard theme Pin a live report page to a dashboard Configure a real-time dashboard Set mobile view 17 - Implement row-level security Configure row-level security with the static method Configure row-level security with the dynamic method Additional course details: Nexus Humans PL-300T00: Microsoft Power BI Data Analyst 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-300T00: Microsoft Power BI Data Analyst 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.

This week long CPD accredited training is ideal for those Real Estate professionals, who are looking to bolster the DCF modelling skills. This course covers Real Estate Investment, Development, Finance & Risk.

The Real Estate Analyst course has been taught non-stop to global real estate firms over the last 25 years, and is without doubt the core financial modelling training in your career portfolio. Whether you have an upcoming financial modelling test for a new job or an APC exam, the Real Estate Analyst course is the choice for you.

This course covers the essential Excel data skills. Our course is interactive, instructor-led. This Excel Data course is on offered on intermediate level of Excel and concentrates on the Data Analytical capabilities of Excel. These concepts are daily used by data analysts and is a basic essential skill for data professionals. By the end, you'll be able to use Excel for analytics, data summaries, trends and statistics. You will create Excel data analytical spreadsheets and samples that you can use as examples at work.

Python Data Analytics with Python using Numpy, Pandas, Dataframes. Most attendees are in-work Data Professional. Private individuals are very welcome. Our Style: Hands-on, Practical Location: Online, Instructor-led

The Real Estate Investor course primarily focuses on financial modelling and commercial considerations in the real estate industry across various sectors, geographies, and project types.

Data analysis translates numbers and data into information that can be used to solve problems or track business performance. Data analysis produces graphs, charts, tables and reports. Data analysis is in high demand across all sectors, such as finance, consulting, manufacturing, pharmaceuticals, government and education. The ability to pay attention to detail, communicate well and be highly organised are essential skills for data analysts. They not only need to understand the data but be able to provide insight and analysis through clear visual, written and verbal communication. This course provides the knowledge and skills to help you hone your data analysis skills.

Python Data Analytics boot camp. 12 1 day lessons, learn Python Basics through to machine learning and front-ends. With practical project to give you full confidence and credibility.

Join us this November for a FREE in-person workshop in Braintree, which introduces SMEs to a variety of AI tools useful for improving business processes!