59 Data Analyst courses delivered Live Online

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.

Get job ready with CompTIA's Data Analysis Certification. Live Classes - Career Guidance - Exam Included.

Duration 4 Days 24 CPD hours This course is intended for This course is designed for data analysts, business intelligence specialists, developers, system architects, and database administrators. Overview Skills gained in this training include:The features that Pig, Hive, and Impala offer for data acquisition, storage, and analysisThe fundamentals of Apache Hadoop and data ETL (extract, transform, load), ingestion, and processing with HadoopHow Pig, Hive, and Impala improve productivity for typical analysis tasksJoining diverse datasets to gain valuable business insightPerforming real-time, complex queries on datasets Cloudera University?s four-day data analyst training course focusing on Apache Pig and Hive and Cloudera Impala will teach you to apply traditional data analytics and business intelligence skills to big data. Hadoop Fundamentals The Motivation for Hadoop Hadoop Overview Data Storage: HDFS Distributed Data Processing: YARN, MapReduce, and Spark Data Processing and Analysis: Pig, Hive, and Impala Data Integration: Sqoop Other Hadoop Data Tools Exercise Scenarios Explanation Introduction to Pig What Is Pig? Pig?s Features Pig Use Cases Interacting with Pig Basic Data Analysis with Pig Pig Latin Syntax Loading Data Simple Data Types Field Definitions Data Output Viewing the Schema Filtering and Sorting Data Commonly-Used Functions Processing Complex Data with Pig Storage Formats Complex/Nested Data Types Grouping Built-In Functions for Complex Data Iterating Grouped Data Multi-Dataset Operations with Pig Techniques for Combining Data Sets Joining Data Sets in Pig Set Operations Splitting Data Sets Pig Troubleshoot & Optimization Troubleshooting Pig Logging Using Hadoop?s Web UI Data Sampling and Debugging Performance Overview Understanding the Execution Plan Tips for Improving the Performance of Your Pig Jobs Introduction to Hive & Impala What Is Hive? What Is Impala? Schema and Data Storage Comparing Hive to Traditional Databases Hive Use Cases Querying with Hive & Impala Databases and Tables Basic Hive and Impala Query Language Syntax Data Types Differences Between Hive and Impala Query Syntax Using Hue to Execute Queries Using the Impala Shell Data Management Data Storage Creating Databases and Tables Loading Data Altering Databases and Tables Simplifying Queries with Views Storing Query Results Data Storage & Performance Partitioning Tables Choosing a File Format Managing Metadata Controlling Access to Data Relational Data Analysis with Hive & Impala Joining Datasets Common Built-In Functions Aggregation and Windowing Working with Impala How Impala Executes Queries Extending Impala with User-Defined Functions Improving Impala Performance Analyzing Text and Complex Data with Hive Complex Values in Hive Using Regular Expressions in Hive Sentiment Analysis and N-Grams Conclusion Hive Optimization Understanding Query Performance Controlling Job Execution Plan Bucketing Indexing Data Extending Hive SerDes Data Transformation with Custom Scripts User-Defined Functions Parameterized Queries Choosing the Best Tool for the Job Comparing MapReduce, Pig, Hive, Impala, and Relational Databases Which to Choose?

OVERVIEW This official Microsoft Power BI training course will teach you how to connect to data from many sources, clean and transform it using Power Query, create a data model consisting of multiple tables connected with relationships and build visualisations and reports to show the patterns in the data. The course will explore formulas created using the DAX language, including the use of advanced date intelligence calculations. Additional visualisation features including interactivity between the elements of a report page are covered as well as parameters and row-level security, which allows a report to be tailored according to who is viewing it. The course will also show how to publish reports and dashboards to a workspace on the Power BI Service. COURSE BENEFITS: Learn how to clean, transform, and load data from many sources Use database queries in Power Query to combine tables using append and merge 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 advanced time calculations using date tables Optimise report calculations using the Performance Analyzer Manage and share report assets to the Power BI Service Prepare for the official Microsoft PL-300 exam using Microsoft Official Courseware WHO IS THE COURSE FOR? Data Analysts with little or no experience of Power BI who wish to upgrade their knowledge to include Business Intelligence Management Consultants who need to conduct rapid analysis of their clients’ data to answer specific business questions Analysts who need to upgrade their organisation from a simple Excel or SQL-based management reporting system to a dynamic BI system Data Analysts who wish to develop organisation-wide reporting in the form of web reports or phone apps Marketers in data-intensive organisations who wish to build visually appealing, dynamic charts for their stakeholders to use COURSE OUTLINE Module 1 Getting Started With Microsoft Data Analytics Data analytics and Microsoft Getting Started with Power BI Module 2 Get Data In Power BI Get data from various data sources Optimize performance Resolve data errors Lab: Prepare Data in Power BI Desktop Module 3 Clean, Transform And Load Data In Power BI Data shaping Data profiling Enhance the data structure Lab: Load Data in Power BI Desktop Module 4 Design A Data Model In Power BI Introduction to data modelling Working with Tables Dimensions and Hierarchies Lab: Model Data in Power BI Desktop Module 5 Create Model Calculations Using DAX In Power BI Introduction to DAX Real-time Dashboards Advanced DAX Lab 1: Create DAX Calculations in Power BI Desktop, Part 1 Lab 2: Create DAX Calculations in Power BI Desktop, Part 2 Module 6 Optimize Model Performance Optimize the data model for performance Optimize DirectQuery models Module 7 Create Reports Design a Report Enhance the Report Lab 1: Design a Report in Power BI Desktop, Part 1 Lab 2: Design a Report in Power BI Desktop, Part 2 Module 8 Create Dashboards Create a Dashboard Real-time Dashboards Enhance a Dashboard Lab: Create a Power BI Dashboard Module 9 Perform Advanced Analytics Advanced analytics Data Insights through AI Visuals Lab: Perform Data Analysis in Power BI Desktop Module 10 Create And Manage Workspaces Creating Workspaces Sharing and managing assets Module 11 Manage Datasets In Power BI Parameters Datasets Module 12 Row-Level Security Security in Power BI Lab: Enforce Row-Level Security

Duration 2 Days 12 CPD hours This course is intended for This course can be valuable for anyone who needs to write basic SQL or Transact-SQL queries. This includes anyone working with data as a data analyst, a data engineer, a data scientist, a database administrator or a database developer. It can also be useful for others peripherally involved with data, or wanting to learn more about working with data such as solution architects, students and technology managers. This course will teach the basics of Microsoft's dialect of the standard SQL language: Transact-SQL. Topics include both querying and modifying data in relational databases that are hosted in Microsoft SQL Server-based database systems, including: Microsoft SQL Server, Azure SQL Database and, Azure Synapse Analytics. 1 - Introduction to Transact-SQL Work with schemas Explore the structure of SQL statements Examine the SELECT statement Work with data types Handle NULLs 2 - Sort and filter results in T-SQL Sort your results Limit the sorted results Page results Remove duplicates Filter data with predicates 3 - Combine multiple tables with JOINs in T-SQL Understand joins concepts and syntax Use inner joins Use outer joins Use cross joins Use self joins 4 - Write Subqueries in T-SQL Understand subqueries Use scalar or multi-valued subqueries Use self-contained or correlated subqueries 5 - Use built-in functions and GROUP BY in Transact-SQL Categorize built-in functions Use scalar functions Use ranking and rowset functions Use aggregate functions Summarize data with GROUP BY Filter groups with HAVING 6 - Modify data with T-SQL Insert data Generate automatic values Update data Delete data Merge data based on multiple tables Additional course details: Nexus Humans DP-080T00 Querying Data with Microsoft Transact-SQL 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 DP-080T00 Querying Data with Microsoft Transact-SQL 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.

Data modelling and visualisation skills are in demand! Create Interactive Reports and Dashboards.

Duration 1 Days 6 CPD hours This course is intended for The primary audience for this course is data professionals who are familiar with data modeling, extraction, and analytics. It is designed for professionals who are interested in gaining knowledge about Lakehouse architecture, the Microsoft Fabric platform, and how to enable end-to-end analytics using these technologies. Job role: Data Analyst, Data Engineer, Data Scientist Overview Describe end-to-end analytics in Microsoft Fabric Describe core features and capabilities of lakehouses in Microsoft Fabric Create a lakehouse Ingest data into files and tables in a lakehouse Query lakehouse tables with SQL Configure Spark in a Microsoft Fabric workspace Identify suitable scenarios for Spark notebooks and Spark jobs Use Spark dataframes to analyze and transform data Use Spark SQL to query data in tables and views Visualize data in a Spark notebook Understand Delta Lake and delta tables in Microsoft Fabric Create and manage delta tables using Spark Use Spark to query and transform data in delta tables Use delta tables with Spark structured streaming Describe Dataflow (Gen2) capabilities in Microsoft Fabric Create Dataflow (Gen2) solutions to ingest and transform data Include a Dataflow (Gen2) in a pipeline This course is designed to build your foundational skills in data engineering on Microsoft Fabric, focusing on the Lakehouse concept. This course will explore the powerful capabilities of Apache Spark for distributed data processing and the essential techniques for efficient data management, versioning, and reliability by working with Delta Lake tables. This course will also explore data ingestion and orchestration using Dataflows Gen2 and Data Factory pipelines. This course includes a combination of lectures and hands-on exercises that will prepare you to work with lakehouses in Microsoft Fabric. Introduction to end-to-end analytics using Microsoft Fabric Explore end-to-end analytics with Microsoft Fabric Data teams and Microsoft Fabric Enable and use Microsoft Fabric Knowledge Check Get started with lakehouses in Microsoft Fabric Explore the Microsoft Fabric Lakehouse Work with Microsoft Fabric Lakehouses Exercise - Create and ingest data with a Microsoft Fabric Lakehouse Use Apache Spark in Microsoft Fabric Prepare to use Apache Spark Run Spark code Work with data in a Spark dataframe Work with data using Spark SQL Visualize data in a Spark notebook Exercise - Analyze data with Apache Spark Work with Delta Lake Tables in Microsoft Fabric Understand Delta Lake Create delta tables Work with delta tables in Spark Use delta tables with streaming data Exercise - Use delta tables in Apache Spark Ingest Data with DataFlows Gen2 in Microsoft Fabric Understand Dataflows (Gen2) in Microsoft Fabric Explore Dataflows (Gen2) in Microsoft Fabric Integrate Dataflows (Gen2) and Pipelines in Microsoft Fabric Exercise - Create and use a Dataflow (Gen2) in Microsoft Fabric

This course will enable you to bring value to the business by putting data science concepts into practice. Data is crucial for understanding where the business is and where it's headed. Not only can data reveal insights, but it can also inform - by guiding decisions and influencing day-to-day operations.

This course shows you how to apply various approaches and algorithms to solve business problems through AI and ML, follow a methodical workflow to develop sound solutions, use open-source, off-the-shelf tools to develop, test, and deploy those solutions, and ensure that they protect the privacy of users. This course includes hands-on activities for each topic area.

OVERVIEW Prerequisites—this is a day of supervised revision for anyone who wishes to take the PL-300 exam so we expect you to have attended a PL-300 course, either taught or on your own, before attending this day of revision. We are happy for attendees to join the course if you have taken the PL-300 with us or with another provider. In the morning we look at questions from the PL-300 exam, grouped by subject area. For each question we show you the correct answer and then explain why that is the correct answer. After lunch everyone tries a practice exam under exam conditions and we finish the day with clarification on the subjects or specific questions that the class is finding hard. The cost of the course includes a free voucher to take the exam, so please don’t buy your own separately. If you do so we cannot reimburse you with the cost of the exam. COURSE BENEFITS: Discover the parts of the course on which to focus most attention Become familiar with the styles and formats of the exam questions Alert yourself to some of the particularly tricky questions Familiarise yourself with the style of the 'case study' question Practice an exam under real exam conditions Get a feel for the time you need to devote to the normal questions and to the case study WHO IS THE COURSE FOR? Power BI report developers who need PL-300 Certification to apply for a job Business Intelligence specialists who wish to enhance their career prospects with a PL-300 Certification Anyone who wishes to maximise their chances of passing the PL-300 Power BI Data Analyst exam COURSE OUTLINE Module 1 Structure Of The Exam Registration for the exam and setup of your workspace The percentage of marks devoted to each subject area Types of questions used in the exam Advised timing for the normal questions and for the case study question Module 2 Individual Exam Question Practice The exam questions are divided into subject areas and for each question… We consider the question and try to answer it We view the answer Where necessary, we look at an in-depth explanation of why that is the correct answer Examine case study questions and how to treat these differently from the normal questions Module 3 Practice Exam Under Exam Conditions Attendees take a practice exam Attendees receive a mark, broken down into subject areas Module 4 Exam Question Practice Focussed On Tricky Areas Together, based on the results of attendees’ exam results we decide which areas on which to focus More practice on individual exam questions using the same style as in Module 2