74 Business Intelligence (BI) courses in Cardiff delivered Live Online

Create Animations Using Flourish Studio Course Overview "Create Animations Using Flourish Studio" is designed to teach learners how to create dynamic, engaging animations using Flourish Studio, a powerful visualisation tool. This course covers everything from understanding the interface to building complex, interactive visualisations that can bring data to life. Through step-by-step instructions, learners will develop the skills necessary to enhance presentations, reports, and projects with professional-quality animations. By the end of the course, participants will be able to confidently use Flourish Studio to create visually compelling animations that are tailored to their specific data and narrative needs. This course is suitable for those looking to boost their visual communication skills and make an impact in data presentation. Course Description This course delves into the various capabilities of Flourish Studio, focusing on both its basic and advanced features. Learners will start by exploring the interface and learning how to work with different templates. The course then covers key areas such as importing and managing data, creating animations, and customising visualisations from scratch. In addition to mastering specific templates, participants will also learn how to craft a compelling data story and explore Flourish's other unique features. By the end of the course, learners will have the knowledge and skills to create engaging animations that effectively communicate data insights. Resources and tips for continued development will also be provided, ensuring that learners can keep building on their newfound expertise. Create Animations Using Flourish Studio Curriculum Module 01: Introduction to Flourish Studio Module 02: Getting Started with Flourish Module 03: Adding and Managing Data in Flourish Templates Module 04: Creating Visualisations in Flourish Studio from Scratch Module 05: More Visualisation Templates in Flourish Studio Module 06: Creating a Story and Other Options Module 07: Other Exciting and Important Features Module 08: Data Visualisation Tips & Resources Module 09: Congratulations (See full curriculum) Who is this course for? Individuals seeking to enhance their data presentation skills. Professionals aiming to improve their visual communication abilities. Beginners with an interest in data visualisation or animation. Anyone involved in creating impactful presentations or reports. Career Path Data Visualisation Specialist Marketing Analyst Data Storyteller Presentation Designer Business Intelligence Analyst Marketing Manager Data Analyst

Diploma in Data Analysis Fundamentals Course Overview The Diploma in Data Analysis Fundamentals provides a comprehensive introduction to the core principles and techniques used in data analysis. Throughout this course, learners will explore various data analysis tools and methods, such as Pareto charts, histograms, and control charts, to gain insights into processes and performance. By focusing on key data analysis skills, including identifying variation and interpreting results, this course empowers learners to use data-driven approaches to improve business processes. Upon completion, learners will have the ability to assess and present data effectively, enabling informed decision-making in a wide range of industries. Course Description This course covers essential topics in data analysis, including the principles of process management, tools for data analysis, and methods to interpret and present performance data. Learners will delve into key techniques such as Pareto charts, histograms, run charts, and control charts, focusing on how to use these tools to identify patterns, variations, and areas for improvement. The course also includes a structured approach to performance measurement and provides exercises to reinforce the theoretical knowledge gained. By the end of the course, learners will be equipped with the skills to analyse data, identify trends, and contribute to process improvement initiatives within their organisations. Diploma in Data Analysis Fundamentals Curriculum Module 01: Introduction Module 02: Agenda and Principles of Process Management Module 03: The Voice of the Process Module 04: Working as One Team for Improvement Module 05: Exercise: The Voice of the Customer Module 06: Tools for Data Analysis Module 07: The Pareto Chart Module 08: The Histogram Module 09: The Run Chart Module 10: Exercise: Presenting Performance Data Module 11: Understanding Variation Module 12: The Control Chart Module 13: Control Chart Example Module 14: Control Chart Special Cases Module 15: Interpreting the Control Chart Module 16: Control Chart Exercise Module 17: Strategies to Deal with Variation Module 18: Using Data to Drive Improvement Module 19: A Structure for Performance Measurement Module 20: Data Analysis Exercise Module 21: Course Project Module 22: Test your Understanding (See full curriculum) Who is this course for? Individuals seeking to enhance their data analysis skills. Professionals aiming to improve decision-making through data insights. Beginners with an interest in process improvement and business analysis. Data enthusiasts looking to build a solid foundation in analysis techniques. Career Path Data Analyst Business Intelligence Analyst Process Improvement Specialist Operations Analyst Quality Control Analyst

Microsoft Power BI Masterclass 2021 Course Overview: The "Microsoft Power BI Masterclass 2021" provides learners with the skills to become proficient in data analysis and visualization using Power BI. This comprehensive course covers the core functionalities of Power BI, from data preparation and transformation to creating impactful reports and dashboards. Learners will gain valuable insights into data modelling, visualisation, and the use of DAX for advanced calculations. By the end of the course, participants will be able to apply their knowledge to real-world projects, improving their ability to communicate data-driven insights effectively. This course is ideal for professionals and beginners who want to leverage Power BI to unlock the potential of their data. Course Description: This masterclass delves into the essential features of Microsoft Power BI, guiding learners through every stage of data analysis. Starting with project setup and data transformation in the Query Editor, the course progresses to advanced topics such as DAX functions and data storytelling. Learners will explore how to build data models, create dashboards, and employ Python in Power BI to enhance their reports. The course also covers Power BI Service for cloud-based analytics, row-level security for data protection, and integrating additional data sources. With a focus on empowering users to communicate insights clearly, the course ensures learners gain the expertise to manage data efficiently, make informed decisions, and stay up to date with evolving tools and features. Microsoft Power BI Masterclass 2021 Curriculum: Module 01: Introduction Module 02: Preparing our Project Module 03: Data Transformation - The Query Editor Module 04: Data Transformation - Advanced Module 05: Creating a Data Model Module 06: Data Visualization Module 07: Power BI & Python Module 08: Storytelling with Data Module 09: DAX - The Essentials Module 10: DAX - The CALCULATE function Module 11: Power BI Service - Power BI Cloud Module 12: Row-Level Security Module 13: More data sources Module 14: Next steps to improve & stay up to date (See full curriculum) Who is this course for? Individuals seeking to enhance their data analysis skills. Professionals aiming to advance their data visualization expertise. Beginners with an interest in data science or business analytics. Business analysts or data professionals looking to upskill in Power BI. Career Path: Data Analyst Business Intelligence Analyst Data Scientist Power BI Developer Reporting Analyst Data Visualisation Expert

SQL for Data Science, Data Analytics and Data Visualization Course Overview: This course offers a comprehensive introduction to SQL, designed for those looking to enhance their skills in data science, data analytics, and data visualisation. Learners will develop the ability to work with SQL databases, efficiently query and manage data, and apply these techniques for data analysis in both SQL Server and Azure Data Studio. By mastering SQL statements, aggregation, filtering, and advanced commands, learners will be equipped with the technical skills required to manage large datasets and extract meaningful insights. The course provides a solid foundation in data structures, user management, and working with multiple tables, culminating in the ability to perform complex data analysis and visualisation tasks. Course Description: This course covers a broad range of topics essential for anyone working with data in a professional capacity. From setting up SQL servers to mastering database management tools like SQL Server Management Studio (SSMS) and SQL Azure Data Studio, the course provides a thorough grounding in SQL. Learners will gain expertise in data structure statements, filtering data, and applying aggregate functions, as well as building complex SQL queries for data analysis. The course also includes instruction on SQL user management, group by statements, and JOINs for multi-table analysis. Key topics such as SQL constraints, views, stored procedures, and database backup and restore are also explored. The course incorporates SQL visualisation tools in Azure Data Studio, empowering learners to visualise data effectively. By the end of the course, learners will be proficient in SQL queries, data manipulation, and using Azure for data analysis. SQL for Data Science, Data Analytics and Data Visualization Curriculum: Module 01: Getting Started Module 02: SQL Server Setting Up Module 03: SQL Azure Data Studio Module 04: SQL Database Basic SSMS Module 05: SQL Statements for DATA Module 06: SQL Data Structure Statements Module 07: SQL User Management Module 08: SQL Statement Basic Module 09: Filtering Data Rows Module 10: Aggregate Functions Module 11: SQL Query Statements Module 12: SQL Group By Statement Module 13: JOINS for Multiple Table Data Analysis Module 14: SQL Constraints Module 15: Views Module 16: Advanced SQL Commands Module 17: SQL Stored Procedures Module 18: Azure Data Studio Visualisation Module 19: Azure Studio SQL for Data Analysis Module 20: Import & Export Data Module 21: Backup and Restore Database (See full curriculum) Who is this course for? Individuals seeking to enhance their data management and analysis skills. Professionals aiming to progress in data science, data analytics, or database administration. Beginners with an interest in data analysis and SQL databases. Anyone looking to gain expertise in SQL for Azure and SQL Server environments. Career Path: Data Analyst Data Scientist Database Administrator SQL Developer Business Intelligence Analyst Data Visualisation Specialist

Duration 3 Days 18 CPD hours This course is intended for The primary audience for this course are System Administrators and System Architects. Overview Explain the architecture in SAP BusinessObjects Business Intelligence platformConfigure SAP BusinessObjects Business Intelligence platformPerform common server management and administrative tasks in SAP BusinessObjects Business Intelligence platform In this course, students learn how to explain the architecture in the SAP BusinessObjects Business Intelligence platform and perform common server management and administrative tasks in the SAP BusinessObjects Business Intelligence platform. SAP BusinessObjects Business Intelligence Platform Describing the SAP BusinessObjects Business Intelligence Platform Describing the SAP BusinessObjects Business Intelligence Platform Architecture Installation of SAP BusinessObjects Business Intelligence Platform Installing SAP BusinessObjects Business Intelligence Platform: Server-Side Installation Installing SAP BusinessObjects Business Intelligence Platform: Client-Side Installation Server Administration and Management Using the Central Management Console (CMC) Using the Central Configuration Manager (CCM) Web Application Servers Management Configuring Web Application Servers Central Management Server (CMS) Database Managing the Central Management Server (CMS) and System Database Configuring Auditing File Repository Server Management Managing the File Repository Server Using the Repository Diagnostic Tool Adaptive Servers Managing the Adaptive Job Server Managing the Adaptive Processing Server Crystal Reports Servers Demonstrating Information Flows in Crystal Reports Configuring Crystal Reports Managing Crystal Reports Servers Web Intelligence Server Managing Web Intelligence Document Schedules Viewing Web Intelligence Documents Configuring a Web Intelligence Processing Server Configuring a Connection Server Dashboard Servers Configuring Dashboard Servers Managing Dashboard Design Servers Explorer Servers Configuring Explorer Servers Managing Information Spaces Event Servers Configuring Event Servers Managing Event Servers SAP BusinessObjects Business Intelligence Platform 4.1 Monitoring Monitoring the SAP BusinessObjects Business Intelligence Platform 4.1 Using the SAP BusinessObjects Business Intelligence Platform 4.1 Monitoring Dashboard Additional course details: Nexus Humans BOE320 SAP BI Platform - Admin Servers (Win) 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 BOE320 SAP BI Platform - Admin Servers (Win) 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.

Duration 4 Days 24 CPD hours This course is intended for The audience for this course should have previous experience with functional or technical focus in Dynamics 365: Finance and Operations Applications. Primarily for those who are aspired to be and new to solution architect role Overview After completing this course, students will be able to: Understand the tasks expected to be completed by the solution architect for Dynamics implementation Complete the solution blueprint artifacts Know where to find technical information to address their customer's questions This course is developed for those aspired to be and new to the solution architect role. This course provides the technical information focusing on application architecture and technical skills to start their journey into this role. This course will not cover the industrial skills and delivery skills required for this role. The Architect Role The solution architect role Manage Interactions with FastTrack Get to know FastTrack Make the most of FastTrack templates Solution Blueprint Solution blueprint definition and components Project governance and timeline Solution architecture and organizational structure Working with business process catalog Define Environments, Tools, and Deployment Strategy Understand environment planning Application lifecycle management and deployment strategy Using LCS and Azure DevOps Determine Data Management Strategy Data management overview Develop data migration strategy Determine Integration and Interfaces Strategies Develop integration strategy Integration options Define Security Architecture Important security aspects Security framework Define security strategy Define Testing Strategy Testing strategy overview Testing planning and execution Define Performance Testing Strategy Prepare for performance topics Utilize performance testing tools Business Intelligence and Reporting Implement business intelligence and reporting Determine Licensing and Support Understand licensing estimation Understand support options Prepare for Go-Live Complete solution blueprint Prepare for go-live Class recap Additional course details: Nexus Humans MB-700T00 Microsoft Dynamics 365: Finance and Operations Apps Solution Architect 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 MB-700T00 Microsoft Dynamics 365: Finance and Operations Apps Solution Architect 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.

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?

Duration 3 Days 18 CPD hours This course is intended for Data Analysts, Business Analysts, Business Intelligence professionals Cloud Data Engineers who will be partnering with Data Analysts to build scalable data solutions on Google Cloud Platform Overview This course teaches students the following skills: Derive insights from data using the analysis and visualization tools on Google Cloud Platform Interactively query datasets using Google BigQuery Load, clean, and transform data at scale Visualize data using Google Data Studio and other third-party platforms Distinguish between exploratory and explanatory analytics and when to use each approach Explore new datasets and uncover hidden insights quickly and effectively Optimizing data models and queries for price and performance Want to know how to query and process petabytes of data in seconds? Curious about data analysis that scales automatically as your data grows? Welcome to the Data Insights course! This four-course accelerated online specialization teaches course participants how to derive insights through data analysis and visualization using the Google Cloud Platform. The courses feature interactive scenarios and hands-on labs where participants explore, mine, load, visualize, and extract insights from diverse Google BigQuery datasets. The courses also cover data loading, querying, schema modeling, optimizing performance, query pricing, and data visualization. This specialization is intended for the following participants: Data Analysts, Business Analysts, Business Intelligence professionals Cloud Data Engineers who will be partnering with Data Analysts to build scalable data solutions on Google Cloud Platform To get the most out of this specialization, we recommend participants have some proficiency with ANSI SQL. Introduction to Data on the Google Cloud Platform Highlight Analytics Challenges Faced by Data Analysts Compare Big Data On-Premises vs on the Cloud Learn from Real-World Use Cases of Companies Transformed through Analytics on the Cloud Navigate Google Cloud Platform Project Basics Lab: Getting started with Google Cloud Platform Big Data Tools Overview Walkthrough Data Analyst Tasks, Challenges, and Introduce Google Cloud Platform Data Tools Demo: Analyze 10 Billion Records with Google BigQuery Explore 9 Fundamental Google BigQuery Features Compare GCP Tools for Analysts, Data Scientists, and Data Engineers Lab: Exploring Datasets with Google BigQuery Exploring your Data with SQL Compare Common Data Exploration Techniques Learn How to Code High Quality Standard SQL Explore Google BigQuery Public Datasets Visualization Preview: Google Data Studio Lab: Troubleshoot Common SQL Errors Google BigQuery Pricing Walkthrough of a BigQuery Job Calculate BigQuery Pricing: Storage, Querying, and Streaming Costs Optimize Queries for Cost Lab: Calculate Google BigQuery Pricing Cleaning and Transforming your Data Examine the 5 Principles of Dataset Integrity Characterize Dataset Shape and Skew Clean and Transform Data using SQL Clean and Transform Data using a new UI: Introducing Cloud Dataprep Lab: Explore and Shape Data with Cloud Dataprep Storing and Exporting Data Compare Permanent vs Temporary Tables Save and Export Query Results Performance Preview: Query Cache Lab: Creating new Permanent Tables Ingesting New Datasets into Google BigQuery Query from External Data Sources Avoid Data Ingesting Pitfalls Ingest New Data into Permanent Tables Discuss Streaming Inserts Lab: Ingesting and Querying New Datasets Data Visualization Overview of Data Visualization Principles Exploratory vs Explanatory Analysis Approaches Demo: Google Data Studio UI Connect Google Data Studio to Google BigQuery Lab: Exploring a Dataset in Google Data Studio Joining and Merging Datasets Merge Historical Data Tables with UNION Introduce Table Wildcards for Easy Merges Review Data Schemas: Linking Data Across Multiple Tables Walkthrough JOIN Examples and Pitfalls Lab: Join and Union Data from Multiple Tables Advanced Functions and Clauses Review SQL Case Statements Introduce Analytical Window Functions Safeguard Data with One-Way Field Encryption Discuss Effective Sub-query and CTE design Compare SQL and Javascript UDFs Lab: Deriving Insights with Advanced SQL Functions Schema Design and Nested Data Structures Compare Google BigQuery vs Traditional RDBMS Data Architecture Normalization vs Denormalization: Performance Tradeoffs Schema Review: The Good, The Bad, and The Ugly Arrays and Nested Data in Google BigQuery Lab: Querying Nested and Repeated Data More Visualization with Google Data Studio Create Case Statements and Calculated Fields Avoid Performance Pitfalls with Cache considerations Share Dashboards and Discuss Data Access considerations Optimizing for Performance Avoid Google BigQuery Performance Pitfalls Prevent Hotspots in your Data Diagnose Performance Issues with the Query Explanation map Lab: Optimizing and Troubleshooting Query Performance Advanced Insights Introducing Cloud Datalab Cloud Datalab Notebooks and Cells Benefits of Cloud Datalab Data Access Compare IAM and BigQuery Dataset Roles Avoid Access Pitfalls Review Members, Roles, Organizations, Account Administration, and Service Accounts

Duration 2 Days 12 CPD hours This course is intended for This course is aimed at anyone currently working with data who is interested in using data visualisation to more effectively communicate their results. Overview At completion, delegates will understand how data visualisations can be best used to communicate actionable insights from data and be competent with the tools required to do it. Visualising data, and analytics results, is one of the most effective ways to achieve this. This course will cover the theory of data visualisation along with practical skills for creating compelling visualisations from data. Course Outline The use of analytics, statistics and data science in business has grown massively in recent years. Harnessing the power of data is opening actionable insights in diverse industries from banking to horse breeding. The companies doing this most successfully understand that using sophisticated analytics approaches to unlock insights from data is only half the job. Communicating these insights to all of the different parts of an organisation is just as important as doing the actual analysis. Visualising data, and analytics results, is one of the most effective ways to achieve this. This course will cover the theory of data visualisation along with practical skills for creating compelling visualisations from data. To attend this course delegates should be competent in the use of data analysis tools such as reporting tools, spreadsheet software or business intelligence tools. The course will explore the following topics through a series of interactive workshop sessions: Fundamentals of data visualisation Data characteristics & dimensions Mapping visual encodings to data dimensions Colour theory Graphical perception & communication Interaction design Visualisation different characteristics of data: trends, comparisons, correlations, maps, networks, hierarchies, text Designing effective dashboards

Duration 3 Days 18 CPD hours This course is intended for The course will likely be attended by SQL Server report creators who are interested in alternative methods of presenting data. Overview After completing this course, students will be able to: ? Perform Power BI desktop data transformation. ? Describe Power BI desktop modelling. ? Create a Power BI desktop visualization. ? Implement the Power BI service. ? Describe how to connect to Excel data. ? Describe how to collaborate with Power BI data. ? Connect directly to data stores. ? Describe the Power BI developer API. ? Describe the Power BI mobile app. The main purpose of the course is to give students a good understanding of data analysis with Power BI. The course includes creating visualizations, the Power BI Service, and the Power BI Mobile App. Introduction to Self-Service BI Solutions Introduction to business intelligence Introduction to data analysis Introduction to data visualization Overview of self-service BI Considerations for self-service BI Microsoft tools for self-service BI Lab : Exploring an Enterprise BI solution Introducing Power BI Power BI The Power BI service Lab : Creating a Power BI dashboard Power BI Using Excel as a data source for Power BI The Power BI data model Using databases as a data source for Power BI The Power BI service Lab : Importing data into Power BI Shaping and Combining Data Power BI desktop queries Shaping data Combining data Lab : Shaping and combining data Modelling data Relationships DAX queries Calculations and measures Lab : Modelling Data Interactive Data Visualizations Creating Power BI reports Managing a Power BI solution Lab : Creating a Power BI report Direct Connectivity Cloud data Connecting to analysis services Lab : Direct Connectivity Developer API The developer API Custom visuals Lab : Using the developer API Power BI mobile app The Power BI mobile app Using the Power BI mobile app Power BI embedded