144 Courses in Cardiff delivered Live Online

Duration 3 Days 18 CPD hours This course is intended for This course is intended for: Database architects Database administrators Database developers Data analysts and scientists Overview This course is designed to teach you how to: Discuss the core concepts of data warehousing, and the intersection between data warehousing and big data solutions Launch an Amazon Redshift cluster and use the components, features, and functionality to implement a data warehouse in the cloud Use other AWS data and analytic services, such as Amazon DynamoDB, Amazon EMR, Amazon Kinesis, and Amazon S3, to contribute to the data warehousing solution Architect the data warehouse Identify performance issues, optimize queries, and tune the database for better performance Use Amazon Redshift Spectrum to analyze data directly from an Amazon S3 bucket Use Amazon QuickSight to perform data analysis and visualization tasks against the data warehouse Data Warehousing on AWS introduces you to concepts, strategies, and best practices for designing a cloud-based data warehousing solution using Amazon Redshift, the petabyte-scale data warehouse in AWS. This course demonstrates how to collect, store, and prepare data for the data warehouse by using other AWS services such as Amazon DynamoDB, Amazon EMR, Amazon Kinesis, and Amazon S3. Additionally, this course demonstrates how to use Amazon QuickSight to perform analysis on your data Module 1: Introduction to Data Warehousing Relational databases Data warehousing concepts The intersection of data warehousing and big data Overview of data management in AWS Hands-on lab 1: Introduction to Amazon Redshift Module 2: Introduction to Amazon Redshift Conceptual overview Real-world use cases Hands-on lab 2: Launching an Amazon Redshift cluster Module 3: Launching clusters Building the cluster Connecting to the cluster Controlling access Database security Load data Hands-on lab 3: Optimizing database schemas Module 4: Designing the database schema Schemas and data types Columnar compression Data distribution styles Data sorting methods Module 5: Identifying data sources Data sources overview Amazon S3 Amazon DynamoDB Amazon EMR Amazon Kinesis Data Firehose AWS Lambda Database Loader for Amazon Redshift Hands-on lab 4: Loading real-time data into an Amazon Redshift database Module 6: Loading data Preparing Data Loading data using COPY Data Warehousing on AWS AWS Classroom Training Concurrent write operations Troubleshooting load issues Hands-on lab 5: Loading data with the COPY command Module 7: Writing queries and tuning for performance Amazon Redshift SQL User-Defined Functions (UDFs) Factors that affect query performance The EXPLAIN command and query plans Workload Management (WLM) Hands-on lab 6: Configuring workload management Module 8: Amazon Redshift Spectrum Amazon Redshift Spectrum Configuring data for Amazon Redshift Spectrum Amazon Redshift Spectrum Queries Hands-on lab 7: Using Amazon Redshift Spectrum Module 9: Maintaining clusters Audit logging Performance monitoring Events and notifications Lab 8: Auditing and monitoring clusters Resizing clusters Backing up and restoring clusters Resource tagging and limits and constraints Hands-on lab 9: Backing up, restoring and resizing clusters Module 10: Analyzing and visualizing data Power of visualizations Building dashboards Amazon QuickSight editions and feature

Microsoft Power BI Training Course Overview: The Microsoft Power BI Training course is designed to equip learners with the knowledge and skills to use Power BI effectively for data analysis and reporting. This course covers the core features of Power BI, from data import and transformation to the creation of reports and visualizations. Learners will explore how to analyse data, generate insights, and create dynamic dashboards for reporting purposes. Whether you are looking to improve your analytical skills or advance your career, this course provides the foundation needed to become proficient in using Power BI for various data analysis tasks. By the end of the course, learners will be able to handle large data sets, create compelling visual reports, and make data-driven decisions. Course Description: This comprehensive Microsoft Power BI course delves into the essential components of the Power BI platform. Learners will start by exploring how to import and work with data, before progressing to designing reports and visualizations. The course includes an in-depth look at the various types of visualizations available, enabling learners to display data in an intuitive, easy-to-understand format. Additionally, learners will explore the Power BI Web App to access and share their reports online. As they move through the course, participants will gain valuable skills in data transformation, reporting, and visualization, all of which are applicable to industries requiring data-driven decision-making. By completing this course, learners will have a solid understanding of Power BI and the ability to create impactful reports and dashboards for business or personal use. Microsoft Power BI Training Curriculum: Module 01: Getting Started Module 02: Working with Data Module 03: Working with Reports and Visualizations Module 04: A Closer Look at Visualizations Module 05: Introduction to the Power BI Web App (See full curriculum) Who is this course for? Individuals seeking to understand Power BI and data analysis. Professionals aiming to enhance their data reporting skills. Beginners with an interest in business intelligence and data analytics. Anyone looking to improve their ability to visualise data for better decision-making. Career Path: Data Analyst Business Intelligence Analyst Reporting Specialist Data Visualisation Specialist Business 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

Duration 3 Days 18 CPD hours This course is intended for This course is intended for information workers and data science professionals who seek to use database reporting and analysis tools such as Microsoft SQL Server Reporting Services, Excel, Power BI, R, SAS and other business intelligence tools, and wish to use TSQL queries to efficiently retrieve data sets from Microsoft SQL Server relational databases for use with these tools. Overview Identify independent and dependent variables and measurement levels in their own analytical work scenarios. Identify variables of interest in relational database tables. Choose a data aggregation level and data set design appropriate for the intended analysis and tool. Use TSQL SELECT queries to produce ready-to-use data sets for analysis in tools such as PowerBI, SQL Server Reporting Services, Excel, R, SAS, SPSS, and others. Create stored procedures, views, and functions to modularize data retrieval code. This three-day instructor-led course is about writing TSQL queries for the purpose of database reporting, analysis, and business intelligence. Specifically, this course presents TSQL within the context of data analysis in other words, making meaning from the data rather than transaction-oriented data-tier application development. The course starts with a brief discussion of levels of measurement and quantitative research methodogy, and integrates these concepts into each TSQL topic presented. The goal is to provide a consistent, direct, and purposeful learning path from RDBMS data retrieval through analytical tools such as SQL Server Reporting Services, PowerBI, Excel, R, SAS, and SPSS. Module 1: Introduction to TSQL for Business Intelligence Two Approaches to SQL Programming TSQL Data Retrieval in an Analytics / Business Intelligence Environment The Database Engine SQL Server Management Studio and the CarDeal Sample Database Identifying Variables in Tables SQL is a Declarative Language Introduction to the SELECT Query Module 2: Turning Table Columns into Variables for Analysis: SELECT List Expressions, WHERE, and ORDER BY Turning Columns into Variables for Analysis Column Expressions, Data Types, and Built-in Functions Column aliases Data type conversions Built-in Scalar Functions Table Aliases The WHERE clause ORDER BY Module 3: Combining Columns from Multiple Tables into a Single Dataset: The JOIN Operators Primary Keys, Foreign Keys, and Joins Understanding Joins, Part 1: CROSSJOIN and the Full Cartesian Product Understanding Joins, Part 2: The INNERJOIN Understanding Joins, Part 3: The OUTERJOINS Understanding Joins, Part 4: Joining more than two tables Understanding Joins, Part 5: Combining INNER and OUTERJOINs Combining JOIN Operations with WHERE and ORDER BY Module 4: Creating an Appropriate Aggregation Level Using GROUP BY Identifying required aggregation level and granularity Aggregate Functions GROUP BY HAVING Order of operations in SELECT queries Module 5: Subqueries, Derived Tables and Common Table Expressions Non-correlated and correlated subqueries Derived tables Common table expressions Module 6: Encapsulating Data Retrieval Logic Views Table-valued functions Stored procedures Creating objects for read-access users Creating database accounts for analytical client tools Module 7: Getting Your Dataset to the Client Connecting to SQL Server and Submitting Queries from Client Tools Connecting and running SELECT queries from: Excel PowerBI RStudio Exporting datasets to files using Results pane from SSMS The bcp utility The Import/Export Wizard Additional course details: Nexus Humans Writing Analytical Queries for Business Intelligence 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 Writing Analytical Queries for Business Intelligence 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 3 Days 18 CPD hours This course is intended for This class is designed for individuals who are (or will soon be) supporting a Salesforce implementation in a decision-making capacity. This includes, but is not limited to, business analysts, IT managers, project managers, executive leaders, and executive sponsors. This class is not recommended for individuals tasked with solution-building. Overview When you complete this course, you will be able to: Identify key stakeholders needed for a successful Salesforce implementation. Describe the Salesforce data model as it relates to Customer 360, Salesforce Clouds, and the Salesforce Platform. Communicate the appropriate security measures needed to control org and data access. Discuss which standard or custom objects and applications should be implemented based on specific requirements and use cases. Effectively strategize how to migrate data into your Salesforce org while maintaining high data quality. Understand Salesforce automation tools and how they solve for various business challenges. Analyze Salesforce data with Reports and Dashboards. Navigate the key phases and milestones of a Salesforce implementation. Explore Salesforce features and functionality and gain the knowledge to make Salesforce implementation decisions with confidence. In this 3-day, heavily discussion-based class, learn about standard and custom objects and applications, data management, data visualization, flow automation tools, security mechanisms, and more. Successfully navigate the key phases and milestones of a Salesforce implementation, effectively communicate business needs, and provide directives to team members tasked with solution-building to deliver a robust Salesforce solution that achieves business goals. Salesforce Data Model Discover the Customer 360 Platform Examine Salesforce Clouds Navigate the Salesforce Platform Review the Salesforce Platform Data Model Understand Data Visualization Security & Access Create Users Access the Org Control Data Objects & Applications Review Standard Objects Understand Custom Objects Explore Standard Applications Discover Custom Applications Salesforce Customizations Work with Fields Design Page Layouts Understand Record Types Review Dynamic Capabilities Successful Data Management Determine Data Strategy Create Data Ensure Data Quality Process Automation Streamline Business Processes Using Automation Tools Learn Purpose-Driven Automation Automate With Flow Data Analysis Using Reports & Dashboards Organize Reports and Dashboards Build Reports Create Dashboards Create an Analytics Strategy Adoption & Continued Improvement Adopt Your Implementation Evaluate Continued Improvements Additional course details: Nexus Humans Understand and Drive Your Salesforce Implementation ( BSX101 ) 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 Understand and Drive Your Salesforce Implementation ( BSX101 ) 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.

Diploma in Python Programming Course Overview The Diploma in Python Programming offers an in-depth exploration of Python, one of the most versatile and in-demand programming languages. This course is designed to provide learners with a strong foundation in Python, covering essential concepts such as data structures, functions, libraries, and file handling. Learners will gain the skills necessary to write Python code to solve real-world problems, enabling them to create applications, automate tasks, and perform data analysis. By the end of the course, learners will have the practical knowledge to use Python effectively for various programming tasks in both professional and personal settings. Course Description This comprehensive course begins with the basics of Python programming, guiding learners through essential concepts such as syntax, data types, and conditional statements. Learners will progress to more advanced topics, including file handling, data storage structures, and error handling. Key modules like the creation of user functions, working with external libraries, and implementing Python in database management provide valuable skills that can be directly applied in the workplace. This course also covers essential tools such as command prompt usage, Jupyter notebooks, and package management in Python. By the end of the course, learners will have developed the confidence and competence to apply Python across various domains, including software development, data analysis, and system automation. Diploma in Python Programming Curriculum Module 01: Introduction to Python Programming Module 02: Getting Started with Python Module 03: Conditional Branching with Python Module 04: Importing External/Internal Library in Python Module 05: Project Rock Paper and Scissors Module 06: Strings Operation in Python Module 07: Date and Time in Python Module 08: File Handling, Read and Write Using Python Module 09: Data Storage Structures: Tuple, List, and Dictionary Module 10: Writing User Functions in Python Module 11: Sending Mail Module 12: Import Tricks in Python Module 13: Import Operating System and Platform Module 14: Exceptions Handling in Python Module 15: Installing Packages and Scheduling in Python Module 16: Database in Python Using SQLite Module 17: Running Programs from Command Prompt and Jupyter Notebook Module 18: Conclusion (See full curriculum) Who is this course for? Individuals seeking to develop a foundational understanding of Python programming. Professionals aiming to enhance their programming skills for career advancement. Beginners with an interest in software development, data analysis, or automation. Anyone looking to pursue a career in programming or technology. Career Path Software Developer Data Analyst Automation Engineer Python Programmer Database Administrator IT Specialist

Duration 3 Days 18 CPD hours This course is intended for This course is aimed at anyone who wants to harness the power of data analytics in their organization including: Business Analysts, Data Analysts, Reporting and BI professionals Analytics professionals and Data Scientists who would like to learn Python Overview This course teaches delegates with no prior programming or data analytics experience how to perform data manipulation, data analysis and data visualization in Python. Mastery of these techniques and how to apply them to business problems will allow delegates to immediately add value in their workplace by extracting valuable insight from company data to allow better, data-driven decisions. Outcome: After attending this course, delegates will: Be able to write effective Python code Know how to access their data from a variety of sources using Python Know how to identify and fix data quality using Python Know how to manipulate data to create analysis ready data Know how to analyze and visualize data to drive data driven decisioning across your organization Becoming a world class data analytics practitioner requires mastery of the most sophisticated data analytics tools. These programming languages are some of the most powerful and flexible tools in the data analytics toolkit. From business questions to data analytics, and beyond For data analytics tasks to affect business decisions they must be driven by a business question. This section will formally outline how to move an analytics project through key phases of development from business question to business solution. Delegates will be able: to describe and understand the general analytics process. to describe and understand the different types of analytics can be used to derive data driven solutions to business to apply that knowledge to their business context Basic Python Programming Conventions This section will cover the basics of writing R programs. Topics covered will include: What is Python? Using Anaconda Writing Python programs Expressions and objects Functions and arguments Basic Python programming conventions Data Structures in Python This section will look at the basic data structures that Python uses and accessing data in Python. Topics covered will include: Vectors Arrays and matrices Factors Lists Data frames Loading .csv files into Python Connecting to External Data This section will look at loading data from other sources into Python. Topics covered will include: Loading .csv files into a pandas data frame Connecting to and loading data from a database into a panda data frame Data Manipulation in Python This section will look at how Python can be used to perform data manipulation operations to prepare datasets for analytics projects. Topics covered will include: Filtering data Deriving new fields Aggregating data Joining data sources Connecting to external data sources Descriptive Analytics and Basic Reporting in Python This section will explain how Python can be used to perform basic descriptive. Topics covered will include: Summary statistics Grouped summary statistics Using descriptive analytics to assess data quality Using descriptive analytics to created business report Using descriptive analytics to conduct exploratory analysis Statistical Analysis in Python This section will explain how Python can be used to created more interesting statistical analysis. Topics covered will include: Significance tests Correlation Linear regressions Using statistical output to create better business decisions. Data Visualisation in Python This section will explain how Python can be used to create effective charts and visualizations. Topics covered will include: Creating different chart types such as bar charts, box plots, histograms and line plots Formatting charts Best Practices Hints and Tips This section will go through some best practice considerations that should be adopted of you are applying Python in a business context.

Duration 1 Days 6 CPD hours This course is intended for This course is intended for the following participants:Cloud professionals interested in taking the Data Engineer certification exam.Data engineering professionals interested in taking the Data Engineer certification exam. Overview This course teaches participants the following skills: Position the Professional Data Engineer Certification Provide information, tips, and advice on taking the exam Review the sample case studies Review each section of the exam covering highest-level concepts sufficient to build confidence in what is known by the candidate and indicate skill gaps/areas of study if not known by the candidate Connect candidates to appropriate target learning This course will help prospective candidates plan their preparation for the Professional Data Engineer exam. The session will cover the structure and format of the examination, as well as its relationship to other Google Cloud certifications. Through lectures, quizzes, and discussions, candidates will familiarize themselves with the domain covered by the examination, to help them devise a preparation strategy. Rehearse useful skills including exam question reasoning and case comprehension. Tips and review of topics from the Data Engineering curriculum. Understanding the Professional Data Engineer Certification Position the Professional Data Engineer certification among the offerings Distinguish between Associate and Professional Provide guidance between Professional Data Engineer and Associate Cloud Engineer Describe how the exam is administered and the exam rules Provide general advice about taking the exam Sample Case Studies for the Professional Data Engineer Exam Flowlogistic MJTelco Designing and Building (Review and preparation tips) Designing data processing systems Designing flexible data representations Designing data pipelines Designing data processing infrastructure Build and maintain data structures and databases Building and maintaining flexible data representations Building and maintaining pipelines Building and maintaining processing infrastructure Analyzing and Modeling (Review and preparation tips) Analyze data and enable machine learning Analyzing data Machine learning Machine learning model deployment Model business processes for analysis and optimization Mapping business requirements to data representations Optimizing data representations, data infrastructure performance and cost Reliability, Policy, and Security (Review and preparation tips) Design for reliability Performing quality control Assessing, troubleshooting, and improving data representation and data processing infrastructure Recovering data Visualize data and advocate policy Building (or selecting) data visualization and reporting tools Advocating policies and publishing data and reports Design for security and compliance Designing secure data infrastructure and processes Designing for legal compliance Resources and next steps Resources for learning more about designing data processing systems, data structures, and databases Resources for learning more about data analysis, machine learning, business process analysis, and optimization Resources for learning more about data visualization and policy Resources for learning more about reliability design Resources for learning more about business process analysis and optimization Resources for learning more about reliability, policies, security, and compliance Additional course details: Nexus Humans Preparing for the Professional Data Engineer Examination 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 Preparing for the Professional Data Engineer Examination 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.

Excel 2016 Formulas and Functions Course Overview: This course is designed to provide learners with a comprehensive understanding of Excel 2016 formulas and functions. By covering essential tools and techniques, the course enables learners to confidently navigate the Excel environment and utilise formulas for data analysis, calculations, and reporting. With a focus on both fundamental and advanced functions, learners will gain the skills needed to streamline their tasks and improve efficiency in the workplace. The course’s practical value lies in its application across various industries, allowing professionals to enhance their data handling and reporting capabilities, making it an invaluable addition to any skill set. Course Description: The "Excel 2016 Formulas and Functions" course covers the core concepts of using Excel formulas and functions to manage and analyse data. It starts with the basics, such as SUM, AVERAGE, and IF functions, before advancing to more complex tools like VLOOKUP and conditional formatting.Through each module, learners will explore how to use these features to automate calculations, create dynamic reports, and manipulate datasets. The course offers a structured approach to mastering Excel, with clear guidance on how to use each function effectively in a business context. Learners will come away with the knowledge to work more efficiently in Excel, enabling them to make informed data-driven decisions and enhance productivity. Excel 2016 Formulas and Functions Curriculum: Module 01: Getting Started with Microsoft Excel 2016 Module 02: Basic Formulas and Functions Module 03: Formulas and Functions Activities (See full curriculum) Who is this course for? Individuals seeking to improve their Excel skills Professionals aiming to enhance their data analysis capabilities Beginners with an interest in data management and analysis Any other individuals looking to gain proficiency in Excel Career Path: Data Analyst Administrative Assistant Financial Analyst Business Analyst Project Coordinator

Course Overview This "Microsoft Power BI - Master Power BI in 90 Minutes!" course offers a concise yet comprehensive introduction to Power BI, empowering learners to quickly create and manage data dashboards. The course is designed for both newcomers and those looking to enhance their skills, covering essential topics to help users understand and utilise Power BI for data analysis and reporting. Upon completion, learners will gain the ability to design dynamic dashboards, manipulate data, and visualise trends, providing valuable insights for decision-making in various business environments. Course Description This course takes learners through Power BI’s core functionalities, starting with an introduction to the platform before advancing to building basic and sophisticated dashboards. Learners will explore key aspects such as data import, filtering, and the creation of interactive visuals. By working with live data, participants will develop an understanding of how to generate real-time reports, enhancing their ability to analyse data and derive insights. The course offers both beginner and advanced concepts, ensuring that all participants can apply what they’ve learned to real-world data scenarios. Upon completing the course, learners will feel confident in their ability to utilise Power BI to its full potential in any business context. Course Modules Module 01: Power BI - Introduction Module 02: Your First Power BI Dashboard Module 03: Your Advanced Power BI Dashboard with Real Live Data Module 04: Course Bonuses (See full curriculum) Who is this course for? Individuals seeking to enhance their data analysis skills. Professionals aiming to improve data visualisation and reporting capabilities. Beginners with an interest in business intelligence or data management. Anyone looking to gain insights into data-driven decision-making. Career Path Business Intelligence Analyst Data Analyst Data Visualisation Specialist Marketing Data Analyst Financial Analyst