226 Business Analyst courses delivered Live Online

Business Development Course Overview This Business Development course provides a comprehensive foundation in key areas essential for driving organisational growth and operational excellence. Learners will explore critical topics such as succession planning, process and supply chain management, strategic analysis, and effective communication. The course equips participants with the skills needed to manage projects, lead teams, and optimise retail pricing and procurement strategies. Through a focus on developing negotiation, marketing, and conflict management skills, learners will gain the confidence to represent their organisation effectively and make informed decisions. By the end of this course, participants will be prepared to contribute strategically to business growth, operational planning, and risk management, enhancing their professional capabilities and career prospects. Course Description This detailed course covers a wide spectrum of business development areas designed to enhance learners’ understanding of how to grow and sustain a successful organisation. Topics include planning and forecasting operations, supply chain oversight, quality management, and project coordination. Participants will delve into strategic product scope, analysis, and multi-channel selling techniques, alongside essential soft skills such as negotiation, communication, and business etiquette. The learning experience emphasises the development of management competencies, talent and time management, and approaches to conflict resolution. Learners will also engage with modules on marketing fundamentals and risk management, ensuring a well-rounded grasp of business dynamics. This course is ideal for those wishing to elevate their strategic thinking and leadership skills within diverse professional environments. Business Development Curriculum Module 01: Business Development and Succession Planning Module 02: Process Management Module 03: Supply Chain Management Module 04: Planning & Forecasting Operations Module 05: Procurement & Purchasing Management Module 06: Project Management Module 07: Retail Pricing Module 08: Business Analysis Planning and Monitoring Module 09: Strategic Analysis and Product Scope Module 10: Quality Management Module 11: Management Skills for Leading Your Team Module 12: Selling in Multiple Channels Module 13: Representing Your Boss and Company Module 14: Preparing for Brainstorming Module 15: Generating Solutions (I) Module 16: Generating Solutions (II) Module 17: Analyzing Solutions Module 18: Selecting a Solution Module 19: Negotiation Techniques Module 20: Communication Skills Module 21: Skills of an Effective Administrator Module 22: What is Marketing? Module 23: Common Marketing Types (I) Module 24: Common Marketing Types (II) Module 25: Conflict Management Module 26: Talent Management Module 27: Time Management Module 28: Managing Risk and Recovery Module 29: Business Etiquette (See full curriculum) Who Is This Course For? Individuals seeking to enhance their business growth and development skills. Professionals aiming to progress into leadership or management roles. Beginners with an interest in business operations and strategic planning. Team leaders and administrators looking to improve communication and negotiation skills. Career Path Business Development Manager Project Coordinator Supply Chain Analyst Procurement Officer Marketing Executive Operations Manager Sales Manager Team Leader or Supervisor

Duration 2 Days 12 CPD hours This course is intended for Executives, Project Managers, Business Analysts, Business and IT stakeholders engaged in improving the delivery of products and services that meet user needs through the use of Microsoft SharePoint; Anyone who wants to improve their Business Analysis skills; Project stakeholders concerned with SharePoint requirements. Overview Plan, manage and close requirements for a project in reduced time using good business analysis practices Minimize project uncertainty and risk by applying good techniques Ensure your project delivers required functionality and adds value to the business Create an environment of self-management for your team that will be able to continuously align the delivered product or services with desired business needs, easily adapting to changing requirements throughout the process. Requirements can change frequently during a SharePoint project, and therefore projects need a streamlined, flexible approach to requirements change management. SharePoint professionals want to develop systems and services which are both high-quality and high-value, and the easiest way to achieve this is to implement the highest priority requirements first. This enables the projects to maximize value for their stakeholders. Introduction ? Roles involved in a SharePoint project The opportunities and challenges of a SharePoint project The business analysis process BA role vs. project manager role BA / PM competencies Case Study Exercise Understanding SharePoint Requirements Business, User, Functional, Quality-of-service and implementation requirements Requirements vs. specifications Requirements vs. business rules Risk management and risk response strategies Analyzing requirements Characteristics of effective requirements Case Study Exercise SharePoint Requirements Modeling Identify high level scope Identify initial requirements stack Identify an architectural vision Plan your iteration Iteration modeling Model storming Test driven development Case Study Exercise The Change Management Process Managing the Solution Scope and Requirements Capturing the Requirements Traceability Maintaining the Requirements for re-use Managing Requirements Conflicts Preparing the Requirements Package Building the Requirements communications plan Case Study Exercise Assessing & Validating Requirements Validating and verifying SharePoint Requirements Creating a master test plan Create test scenarios and test cases Case Study Exercise Additional Information Useful books and links on managing requirements and projects for SharePoint initiatives

Duration 3 Days 18 CPD hours This course is intended for This course is designed for project managers, Scrum masters, business analysts, and team leaders looking to effectively manage their development projects using Team Foundation Server 2017. Overview The course also demonstrates how TFS facilitates the use of storyboards to prototype experiences, request stakeholder feedback, foster team collaboration, and generate reports. The final two modules of the course provide an overview of how testers and developers can work effectively using appropriate tools in the Visual Studio family. In this course, attendees will plan a new software development project and go through the steps to initiate the project using Visual Studio 2017. This includes recording requirements, creating a product backlog, and estimating effort for backlog items. Introducing the Microsoft Visual Studio 2017 Family What?s new in Visual Studio 2017 Overview of the Visual Studio 2017 family Overview of product features Project workflow across the Visual Studio 2017 suite of products Initiating a New Project Organizing projects in TFS Understanding process templates Creating a new team project Setting team project properties Switching between team projects Work Item Primer Overview of work items Traceability between work items Searching and creating custom queries Work item charting and pinning charts Work item tagging Configuring project notifications Creating our Product Backlog Examining requirement types Creating backlog items Creating requirement hierarchies using features The importance of acceptance criteria Agile Estimation Introduction to estimation Using story points Planning Poker and other popular estimation techniques Adding your estimates to TFS work items Working from the Product Backlog Introducing the Kanban board Entering and editing details on the Kanban board Customizing columns, including using split columns and limiting WIP Recording our Definition of Done (DoD) Understanding the Cumulative Flow Diagram Working in Sprints Specifying your sprint schedule and your team capacity Selecting items for the sprint backlog using forecasting Decomposing requirements into tasks Using burndown charts to track progress Monitoring work using the task board Working with unparented work items Retrospectives The importance of retrospectives Conducting an efficient sprint retrospective What you should avoid in your retrospective Working with TFS Teams Configuring teams in our team project Managing work from a master backlog Allocating work to our teams Configuring iterations for TFS teams Enhancing Requirements Using Storyboards Overview of storyboarding capabilities Creating a storyboard to illustrate a requirement Linking a storyboard to a work item Getting Stakeholder Feedback Introducing the Microsoft Feedback Client Using the Microsoft Feedback Client to provide rich feedback to the team Adding continuous feedback into your workflow Fostering Team Collaboration An overview of the various clients The use of email in sharing information Choosing the appropriate client tool Creating and Customizing Reports Overview of reporting architecture Reviewing the out of the box reports Adding new reports Creating ad hoc reports using Excel Overview of Agile Testing The role of the tester in a sprint planning meeting A lap around web-based test management Creating a test plan Creating manual test cases from requirements Overview of Agile Development Using My Work to select tasks from the sprint backlog Understanding the value of linking changesets to work items The importance of unit testing Creating a continuous integration build Additional course details: Nexus Humans Managing Agile Projects Using TFS 2017 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 Managing Agile Projects Using TFS 2017 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 2 Days 12 CPD hours This course is intended for This introductory-level course is intended for Business Analysts and Data Analysts (or anyone else in the data science realm) who are already comfortable working with numerical data in Excel or other spreadsheet environments. No prior programming experience is required, and a browser is the only tool necessary for the course. Overview This course is approximately 50% hands-on, combining expert lecture, real-world demonstrations and group discussions with machine-based practical labs and exercises. Our engaging instructors and mentors are highly experienced practitioners who bring years of current 'on-the-job' experience into every classroom. Throughout the hands-on course students, will learn to leverage Python scripting for data science (to a basic level) using the most current and efficient skills and techniques. Working in a hands-on learning environment, guided by our expert team, attendees will learn about and explore (to a basic level): How to work with Python interactively in web notebooks The essentials of Python scripting Key concepts necessary to enter the world of Data Science via Python This course introduces data analysts and business analysts (as well as anyone interested in Data Science) to the Python programming language, as it?s often used in Data Science in web notebooks. This goal of this course is to provide students with a baseline understanding of core concepts that can serve as a platform of knowledge to follow up with more in-depth training and real-world practice. This course introduces data analysts and business analysts (as well as anyone interested in Data Science) to the Python programming language, as it's often used in Data Science in web notebooks. This goal of this course is to provide students with a baseline understanding of core concepts that can serve as a platform of knowledge to follow up with more in-depth training and real-world practice. Additional course details: Nexus Humans Python for Data Science Primer: Hands-on Technical Overview (TTPS4872) 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 Python for Data Science Primer: Hands-on Technical Overview (TTPS4872) 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 1 Days 6 CPD hours This course is intended for New administrators, business analysts or report writers who are new to creating reports or dashboards within Salesforce. Overview A student in this class will learn the basic Salesforce object model, and how to create and secure reports and dashboards. The instructor will lead students through exercises to create tabular, summary, matrix and join reports. Students will learn advanced reporting functionality such as charting, report summary fields, bucket fields, conditional highlighting, advanced report filters and building custom report types. Finally, the student will learn how to create and run dashboards and schedule and email reports and dashboards. This course is specifically designed to teach administrators, business analysts or report writers how to utilize the basic and advanced analytic capabilities of Salesforce. Introductions / Login to Training OrgsOverview of Salesforce Object ModelTabular, Summary, Matrix, Join ReportsCharts, Bucket Fields, Report Summary Fields, Conditional HighlightingCustom Report TypesDashboardsReport & Dashboard Scheduling Additional course details: Nexus Humans Introduction to Salesforce.com Analytics - Building Reports and Dashboards 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 Introduction to Salesforce.com Analytics - Building Reports and Dashboards 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 2 Days 12 CPD hours This course is intended for This introductory-level course is intended for Business Analysts and Data Analysts (or anyone else in the data science realm) who are already comfortable working with numerical data in Excel or other spreadsheet environments. No prior programming experience is required, and a browser is the only tool necessary for the course. Overview This course is approximately 50% hands-on, combining expert lecture, real-world demonstrations and group discussions with machine-based practical labs and exercises. Our engaging instructors and mentors are highly experienced practitioners who bring years of current 'on-the-job' experience into every classroom. Throughout the hands-on course students, will learn to leverage Python scripting for data science (to a basic level) using the most current and efficient skills and techniques. Working in a hands-on learning environment, guided by our expert team, attendees will learn about and explore (to a basic level): How to work with Python interactively in web notebooks The essentials of Python scripting Key concepts necessary to enter the world of Data Science via Python This course introduces data analysts and business analysts (as well as anyone interested in Data Science) to the Python programming language, as it?s often used in Data Science in web notebooks. This goal of this course is to provide students with a baseline understanding of core concepts that can serve as a platform of knowledge to follow up with more in-depth training and real-world practice. An Overview of Python Why Python? Python in the Shell Python in Web Notebooks (iPython, Jupyter, Zeppelin) Demo: Python, Notebooks, and Data Science Getting Started Using variables Builtin functions Strings Numbers Converting among types Writing to the screen Command line parameters Flow Control About flow control White space Conditional expressions Relational and Boolean operators While loops Alternate loop exits Sequences, Arrays, Dictionaries and Sets About sequences Lists and list methods Tuples Indexing and slicing Iterating through a sequence Sequence functions, keywords, and operators List comprehensions Generator Expressions Nested sequences Working with Dictionaries Working with Sets Working with files File overview Opening a text file Reading a text file Writing to a text file Reading and writing raw (binary) data Functions Defining functions Parameters Global and local scope Nested functions Returning values Essential Demos Sorting Exceptions Importing Modules Classes Regular Expressions The standard library Math functions The string module Dates and times Working with dates and times Translating timestamps Parsing dates from text Formatting dates Calendar data Python and Data Science Data Science Essentials Pandas Overview NumPy Overview SciKit Overview MatPlotLib Overview Working with Python in Data Science Additional course details: Nexus Humans Python for Data Science: Hands-on Technical Overview (TTPS4873) 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 Python for Data Science: Hands-on Technical Overview (TTPS4873) 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 2 Days 12 CPD hours This course is intended for Business Analysts, Technical Managers, and Programmers Overview This intensive training course helps students learn the practical aspects of the R programming language. The course is supplemented by many hands-on labs which allow attendees to immediately apply their theoretical knowledge in practice. Over the past few years, R has been steadily gaining popularity with business analysts, statisticians and data scientists as a tool of choice for conducting statistical analysis of data as well as supervised and unsupervised machine learning. What is R ? What is R? ? Positioning of R in the Data Science Space ? The Legal Aspects ? Microsoft R Open ? R Integrated Development Environments ? Running R ? Running RStudio ? Getting Help ? General Notes on R Commands and Statements ? Assignment Operators ? R Core Data Structures ? Assignment Example ? R Objects and Workspace ? Printing Objects ? Arithmetic Operators ? Logical Operators ? System Date and Time ? Operations ? User-defined Functions ? Control Statements ? Conditional Execution ? Repetitive Execution ? Repetitive execution ? Built-in Functions ? Summary Introduction to Functional Programming with R ? What is Functional Programming (FP)? ? Terminology: Higher-Order Functions ? A Short List of Languages that Support FP ? Functional Programming in R ? Vector and Matrix Arithmetic ? Vector Arithmetic Example ? More Examples of FP in R ? Summary Managing Your Environment ? Getting and Setting the Working Directory ? Getting the List of Files in a Directory ? The R Home Directory ? Executing External R commands ? Loading External Scripts in RStudio ? Listing Objects in Workspace ? Removing Objects in Workspace ? Saving Your Workspace in R ? Saving Your Workspace in RStudio ? Saving Your Workspace in R GUI ? Loading Your Workspace ? Diverting Output to a File ? Batch (Unattended) Processing ? Controlling Global Options ? Summary R Type System and Structures ? The R Data Types ? System Date and Time ? Formatting Date and Time ? Using the mode() Function ? R Data Structures ? What is the Type of My Data Structure? ? Creating Vectors ? Logical Vectors ? Character Vectors ? Factorization ? Multi-Mode Vectors ? The Length of the Vector ? Getting Vector Elements ? Lists ? A List with Element Names ? Extracting List Elements ? Adding to a List ? Matrix Data Structure ? Creating Matrices ? Creating Matrices with cbind() and rbind() ? Working with Data Frames ? Matrices vs Data Frames ? A Data Frame Sample ? Creating a Data Frame ? Accessing Data Cells ? Getting Info About a Data Frame ? Selecting Columns in Data Frames ? Selecting Rows in Data Frames ? Getting a Subset of a Data Frame ? Sorting (ordering) Data in Data Frames by Attribute(s) ? Editing Data Frames ? The str() Function ? Type Conversion (Coercion) ? The summary() Function ? Checking an Object's Type ? Summary Extending R ? The Base R Packages ? Loading Packages ? What is the Difference between Package and Library? ? Extending R ? The CRAN Web Site ? Extending R in R GUI ? Extending R in RStudio ? Installing and Removing Packages from Command-Line ? Summary Read-Write and Import-Export Operations in R ? Reading Data from a File into a Vector ? Example of Reading Data from a File into A Vector ? Writing Data to a File ? Example of Writing Data to a File ? Reading Data into A Data Frame ? Writing CSV Files ? Importing Data into R ? Exporting Data from R ? Summary Statistical Computing Features in R ? Statistical Computing Features ? Descriptive Statistics ? Basic Statistical Functions ? Examples of Using Basic Statistical Functions ? Non-uniformity of a Probability Distribution ? Writing Your Own skew and kurtosis Functions ? Generating Normally Distributed Random Numbers ? Generating Uniformly Distributed Random Numbers ? Using the summary() Function ? Math Functions Used in Data Analysis ? Examples of Using Math Functions ? Correlations ? Correlation Example ? Testing Correlation Coefficient for Significance ? The cor.test() Function ? The cor.test() Example ? Regression Analysis ? Types of Regression ? Simple Linear Regression Model ? Least-Squares Method (LSM) ? LSM Assumptions ? Fitting Linear Regression Models in R ? Example of Using lm() ? Confidence Intervals for Model Parameters ? Example of Using lm() with a Data Frame ? Regression Models in Excel ? Multiple Regression Analysis ? Summary Data Manipulation and Transformation in R ? Applying Functions to Matrices and Data Frames ? The apply() Function ? Using apply() ? Using apply() with a User-Defined Function ? apply() Variants ? Using tapply() ? Adding a Column to a Data Frame ? Dropping A Column in a Data Frame ? The attach() and detach() Functions ? Sampling ? Using sample() for Generating Labels ? Set Operations ? Example of Using Set Operations ? The dplyr Package ? Object Masking (Shadowing) Considerations ? Getting More Information on dplyr in RStudio ? The search() or searchpaths() Functions ? Handling Large Data Sets in R with the data.table Package ? The fread() and fwrite() functions from the data.table Package ? Using the Data Table Structure ? Summary Data Visualization in R ? Data Visualization ? Data Visualization in R ? The ggplot2 Data Visualization Package ? Creating Bar Plots in R ? Creating Horizontal Bar Plots ? Using barplot() with Matrices ? Using barplot() with Matrices Example ? Customizing Plots ? Histograms in R ? Building Histograms with hist() ? Example of using hist() ? Pie Charts in R ? Examples of using pie() ? Generic X-Y Plotting ? Examples of the plot() function ? Dot Plots in R ? Saving Your Work ? Supported Export Options ? Plots in RStudio ? Saving a Plot as an Image ? Summary Using R Efficiently ? Object Memory Allocation Considerations ? Garbage Collection ? Finding Out About Loaded Packages ? Using the conflicts() Function ? Getting Information About the Object Source Package with the pryr Package ? Using the where() Function from the pryr Package ? Timing Your Code ? Timing Your Code with system.time() ? Timing Your Code with System.time() ? Sleeping a Program ? Handling Large Data Sets in R with the data.table Package ? Passing System-Level Parameters to R ? Summary Lab Exercises Lab 1 - Getting Started with R Lab 2 - Learning the R Type System and Structures Lab 3 - Read and Write Operations in R Lab 4 - Data Import and Export in R Lab 5 - k-Nearest Neighbors Algorithm Lab 6 - Creating Your Own Statistical Functions Lab 7 - Simple Linear Regression Lab 8 - Monte-Carlo Simulation (Method) Lab 9 - Data Processing with R Lab 10 - Using R Graphics Package Lab 11 - Using R Efficiently

Duration 2 Days 12 CPD hours This course is intended for Application Consultants, Business Analysts, and Process Owners Overview Learn to navigate the catalog, create and approve requisitions, and receive against POs. This course covers all of the functions of SAP Ariba Buying related to the creation of requisitions, the issuing of purchase orders, and receiving against purchase orders. Course Outline Introduction The Dashboard Catalogs Requisitions Accounting Approval Managing POs Receiving SAP Ariba Mobile Searching and Reporting Collaboration Demand Aggregation

Duration 2 Days 12 CPD hours This course is intended for Application Developers Business Analysts Developer End Users Functional Implementer Java Developer System Analysts Technical Administrator Overview Create administrator-level personalizations Personalize configurable pages Utilize advanced personalization features Implement flexfields on OA Framework-based pages Create custom look and feel definitions Create user-level personalizations This course will be applicable for customers who have implemented Oracle E-Business Suite Release 12 or Oracle E-Business Suite 12.1. This course will be applicable for customers who have implemented Oracle E-Business Suite Release 12 or Oracle E-Business Suite 12.1.

Duration 2 Days 12 CPD hours This course is intended for Application consultants, Business Analysts, Executives, Technology Consultants, Users Overview By the end of this course, students will be able to:Explain SAP LumiraCreate documents and acquire dataPrepare datasetsVisualize dataShare stories In this course, students will learn how to create stunning and interactive visualizations by choosing a rich library of visualization types, ranging from scatter plots, heat and geo maps to tag clouds, box plots and network charts. Course Outline Positioning and Overview of SAP Lumira Discovery Navigating the BI Launchpad Acquiring Data Enrich the Dataset Create Visualizations Create a Story Sharing Options Using the Lumira Discovery Formula Editor Additional Data Sources Data Mashups