1291 Business Analysis courses

Overview of Organisational Change & Effective Planning In today’s fast-moving business world, change is not just common—it’s necessary. Companies must keep adapting to stay ahead, and that’s why learning how to manage change is so important. Our Organisational Change & Effective Planning course is here to help you build the right skills to handle change in any workplace. Whether your organisation is going through big shifts or small adjustments, this course shows you how to manage change smoothly and with confidence. More than 70% of UK organisations have gone through major changes in the last three years. With over £4.5 billion spent every year on organisational development, having the right knowledge is key. This Organisational Change & Effective Planning course takes you through the full process—from understanding how businesses are structured to making strong plans that get results. You’ll learn how to guide your team during transitions, use training methods that work, and make HR a strong part of the change process. This course gives you clear tools and methods that make a real difference. You’ll learn how to support your team, plan change that works, and lead with purpose. Whether you're handling change in a small department or across an entire company, Organisational Change & Effective Planning gives you the support you need to succeed—again and again. By the end of the Organisational Change & Effective Planning course, you will be able to: Understand different types of organisational structures and how they affect daily work Use practical leadership skills to manage and support different teams Apply simple but powerful training methods across departments Recognise how HR helps in growing and changing an organisation Build smart strategies to manage and lead through business changes Create strong change plans that show clear results Who Should Take This Course This course is ideal for: Managers who want to lead change in their team or department HR professionals working on company development or transformation Team leaders who are starting to take on more change-related tasks Business analysts involved in helping companies restructure Anyone working in fast-changing industries who needs to keep up and improve Process of Evaluation After studying the Organisational Change & Effective Planning Course, your skills and knowledge will be tested with an MCQ exam or assignment. You have to get a score of 60% to pass the test and get your certificate. Certificate of Achievement Certificate of Completion - Digital / PDF Certificate After completing the Organisational Change & Effective Planning Course, you can order your CPD Accredited Digital / PDF Certificate for £5.99. (Each) Certificate of Completion - Hard copy Certificate You can get the CPD Accredited Hard Copy Certificate for £12.99. (Each) Shipping Charges: Inside the UK: £3.99 International: £10.99 Requirements You don't need any educational qualification or experience to enrol in the Organisational Change & Effective Planning course. Career Path After completing the Organisational Change & Effective Planning course, you can explore roles such as: Change Management Consultant – £45K to £70K per year Organisational Development Manager – £40K to £65K per year HR Business Partner – £35K to £55K per year Team Development Specialist – £30K to £45K per year Business Transformation Analyst – £38K to £60K per year Course Curriculum Module 01: Types Of Organisations 00:16:00 Module 02: Managing And Leading Teams 00:15:00 Module 03: Applying The Group Or Functional Approach To Training 00:12:00 Module 04: Role Of HR & Organisational Development 00:14:00 Module 05: Change In A Business 00:15:00 Module 06: Organisational Commitment, Motivating And Supporting 00:13:00 Module 07: Developing A Change Plan And Evaluating The Effectiveness 00:14:00

Unlock the power of data with our comprehensive course on Business and Data Analysis with SQL. Learn essential SQL skills to extract meaningful insights, make data-driven decisions, and drive business success. Whether you're a beginner or looking to enhance your expertise, our course empowers you with the tools and knowledge needed to excel in the dynamic world of data analysis. Enroll now to master SQL for business intelligence and elevate your analytical skills to new heights.

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

Overview of HR System Selection Essentials In today’s changing workplace, HR systems play a big role in helping organisations grow and succeed. The HR System Selection Essentials course comes at the right time, as more UK businesses are putting money into HR technology. In fact, the HR tech market in the UK is expected to reach £1.2 billion by 2026. A well-chosen HR system makes everyday tasks easier, helps employees have a better experience at work, and gives useful data to support smart decisions. The HR System Selection Essentials course helps learners understand what to look for when choosing the right HR system. It covers the basic parts of HR systems and how they can help with hiring, keeping good staff, and supporting employee growth. With many businesses trying hard to keep top talent, knowing how to choose a system that supports these goals gives professionals an advantage. This course also shows how to use data to help with planning and decision-making in HR. Whether you're working in HR or planning to, the HR System Selection Essentials course builds the knowledge needed for today’s digital workplace. It also teaches how to set clear goals for system selection and manage the setup process well. By taking the HR System Selection Essentials course, you’ll learn how to support your team better through smart technology choices. By the end of the HR System Selection Essentials course, you will be able to: Understand the main parts of today’s HR systems Check if system reports meet your company’s needs Look at the kind of HR data needed for good decision-making Build a clear checklist to choose the right HR system Plan how to set up a new HR system in your workplace Measure how well the system is working using real results Who is this course for The HR System Selection Essentials course is perfect for: HR professionals who want to improve their HR technology and know how to pick the right system IT team members who work with HR on setting up or connecting systems Managers who help make decisions about HR technology Business analysts who review what HR systems can and should do Operations leaders who want to make HR processes smoother and more effective Process of Evaluation After studying the HR System Selection Essentials Course, an MCQ exam or assignment will test your skills and knowledge. You have to get a score of 60% to pass the test and get your certificate. Certificate of Achievement Certificate of Completion - Digital / PDF Certificate After completing the HR System Selection Essentials Course, you can order your CPD Accredited Digital / PDF Certificate for £5.99. (Each) Certificate of Completion - Hard copy Certificate You can get the CPD Accredited Hard Copy Certificate for £12.99. (Each) Shipping Charges: Inside the UK: £3.99 International: £10.99 Requirements You don't need any educational qualification or experience to enrol in the HR System Selection Essentials course. Career Path After completing the HR System Selection Essentials course, you could work in roles such as: HR Systems Manager – £45K to £65K per year HR Technology Consultant – £50K to £75K per year HRIS Analyst – £35K to £55K per year HR Project Manager – £40K to £60K per year HR Data Analyst – £38K to £58K per year Course Curriculum HR System Selection Essentials Lesson 01: Introduction 00:04:00 Lesson 02: Elements of HR System 00:10:00 Lesson 03: Reporting and Analytics 00:00:00 Lesson 04: Selecting an HR System 00:18:00 Lesson 05: Implementing the New System 00:15:00

Business Finance 101: A Beginner’s Guide to Business Accounting and Finance   Course Description   Course Description Three are three main reasons for business failure – an under-skilled management team; ineffective marketing; and poor financial management. Every manager, or student of management, requires a good grasp of business finance. This course will help.  Business finance concerns the management of the monetary resources of an organisation. There are two aspects to this: Raising the money to invest in the business Managing that investment properly to generate a return   Raising the money is about having an attractive proposition and managing the risk to investors. Managing the investment is about the financial controls and reporting of the business. This course covers the three main financial reports; financial performance indicators; and investment analysis.  This course will give you a good grasp of the key principles and issues in business finance.     Key Learning Participants in this course will learn: The history of business accounting Why businesses fail The two main purposes of business finance and accounting The key principles of business finance and what they mean What debits and credits are The three key financial statements for an organisation What the Balance Sheet tells you What the Income Statement (also called the Profit and Loss Account) tells you What the Cashflow Statement tells you Key financial performance indicators in business Analysing business investments   Curriculum L1 What is business finance? L2 Why businesses fail L3 The Principles of Business Finance Part 1 L4 The Principles of Business Finance Part 2 L5 The Balance Sheet L6 The Income Statement L7 The Cashflow Statement L8 A Business Finance Exercise L9 Financial Performance Indicators L10 Investment Analysis L11 Investment Analysis Exercise L12 Key Learning Points in Business Finance   Pre-Course Requirements None     Additional Resources None     Course Tutor Your tutor is Ross Maynard. Ross is a Fellow of the Chartered Institute of Management Accountants in the UK and has 30 years’ experience as a process improvement consultant specialising in business processes and organisation development. Ross is also a professional author of online training courses. Ross lives in Scotland with his wife, daughter and Cocker Spaniel

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