Duration 2 Days 12 CPD hours This course is intended for Executives, Project Managers, Business Analysts, Business and IT stakeholders working with analysts, Quality and process engineers, technicians, corrective action coordinators or managers; supervisors, team leaders, and process operators; anyone who wants to improve their ability to solve recurring problems. Overview Learn how to initiate a root cause analysis and gather data for investigating process and non-process incidentsDemonstrate how to collect data through interviews and analysisApply powerful techniques to identify and know the difference between symptoms and root causesLearn to know when to use the appropriate technique in root cause identification Learn how to avoid future incidents by developing appropriate recommendations to address causal factors and root causes Develop a process to identify systemic problem areas In this course, participants will learn to apply several practical, systematic methods for analyzing incidents and problems to uncover root causes. Understanding of these techniques will be reinforced by classroom exercises. Introduction & Objectives What is a 'Problem?' Why Problems Persist What is A Root Cause? Why Root Causes are important How to Organize for an RCA RCA Roles and Responsibilities Assemble your RCA Team Modes of Communication How to Resolve Conflict Case Study Exercise Select the Problem to Analyze Define the selection criteria Plan and estimate tasks for the team Finalize the plan and gain agreement among your stakeholders Case Study Exercise Define the Problem What to look for - Problem-as-Given (PAG) vs. Problem-as-Understood (PAU) Developing your problem statement Refining the problem specification Case Study Exercise Identify the Source of the Problem Discuss when to use the appropriate analysis technique to determine the problem source Process Diagram Forms & Checklists Statistical Sampling Fishbone Diagram Surveys Charts - Line, Scatter, Bar, & Pie Case Study Exercise Solution Options Analysis & Selecting the 'Best Fit' How to approach different solution options Brainstorming Weighted Evaluation Selecting the appropriate option Hold an Retrospective on your approach Planning the proposal Case Study Exercise Putting RCA into Practice Create a Root Cause Analysis program within your organization How to develop appropriate recommendations to address root causes at various levels to avoid future incidents Additional course details: Nexus Humans BA10 - Understanding Root Cause Analysis 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 BA10 - Understanding Root Cause Analysis 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 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.
Introduction to Agile for Executives: In-House Training This session provides executives with an overview of Agile values and principles, the key benefits of an Agile approach, and its differences with the traditional Waterfall method. During the session, we compare and contrast the major Agile methods, with an emphasis on Scrum, as the most popular in the market. And most importantly, we present some criteria for Agile Transformation, possible certifications to pursue, and what is needed at the senior leadership level to achieve the best business results. What you will Learn At the end of this program, you will be able to: Explain the basics and benefits of using an Agile approach Describe the Scrum framework, its events, artifacts, and roles and responsibilities Illustrate an Agile approach outside of Software Development Define Scaled Agile Determine how to support an Agile transformation for your organization Getting Started Introduction Course structure Course goals and objectives Agile Introduction What is Agile? Agile benefits Agile myths and realities Overview of Agile Methods Overview of Agile methods Scrum method Lean and Kanban methods Criteria and certifications What Executives Need to Know About Agile Agile is not just for IT Agile can be scaled Agile transformation needs your support Summary and Next Steps Review Personal Action Plan
Introduction to Agile and Scrum: Virtual In-House Training This half-day course provides an overview of Agile principles and mindset, and the Scrum framework as a key Agile approach. It will provide you with the key benefits of an Agile approach, and its differences with the traditional Waterfall method. Lastly, as Agile is looked upon more frequently as an alternative delivery method, you will review situations where Agile can be adapted outside of software development, where it is most commonly used. What you will Learn At the end of this program, you will be able to: Explain the basics and benefits of using an Agile approach Describe the Scrum framework, its events, artifacts and roles and responsibilities Illustrate Agile approaches outside of Software Development Getting Started Introduction Course structure Course goals and objectives Agile Introduction What is Agile? Agile Benefits Agile Methods Overview of Scrum Scrum Overview Scrum Events Scrum Artifacts Scrum Roles Definition of Done Agile Approaches Outside of Software Development Agile in other environments Product Development Course Development Marketing Agile Project Candidates Summary What Agile is not... Concerns and Pitfalls
This course is very much a discussion, so be prepared to present and critically analyse your own and class mates work. You will also need to bring a few examples of work you have done in the past. Learning and applying best practice visualisation principles will improve effective discussions amongst decision makers throughout your organisation. As a result more end-users of your dashboards will be able to make better decisions, more quickly. This 2 Day training course is aimed at analysts with good working knowledge of BI tools (we use Tableau to present, but attendees can use their own software such as Power BI or Qlik Sense). It is a great preparation for taking advanced certifications, such as Tableau Certified Professional. Contact us to discuss the Visual Analytics Best Practice course Email us if you are interested in an on-site course, or would be interested in different dates and locations This Tableau Desktop training intermediate course is designed for the professional who has a solid foundation with Tableau and is looking to take it to the next level. Attendees should have a good understanding of the fundamental concepts of building Tableau worksheets and dashboards typically achieved from having attended our Tableau Desktop Foundation Course. At the end of this course you will be able to communicate insights more effectively, enabling your organisation to make better decisions, quickly. The Tableau Desktop Analyst training course is aimed at people who are used to working with MS Excel or other Business Intelligence tools and who have preferably been using Tableau already for basic reporting. The course includes the following topics: WHAT IS VISUAL ANALYSIS? Visual Analytics Visual Analytics Process Advantages of Visual Analysis Exercise: Interpreting Visualisations HOW DO WE PROCESS VISUAL INFORMATION? Memory and Processing Types Exercise: Identifying Types of Processing Cognitive Load Exercise: Analysing Cognitive Load Focus and Guide the Viewer Remove Visual Distractions Organise Information into Chunks Design for Proximity Exercise: Reducing Cognitive Load SENSORY MEMORY Pre-attentive Attributes Quantitatively-Perceived Attributes Categorically-Perceived Attributes Exercise: Analysing Pre-attentive Attributes Form & Attributes Exercise: Using Form Effectively Colour & Attributes Exercise: Using Colour Effectively Position & Attributes Exercise: Using Position Effectively ENSURING VISUAL INTEGRITY Informing without Misleading Gestalt Principles Visual Area Axis & Scale Colour Detail Exercise: Informing without Misleading CHOOSING THE RIGHT VISUALISATION Comparing and Ranking Categories Comparing Measures Comparing Parts to Whole Viewing Data Over Time Charts Types for Mapping Viewing Correlation Viewing Distributions Viewing Specific Values DASHBOARDS AND STORIES Exercise: Picking the Chart Type Exercise: Brainstorming Visual Best Practice Development Process for Dashboards and Stories Plan the Visualisation Create the Visualisation Test the Visualisation Exercise: Designing Dashboards and Stories This training course includes over 20 hands-on exercises to help participants “learn by doing” and to assist group discussions around real-life use cases. Each attendee receives an extensive training manual which covers the theory, practical applications and use cases, exercises and solutions together with a USB with all the materials required for the training. The course starts at 09:30 on the first day and ends at 17:00. On the second day the course starts at 09:00 and ends at 17:00. Students must bring their own laptop with an active version of Tableau Desktop 10.5 (or later) pre-installed. What People Are Saying About This Course "Steve was willing to address questions arising from his content in a full and understandable way"Lisa L. "Really enjoyed the course and feel the subject and the way it was taught was very close to my needs"James G. "The course tutor Steve was incredibly helpful and taught the information very well while making the two days very enjoyable."Bradd P. "The host and his courses will give you the tools and confidence that you need to be comfortable with Tableau."Jack S. "Steve was fantastic with his knowledge and knowhow about the product. Where possible he made sure you could put demonstrations in to working practice, to give the audience a clear understanding."Tim H. "This was a very interesting and helpful course, which will definitely help me produce smarter, cleaner visualisations that will deliver more data-driven insights within our business."Richard A. "Steve is very open to questions and will go out of his way to answer any query. Thank you"Wasif N. "Steve was willing to address questions arising from his content in a full and understandable way"Lisa L. "Really enjoyed the course and feel the subject and the way it was taught was very close to my needs"James G.
Introduction to Agile for Executives: Virtual In-House Training This session provides executives with an overview of Agile values and principles, the key benefits of an Agile approach, and its differences with the traditional Waterfall method. During the session, we compare and contrast the major Agile methods, with an emphasis on Scrum, as the most popular in the market. And most importantly, we present some criteria for Agile Transformation, possible certifications to pursue, and what is needed at the senior leadership level to achieve the best business results. What you will Learn At the end of this program, you will be able to: Explain the basics and benefits of using an Agile approach Describe the Scrum framework, its events, artifacts, and roles and responsibilities Illustrate an Agile approach outside of Software Development Define Scaled Agile Determine how to support an Agile transformation for your organization Getting Started Introduction Course structure Course goals and objectives Agile Introduction What is Agile? Agile benefits Agile myths and realities Overview of Agile Methods Overview of Agile methods Scrum method Lean and Kanban methods Criteria and certifications What Executives Need to Know About Agile Agile is not just for IT Agile can be scaled Agile transformation needs your support Summary and Next Steps Review Personal Action Plan
Introduction to Agile and Scrum: In-House Training This half-day course provides an overview of Agile principles and mindset, and the Scrum framework as a key Agile approach. It will provide you with the key benefits of an Agile approach, and its differences with the traditional Waterfall method. Lastly, as Agile is looked upon more frequently as an alternative delivery method, you will review situations where Agile can be adapted outside of software development, where it is most commonly used. What you will Learn At the end of this program, you will be able to: Explain the basics and benefits of using an Agile approach Describe the Scrum framework, its events, artifacts and roles and responsibilities Illustrate Agile approaches outside of Software Development Getting Started Introduction Course structure Course goals and objectives Agile Introduction What is Agile? Agile Benefits Agile Methods Overview of Scrum Scrum Overview Scrum Events Scrum Artifacts Scrum Roles Definition of Done Agile Approaches Outside of Software Development Agile in other environments Product Development Course Development Marketing Agile Project Candidates Summary What Agile is not... Concerns and Pitfalls
Duration 4 Days 24 CPD hours This course is intended for This basic course is for business data analysts who want to profile and assess data using Information Analyzer, also data quality analysts who need to measure data quality. Overview Analyze data structures to determine agreement with documented metadataDiscover data anomaliesIdentify invalid and incomplete data valuesDetermine potential primary keys to table structuresAdd business meaning to dataProduce deliverables that can be used by business users and ETL developersConfigure Information AnalyzerAdminister the Information Analyzer environmentUnderstand security considerations around data analysisUnderstand the methodology supporting data analysisUse Information Analyzer to analyze data content and structureUse Information Analyzer to construct data rules and utilize IBM-supplied data rule templates In this course, you will learn how to use the IBM InfoSphere suite to analyze data and report results to business users. Course Outline Information Analysis concepts Information Server overview Information Analyzer overview Information Analyzer Setup Column analysis Concepts Basic data profiling techniques in practice Data profiling techniques Primary key analysis Concepts Basic data profiling techniques in practice Foreign key and cross domain analysis Concepts Basic data profiling techniques in practice Baseline analysis Reporting and publishing Extending the meta data using Information Governance Catalog and Information Analyzer Data Rules and Metrics Additional course details: Nexus Humans KM803 IBM Information Analyzer Essentials v11.5 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 KM803 IBM Information Analyzer Essentials v11.5 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 course is suited to marketeers, business analysts, and researchers who are interested in increasing their statistical knowledge. Overview After attending this course, delegates will understand how statistics can be used to provide valuable insight into their business, and be able to apply statistical methods to solve business problems. On returning to work delegates will immediately be able to make a difference to the way that their organisations make decisions. This course covers the statistical methods that analysts need to move from simple reporting on business problems to extracting insight to solve business problems. Course Outline The course will explore the following topics through a series of lectures and workshops: Summary statistics for both continuous data and categorical data Using and reporting confidence intervals Using hypothesis tests to answer business questions Using correlations to explore data relationships Simple prediction models Analysing categorical data Additional course details: Nexus Humans Data-driven Business Using Statistical Analysis 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 Data-driven Business Using Statistical Analysis 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 5 Days 30 CPD hours This course is intended for This course is designed for business analysts. Overview After completing this course, you should be able to:Describe the benefits of implementing an Operational Decision Manager solution, and the collaboration that is required between the business and development teamsIdentify the main user roles that are involved in designing and developing an Operational Decision Manager solution, and the tasks that are associated with each roleExplain modeling concepts and the UML notation that is relevant to modeling for business rules and eventsDefine and implement object models for business rulesSet up the rule authoring environment in Designer by working with decision services and synchronizing across development and business environmentsCustomize the vocabulary that is used in rulesDiscover and analyze business rules for implementationUse the Operational Decision Manager rule editors to author business rules and decision tablesRun tests and simulations in the Decision Center Enterprise console to validate decision logic and rule changesExplain governance issues and work with Operational Decision Manager features that support decision governance This course introduces business analysts to IBM Operational Decision Manager V8.7.1. You learn the concepts and skills that are necessary to capture, author, validate, and manage business rules with Operational Decision Manager. Course Outline Course introduction Introducing IBM Operational Decision Manager V8.7.1 Exercise: Operational Decision Manager in action Modeling for business rules Exercise: Building the model on paper Exercise: Implementing the model Understanding decision services Exercise: Setting up a decision service Working with the BOM Exercise: Working with the BOM Introducing Decision Center Exercise: Exploring the Decision Center Business console Exercise: Exploring the Decision Center Enterprise console Introducing rule authoring Exercise: Understanding the case study Discovering and analyzing rules Exercise: Discovering rules Exercise: Analyzing rules Working with conditions in rules Exercise: Working with conditions in rules Working with definitions in rules Exercise: Working with definitions in rules Writing complete rules Exercise: Writing complete rules Authoring decision tables and trees Exercise: Authoring decision tables and trees Exercise: Authoring rules: Putting it all together Running tests and simulations in the Enterprise console Exercise: Running tests and simulations in the Enterprise console Introducing decision governance Exercise: Working with the decision governance framework Course summary