469 Courses delivered Online

Duration 5 Days 30 CPD hours This course is intended for The primary audience for this course are Application Consultants, Business Analysts, Business Process Owners/Team Leads/Power Users, Data Consultants /Managers, Program/Project Managers, and Solution Architects. Overview Gain hands-on experience in running SAP BusinessObjects BI tools on top of SAP NetWeaver BW data In this course, students are provided with detailed knowledge on the integration for reporting of SAP BusinessObjects BI Platform 4.x with SAP NetWeaver 7.x. Overview of SAP BusinessObjects Business Intelligence(BI) 4.x and SAP NetWeaver Describing SAP BusinessObjects 4.x Semantic Layer in SAP BusinessObjects BI 4.x and Data Connectivity Describing Semantic Layer Technology Creating a Universe with the Information Design Tool SAP BusinessObjects Analysis, Edition for Microsoft Office and SAP NetWeaver BW Creating a Workbook in SAP BusinessObjects Analysis, Edition for Microsoft Office Creating a Workbook with SAP BusinessObjects Analysis, Edition for Microsoft Office and SAP BW SAP BusinessObjects Analysis, Edition for OLAP and SAP NetWeaver BW Creating a Workspace with SAP BusinessObjects Analysis, Edition for OLAP Creating a Workspace in SAP BusinessObjects Analysis, Edition for OLAP Based on a BW Query SAP BusinessObjects Design Studio and SAP NetWeaver BW Creating an Analytical Application in SAP BusinessObjects Design Studio Creating an Analytical Application with Scripting SAP BusinessObjects Dashboards and SAP NetWeaver BW Creating a Dashboard with SAP BusinessObjects Dashboards Creating a Dashboard with BEx Query SAP Crystal Reports and SAP NetWeaver BW Creating a Report with SAP Crystal Reports for Enterprise Creating a Report with SAP Crystal Reports 2013 Creating a Report with SAP Crystal Reports 2013 and SAP NetWeaver BW Differentiating SAP Crystal Reports 2013 and SAP Crystal Reports for Enterprise SAP BusinessObjects Web Intelligence and SAP NetWeaver BW Creating a Web Intelligence Document Creating a Web Intelligence Document for SAP NetWeaver BW SAP BusinessObjects Explorer and SAP NetWeaver BW Creating an SAP BusinessObjects Explorer Information Space Describing Data Connectivity between SAP BusinessObjects Explorer and SAP NetWeaver BW Information Distribution Reporting with Mobile Devices Creating Publications with SAP Crystal Reports and SAP BusinessObjects Web Intelligence Integrating BI Content with SAP NetWeaver Enterprise Portal

Duration 3 Days 18 CPD hours This course is intended for The primary audience for this course are Application Consultants, Business Analysts, Business Process Owners/Team Leads/Power Users, Solution Architects, and System Architects. Overview Describe the SAP BusinessObjects Business Intelligence tools.Learn about the use cases and get an overview of basic functions of the most important BusinessObjects reporting tools. In this course, students describe the SAP BusinessObjects Business Intelligence tools and learn about the use cases by getting an overview of basic functions of the most important BusinessObjects reporting tools. Overview of SAP BusinessObjects Business Intelligence (BI) 4.1 Describing SAP Analytics Solutions Identifying the Components of SAP BusinessObjects 4.1 Semantic Layer in SAP BusinessObjects BI 4.1 Describing Semantic Layer Technology Creating a Universe in the Information Design Tool SAP Crystal Reports Creating a Report in SAP Crystal Reports for Enterprise Creating a Report in SAP Crystal Reports 2013 Differentiating SAP Crystal Reports 2013 and SAP Crystal Reports for Enterprise SAP BusinessObjects Web Intelligence Creating Web Intelligence Documents in SAP BusinessObjects Web Intelligence SAP BusinessObjects Analysis, Edition for Microsoft Office Creating a Workbook in SAP BusinessObjects Analysis, Edition for Microsoft Office SAP BusinessObjects Analysis, Edition for OLAP Creating a Workspace with SAP BusinessObjects Analysis, Edition for OLAP SAP BusinessObjects Design Studio 1.2 Creating an Analytical Application in SAP BusinessObjects Design Studio 1.2 SAP BusinessObjects Dashboards Creating a Dashboard with SAP BusinessObjects Dashboards SAP BusinessObjects Explorer Creating an SAP BusinessObjects Explorer Information Space SAP Lumira and SAP Predictive Analysis Visualizing Data in SAP Lumira Forecasting in SAP Predictive Analysis Additional course details: Nexus Humans SAPBI Introduction to SAP BusinessObjects BI Solutions 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 SAPBI Introduction to SAP BusinessObjects BI Solutions 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 in an intermediate and beyond-level course is geared for experienced Python developers looking to delve into the exciting field of Natural Language Processing. It is ideally suited for roles such as data analysts, data scientists, machine learning engineers, or anyone working with text data and seeking to extract valuable insights from it. If you're in a role where you're tasked with analyzing customer sentiment, building chatbots, or dealing with large volumes of text data, this course will provide you with practical, hands on skills that you can apply right away. Overview This course combines engaging instructor-led presentations and useful demonstrations with valuable hands-on labs and engaging group activities. Throughout the course you'll: Master the fundamentals of Natural Language Processing (NLP) and understand how it can help in making sense of text data for valuable insights. Develop the ability to transform raw text into a structured format that machines can understand and analyze. Discover how to collect data from the web and navigate through semi-structured data, opening up a wealth of data sources for your projects. Learn how to implement sentiment analysis and topic modeling to extract meaning from text data and identify trends. Gain proficiency in applying machine learning and deep learning techniques to text data for tasks such as classification and prediction. Learn to analyze text sentiment, train emotion detectors, and interpret the results, providing a way to gauge public opinion or understand customer feedback. The Hands-on Natural Language Processing (NLP) Boot Camp is an immersive, three-day course that serves as your guide to building machines that can read and interpret human language. NLP is a unique interdisciplinary field, blending computational linguistics with artificial intelligence to help machines understand, interpret, and generate human language. In an increasingly data-driven world, NLP skills provide a competitive edge, enabling the development of sophisticated projects such as voice assistants, text analyzers, chatbots, and so much more. Our comprehensive curriculum covers a broad spectrum of NLP topics. Beginning with an introduction to NLP and feature extraction, the course moves to the hands-on development of text classifiers, exploration of web scraping and APIs, before delving into topic modeling, vector representations, text manipulation, and sentiment analysis. Half of your time is dedicated to hands-on labs, where you'll experience the practical application of your knowledge, from creating pipelines and text classifiers to web scraping and analyzing sentiment. These labs serve as a microcosm of real-world scenarios, equipping you with the skills to efficiently process and analyze text data. Time permitting, you?ll also explore modern tools like Python libraries, the OpenAI GPT-3 API, and TensorFlow, using them in a series of engaging exercises. By the end of the course, you'll have a well-rounded understanding of NLP, and will leave equipped with the practical skills and insights that you can immediately put to use, helping your organization gain valuable insights from text data, streamline business processes, and improve user interactions with automated text-based systems. You?ll be able to process and analyze text data effectively, implement advanced text representations, apply machine learning algorithms for text data, and build simple chatbots. Launch into the Universe of Natural Language Processing The journey begins: Unravel the layers of NLP Navigating through the history of NLP Merging paths: Text Analytics and NLP Decoding language: Word Sense Disambiguation and Sentence Boundary Detection First steps towards an NLP Project Unleashing the Power of Feature Extraction Dive into the vast ocean of Data Types Purification process: Cleaning Text Data Excavating knowledge: Extracting features from Texts Drawing connections: Finding Text Similarity through Feature Extraction Engineer Your Text Classifier The new era of Machine Learning and Supervised Learning Architecting a Text Classifier Constructing efficient workflows: Building Pipelines for NLP Projects Ensuring continuity: Saving and Loading Models Master the Art of Web Scraping and API Usage Stepping into the digital world: Introduction to Web Scraping and APIs The great heist: Collecting Data by Scraping Web Pages Navigating through the maze of Semi-Structured Data Unearth Hidden Themes with Topic Modeling Embark on the path of Topic Discovery Decoding algorithms: Understanding Topic-Modeling Algorithms Dialing the right numbers: Key Input Parameters for LSA Topic Modeling Tackling complexity with Hierarchical Dirichlet Process (HDP) Delving Deep into Vector Representations The Geometry of Language: Introduction to Vectors in NLP Text Manipulation: Generation and Summarization Playing the creator: Generating Text with Markov Chains Distilling knowledge: Understanding Text Summarization and Key Input Parameters for TextRank Peering into the future: Recent Developments in Text Generation and Summarization Solving real-world problems: Addressing Challenges in Extractive Summarization Riding the Wave of Sentiment Analysis Unveiling emotions: Introduction to Sentiment Analysis Tools Demystifying the Textblob library Preparing the canvas: Understanding Data for Sentiment Analysis Training your own emotion detectors: Building Sentiment Models Optional: Capstone Project Apply the skills learned throughout the course. Define the problem and gather the data. Conduct exploratory data analysis for text data. Carry out preprocessing and feature extraction. Select and train a model. ? Evaluate the model and interpret the results. Bonus Chapter: Generative AI and NLP Introduction to Generative AI and its role in NLP. Overview of Generative Pretrained Transformer (GPT) models. Using GPT models for text generation and completion. Applying GPT models for improving autocomplete features. Use cases of GPT in question answering systems and chatbots. Bonus Chapter: Advanced Applications of NLP with GPT Fine-tuning GPT models for specific NLP tasks. Using GPT for sentiment analysis and text classification. Role of GPT in Named Entity Recognition (NER). Application of GPT in developing advanced chatbots. Ethics and limitations of GPT and generative AI technologies.

Duration 2 Days 12 CPD hours Overview Create heightened self-awareness and personal discovery Establish a space of mutual respect by adapting your communication Work with resistance to gain commitment and buy-in Recognize and enhance trust by leading from any position Distinguish among varying attitudes and behaviors to make your teams work as a stronger unit One of DISC?s most intriguing applications is leveraging behavioral identification and adaptability. This workshop will guide you on the path of heightened self-awareness and personal discovery. You can make this your cornerstone seminar, revealing your unique behavioral style blend and how to apply that knowledge prescriptively to others, based on their style blend; thus boosting communication effectiveness. Studies indicate that 92% of workplace conflict is the result of misunderstanding and communication breakdowns. Your entire organization can apply DISC?s prescriptive lessons of behavioral adaptability to reduce employee conflict and turnover, increase productivity, and optimize team performance. Private classes on this topic are available. We can address your organization?s issues, time constraints, and save you money, too. Contact us to find out how. 1. Understanding The World Of Disc What is DISC? Breaking down the four main styles: Dominant Influencing Steady Conscientious Determining behaviors to read styles: Indirect vs. Direct Open vs. Guarded 2. Building Stronger Self-Awareness Rating your own style Understanding the Platinum Rule Grid Breaking down your profile Natural Style Adapted Style 3. Reading And Adapting To Others? Behaviors Applying the Platinum Rule Identifying characteristics in others Communication strategies with others Adapting your approaches 4. Getting Buy-In From Others Selling yourself to others Getting buy-in from each profile Understanding the cycle of getting buy-in Assessing Solving Confirming agreement Assuring satisfaction 5. Trust-Based Leadership High performance leadership characteristics The key to listening to build trust Motivating strategies with each profile 6. Making Teams Work Understanding how we each make decisions Seeing the power in each style as a role Blending team styles for teamwork Reviewing the team needs to optimize effectiveness

Duration 3 Days 18 CPD hours This course is intended for This is an introductory level course, designed for web developers that need to upgrade core skills leveraging modern scripting and web development languages and standards. This course provides an excellent foundation for continued learning to gain in-demand skills in in-demand skills and technologies such as Angular, React, NodeJS, JQuery and more. This course can also be tuned for non-developers. Please inquire for details. Overview This 'skills-focused' course is approximately 50% hands-on, combining expert lecture, real-world demonstrations and group discussions with machine-based practical labs and exercises. Our instructors are highly experienced practitioners who bring years of current 'on-the-job' experience into every classroom. Working within in a hands-on learning environment guided by our expert team, attendees will explore: HTML5: How to effectively meet requirements using the full range of HTML5 semantic and structural elements To work with technologies such as web storage, application caching, and cross-domain messaging to improve performance and the user experience CSS: What features CSS3 supports and how they can be effectively used with HTML5 and other technologies To adapt to varying degrees of browser support for HTML5 and CSS3 JavaScript: What JavaScript is, how it relates to other programming languages, and how to script your web pages with it To traverse and manipulate the DOM and handle events in ways that work in all browsers To work with closures and prototypes and other exotic features of JavaScript Debugging What is needed to effectively debug these web technologies How to use both browser-based and proxy-based debuggers and tools Introduction to HTML5, CSS3 & JavaScript is geared for developers who need to understand the latest web technologies and responsive design practices central to targeting the entire spectrum of user platforms and browsers. This jumpstart style course provides a balanced mixture of theory and practical labs designed to take students through HTML5, CSS3 and JavaScript. Students who attend this course will leave this course armed with the new skills to begin to design, implement, and deploy robust, flexible, and safe web applications HTML Refresher HTML Review Introduction to HTML5 Introduction to CSS CSS Basics CSS3 Overview CSS3 Advanced Selectors CSS3 Visual Effects Introduction to JavaScript JavaScript Basics Debugging Tools JavaScript Functions JavaScript Arrays, Math and Date JavaScript Event Handling and the DOM Object-Oriented JavaScript

Duration 3 Days 18 CPD hours This course is intended for This introductory-level course is for experienced application developers new to MongoDB. Overview This course is approximately 50% hands-on lab to lecture ratio, combining engaging expert lessons, demos and group discussions with real-world, skills-focused machine-based labs and exercises. Working in a hands-on learning environment, guided by our expert team, you'll explore: Storage Basics MongoDB Document Model MongoDB Setup CRUD: Basics through Advanced Concepts Performance: Basics through Advanced Concepts Aggregation: Basics through Advanced Concepts Replication: Basics through Advanced Concepts Sharding: Basics through Advanced Concepts Schema Design Security Basics, Authentication & Authorization Application Development and Drivers Geared for experienced developers, Introduction to MongoDB for Developers is a comprehensive course that provides you with hands-on experience with the MongoDB query language, aggregation framework, data modeling, indexes, drivers, basic performance tuning, high availability and scaling. Throughout the course, you?ll explore the MongoDB Atlas database environment in detail, gaining job-ready skills you can put right to work after class. Storage Basics What is a Storage Engine? WiredTiger Storage Engine In-Memory Storage Engine Encrypted Storage Engine MongoDB Document Model JSON and BSON MongoDB Data Types MongoDB Setup Atlas Setup / Local MongoDB Setup CRUD Basics Insert Command Find Command Query Operators Remove Command Updating Documents CRUD Advanced Bulk Writes Retryable Writes Find and Modify Transactions Performance Basics Indexes Aggregation Basics Aggregation Pipeline Concepts Aggregation Pipeline Stages Aggregation Pipeline Expressions Aggregation Advanced $lookup stage $graphLookup stage $expr operator Faceted Search Type Conversions Advanced Expression Operators Date Expression Operators Expression Variables Aggregation Pipeline Optimizations Aggregation in a Sharded Cluster Replication Basics MongoDB Replica Sets Replica Set Use Cases Replication Mechanics Replication Advanced Using Write Concern to Tune Durability Semantics Using Read Concern to Tune Read Isolation Using Read Preference Replica Set Tag Sets Sharding Basics Sharding Concepts When to Shard What is a Shard Key? Zoned Sharding / MongoDB Atlas Global Clusters Sharding Advanced Components of a Sharded Cluster Sharding Mechanics Choosing a Good Shard Key Schema Design Schema Design Core Concepts Common Patterns Security Basics Authentication & Authorization Network Encryption Encryption at Rest Auditing

Duration 3 Days 18 CPD hours This course is intended for If you have worked in C++ but want to learn how to make the most of this language, especially for large projects, this course is for you. Overview By the end of this course, you'll have developed programming skills that will set you apart from other C++ programmers. After completing this course, you will be able to: Delve into the anatomy and workflow of C++ Study the pros and cons of different approaches to coding in C++ Test, run, and debug your programs Link object files as a dynamic library Use templates, SFINAE, constexpr if expressions and variadic templates Apply best practice to resource management This course begins with advanced C++ concepts by helping you decipher the sophisticated C++ type system and understand how various stages of compilation convert source code to object code. You'll then learn how to recognize the tools that need to be used in order to control the flow of execution, capture data, and pass data around. By creating small models, you'll even discover how to use advanced lambdas and captures and express common API design patterns in C++. As you cover later lessons, you'll explore ways to optimize your code by learning about memory alignment, cache access, and the time a program takes to run. The concluding lesson will help you to maximize performance by understanding modern CPU branch prediction and how to make your code cache-friendly. Anatomy of Portable C++ Software Managing C++ Projects Writing Readable Code No Ducks Allowed ? Types and Deduction C++ Types Creating User Types Structuring our Code No Ducks Allowed ? Templates and Deduction Inheritance, Polymorphism, and Interfaces Templates ? Generic Programming Type Aliases ? typedef and using Class Templates No Leaks Allowed ? Exceptions and Resources Exceptions in C++ RAII and the STL Move Semantics Name Lookup Caveat Emptor Separation of Concerns ? Software Architecture, Functions, and Variadic Templates Function Objects and Lambda Expressions Variadic Templates The Philosophers' Dinner ? Threads and Concurrency Synchronous, Asynchronous, and Threaded Execution Review Synchronization, Data Hazards, and Race Conditions Future, Promises, and Async Streams and I/O File I/O Implementation Classes String I/O Implementation I/O Manipulators Making Additional Streams Using Macros Everybody Falls, It's How You Get Back Up ? Testing and Debugging Assertions Unit Testing and Mock Testing Understanding Exception Handling Breakpoints, Watchpoints, and Data Visualization Need for Speed ? Performance and Optimization Performance Measurement Runtime Profiling Optimization Strategies Cache Friendly Code

Duration 3 Days 18 CPD hours This course is intended for This is an introductory-level course designed to teach experienced systems administrators how to install, maintain, monitor, troubleshoot, optimize, and secure Hadoop. Previous Hadoop experience is not required. Overview Working within in an engaging, hands-on learning environment, guided by our expert team, attendees will learn to: Understand the benefits of distributed computing Understand the Hadoop architecture (including HDFS and MapReduce) Define administrator participation in Big Data projects Plan, implement, and maintain Hadoop clusters Deploy and maintain additional Big Data tools (Pig, Hive, Flume, etc.) Plan, deploy and maintain HBase on a Hadoop cluster Monitor and maintain hundreds of servers Pinpoint performance bottlenecks and fix them Apache Hadoop is an open source framework for creating reliable and distributable compute clusters. Hadoop provides an excellent platform (with other related frameworks) to process large unstructured or semi-structured data sets from multiple sources to dissect, classify, learn from and make suggestions for business analytics, decision support, and other advanced forms of machine intelligence. This is an introductory-level, hands-on lab-intensive course geared for the administrator (new to Hadoop) who is charged with maintaining a Hadoop cluster and its related components. You will learn how to install, maintain, monitor, troubleshoot, optimize, and secure Hadoop. Introduction Hadoop history and concepts Ecosystem Distributions High level architecture Hadoop myths Hadoop challenges (hardware / software) Planning and installation Selecting software and Hadoop distributions Sizing the cluster and planning for growth Selecting hardware and network Rack topology Installation Multi-tenancy Directory structure and logs Benchmarking HDFS operations Concepts (horizontal scaling, replication, data locality, rack awareness) Nodes and daemons (NameNode, Secondary NameNode, HA Standby NameNode, DataNode) Health monitoring Command-line and browser-based administration Adding storage and replacing defective drives MapReduce operations Parallel computing before MapReduce: compare HPC versus Hadoop administration MapReduce cluster loads Nodes and Daemons (JobTracker, TaskTracker) MapReduce UI walk through MapReduce configuration Job config Job schedulers Administrator view of MapReduce best practices Optimizing MapReduce Fool proofing MR: what to tell your programmers YARN: architecture and use Advanced topics Hardware monitoring System software monitoring Hadoop cluster monitoring Adding and removing servers and upgrading Hadoop Backup, recovery, and business continuity planning Cluster configuration tweaks Hardware maintenance schedule Oozie scheduling for administrators Securing your cluster with Kerberos The future of Hadoop

Duration 1 Days 6 CPD hours This course is intended for This course is intended for data warehouse engineers, data platform engineers, and architects and operators who build and manage data analytics pipelines. Completed either AWS Technical Essentials or Architecting on AWS Completed Building Data Lakes on AWS Overview In this course, you will learn to: Compare the features and benefits of data warehouses, data lakes, and modern data architectures Design and implement a data warehouse analytics solution Identify and apply appropriate techniques, including compression, to optimize data storage Select and deploy appropriate options to ingest, transform, and store data Choose the appropriate instance and node types, clusters, auto scaling, and network topology for a particular business use case Understand how data storage and processing affect the analysis and visualization mechanisms needed to gain actionable business insights Secure data at rest and in transit Monitor analytics workloads to identify and remediate problems Apply cost management best practices In this course, you will build a data analytics solution using Amazon Redshift, a cloud data warehouse service. The course focuses on the data collection, ingestion, cataloging, storage, and processing components of the analytics pipeline. You will learn to integrate Amazon Redshift with a data lake to support both analytics and machine learning workloads. You will also learn to apply security, performance, and cost management best practices to the operation of Amazon Redshift. Module A: Overview of Data Analytics and the Data Pipeline Data analytics use cases Using the data pipeline for analytics Module 1: Using Amazon Redshift in the Data Analytics Pipeline Why Amazon Redshift for data warehousing? Overview of Amazon Redshift Module 2: Introduction to Amazon Redshift Amazon Redshift architecture Interactive Demo 1: Touring the Amazon Redshift console Amazon Redshift features Practice Lab 1: Load and query data in an Amazon Redshift cluster Module 3: Ingestion and Storage Ingestion Interactive Demo 2: Connecting your Amazon Redshift cluster using a Jupyter notebook with Data API Data distribution and storage Interactive Demo 3: Analyzing semi-structured data using the SUPER data type Querying data in Amazon Redshift Practice Lab 2: Data analytics using Amazon Redshift Spectrum Module 4: Processing and Optimizing Data Data transformation Advanced querying Practice Lab 3: Data transformation and querying in Amazon Redshift Resource management Interactive Demo 4: Applying mixed workload management on Amazon Redshift Automation and optimization Interactive demo 5: Amazon Redshift cluster resizing from the dc2.large to ra3.xlplus cluster Module 5: Security and Monitoring of Amazon Redshift Clusters Securing the Amazon Redshift cluster Monitoring and troubleshooting Amazon Redshift clusters Module 6: Designing Data Warehouse Analytics Solutions Data warehouse use case review Activity: Designing a data warehouse analytics workflow Module B: Developing Modern Data Architectures on AWS Modern data architectures

Duration 3 Days 18 CPD hours This course is intended for The Foundation course is designed for individuals who want to gain an overview of Business Analysis (Business Analysts, Requirements Engineers, Product manager, Product Owner, Chief Product Owner, Service Manager, Service Owner, Project manager, Consultants) Overview Students should be able to demonstrate knowledge and understanding of business analysis principles and techniques. Key areas are: the role and competencies of a business analyst strategy analysis business system and business process modelling stakeholder analysis investigation and modelling techniques requirements engineering business case development The business analyst role analyzes, understands and manages the requirements in a customer-supplier relationship and ensures that the right products are delivered. The Foundation Seminar gives a good introduction to the spectrum of this responsibility. Course Introduction Let?s Get to Know Each Other Course Overview Course Learning Objectives Course Structure Course Agenda Introduction to Business Analysis Structure and Benefits of Business Analysis Foundation Exam Details Business Analysis Certification Scheme What is Business Analysis? Intent and Context Origins of business analysis The development of business analysis The scope of business analysis work Taking a holistic approach The role and responsibilities of the business analyst The competencies of a Business Analyst Personal qualities Business knowledge Professional techniques The development of competencies Strategy Analysis The context for strategy The defiition of strategy Strategy development External environmental analysis Internal invironmental analysis SWOT analysis Executing strategy Business Analysis Process Model An approach to problem solving Stages of the business analysis process model Objectives of the process model stages Procedures for each process model stage Techniques used within each process model stage Investigation Techniques Interviews Observation Workshops Scenarios Prototyping Quantitative approaches Documenting the current situation Stakeholder Analysis and Management Stakeholder categories and identification Analysing stakeholders Stakeholder management strategies Managing stakeholders Understanding stakeholder perspectives Business activity models Modelling Business Processes Organizational context An altrnative view of an organization The organizational view of business processes Value propositions Process models Analysing the as-is process model Improving business processes (to-be business process) Defining the Solution Gab analysis Introduction to Business Architecture Definition to Business Architecture Business Architecture techniques Business and Financial Case The business case in the project lifecycle Identifying options Assessing project feasibility Structure of a business case Investment appraisal Establishing the Requirements A framework for requirements engineering Actors in requirements engineering Requirements elicitation Requirements analysis Requirements validation Documenting and Managing the Requirements The requirements document The requirements catalogue Managing requirements Modelling the Requirements Modelling system functions Modelling system data Delivering the Requirements Delivering the solution Context Lifecycles Delivering the Business Solution BA role in the business change lifecycle Design stage Implementation stage Realization stage