177 Business Analyst courses

Practical Sales Skills 1 Day Workshop in Birmingham

Practical Sales Skills 1 Day Workshop in Reading

Practical Sales Skills 1 Day Workshop in Watford

Practical Sales Skills 1 Day Workshop in Maidstone

Practical Sales Skills 1 Day Workshop in Glasgow

Practical Sales Skills 1 Day Workshop in Cirencester

Practical Sales Skills 1 Day Workshop in Bolton

ISTQB® FOUNDATION TRAINING COURSE (2 persons minimum) The aim of this course is to provide you with the knowledge and skills to pass an exam certifying you as an ISTQB® Certified Tester - Foundation Level. Most organisations require this certification as a minimum skill requirement for software testers. In this course you will learn a standardized approach to software testing that will be immediately applicable to your projects. In order to get the certification you will be required to pass a 60-minute exam. Our trainers will fully prepare you by employing scenarios that mirror the exam questions, and by focusing course delivery with a balance of theory and practice. Target group: Functional Tester, Agile Tester, User Acceptance Tester, Test Automation Specialist, Performance Testing Specialist, Testing Team Lead, Test Manager, Business analyst Prerequisites: There are no specific prerequisites for this course. This course is suitable for anyone involved in software testing. Duration: 3 days. Training objectives: Learn aspects of test planning, estimation, monitoring and control. Understand and use international standards and terminology. Understand and implement effective testing techniques. Be well prepared for the exam. Identify the missing testing skills for the career development purposes. This course covers the following areas: Fundamentals of software testing Testing throughout the life cycle (software development models, test levels, test types) Test design techniques (e.g. specification-based or black-box techniques, structure-based or white-box techniques) Static testing (static testing techniques, review process, tool-assisted static analysis) Test management (test organisation, test planning and estimation, test progress monitoring and control, risks) Tools to support testing (types, benefits and risks) Language: English

Business Intelligence Business Intelligence (BI) refers to a set of technology-based techniques, applications, and practices used to aggregate, analyze, and present business data. BI practices provide historical and current views of vast amounts of data and generate predictions for business operations. The purpose of Business Intelligence is the support of better business decision making. This course provides an overview of the technology and application of BI and how it can be used to improve corporate performance. What you will Learn You will learn how to: Specify a data warehouse schema Identify the data and visualization to be used for data mining and Business Intelligence Design a Business Intelligence user interface Getting Started Introductions Agenda Expectations Foundation Concepts The challenge of decision making What is Business Intelligence? The Business Intelligence value proposition Business Intelligence taxonomy Business Intelligence management issues Sources of Business Intelligence Data warehousing Data and information Information architecture Defining the data warehouse and its relationships Facts and dimensions Modeling, meta-modeling, and schemas Alternate architectures Building the data warehouse Extracting Transforming Loading Setting up the data and relationships Dimensions and the Fact Table Implementing many-to-many relationships in data warehouse Data marts Online Analytical Processing (OLAP) What is OLAP? OLAP and OLTP OLAP functionality Multi-dimensions Thinking in more than two dimensions What are the possibilities? OLAP architecture Cubism Tools OLAP variations - MOLAP, ROLAP, HOLAP BI using SOA Applications of Business Intelligence Applying BI through OLAP Enterprise Resource Planning and CRM Business Intelligence and financial information Business Intelligence User Interfaces and Presentations Data access Push-pull data access Types of decision support systems Designing the front end Presentation formats Dashboards Types of dashboards Common dashboard features Briefing books and scorecards Querying and Reporting Reporting emphasis Retrofitting Talking back Key Performance Indicators Report Definition and Visualization Typical reporting environment Forms of visualization Unconstrained views Data mining What is in the mine? Applications for data mining Data mining architecture Cross Industry Standard Process for Data Mining (CISP-DM) Data mining techniques Validation The Business Intelligence User Experience The business analyst role Business analysis and data analysis Five-step approach Cultural impact Identifying questions Gathering information Understand the goals The strategic Business Intelligence cycle Focus of Business Intelligence Design for the user Iterate the access Iterative solution development process Review and validation questions Basic approaches Building ad-hoc queries Building on-demand self-service reports Closed loop Business Intelligence Coming attractions - future of Business Intelligence Best practices in Business Intelligence

Business Intelligence: In-House Training Business Intelligence (BI) refers to a set of technology-based techniques, applications, and practices used to aggregate, analyze, and present business data. BI practices provide historical and current views of vast amounts of data and generate predictions for business operations. The purpose of Business Intelligence is the support of better business decision making. This course provides an overview of the technology and application of BI and how it can be used to improve corporate performance. What you will Learn You will learn how to: Specify a data warehouse schema Identify the data and visualization to be used for data mining and Business Intelligence Design a Business Intelligence user interface Getting Started Introductions Agenda Expectations Foundation Concepts The challenge of decision making What is Business Intelligence? The Business Intelligence value proposition Business Intelligence taxonomy Business Intelligence management issues Sources of Business Intelligence Data warehousing Data and information Information architecture Defining the data warehouse and its relationships Facts and dimensions Modeling, meta-modeling, and schemas Alternate architectures Building the data warehouse Extracting Transforming Loading Setting up the data and relationships Dimensions and the Fact Table Implementing many-to-many relationships in data warehouse Data marts Online Analytical Processing (OLAP) What is OLAP? OLAP and OLTP OLAP functionality Multi-dimensions Thinking in more than two dimensions What are the possibilities? OLAP architecture Cubism Tools OLAP variations - MOLAP, ROLAP, HOLAP BI using SOA Applications of Business Intelligence Applying BI through OLAP Enterprise Resource Planning and CRM Business Intelligence and financial information Business Intelligence User Interfaces and Presentations Data access Push-pull data access Types of decision support systems Designing the front end Presentation formats Dashboards Types of dashboards Common dashboard features Briefing books and scorecards Querying and Reporting Reporting emphasis Retrofitting Talking back Key Performance Indicators Report Definition and Visualization Typical reporting environment Forms of visualization Unconstrained views Data mining What is in the mine? Applications for data mining Data mining architecture Cross Industry Standard Process for Data Mining (CISP-DM) Data mining techniques Validation The Business Intelligence User Experience The business analyst role Business analysis and data analysis Five-step approach Cultural impact Identifying questions Gathering information Understand the goals The strategic Business Intelligence cycle Focus of Business Intelligence Design for the user Iterate the access Iterative solution development process Review and validation questions Basic approaches Building ad-hoc queries Building on-demand self-service reports Closed loop Business Intelligence Coming attractions - future of Business Intelligence Best practices in Business Intelligence