5 Business Information Technology courses in London

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

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

In the past, popular thought treated artificial intelligence (AI) as if it were the domain of science fiction or some far-flung future. In the last few years, however, AI has been given new life. The business world has especially given it renewed interest. However, AI is not just another technology or process for the business to consider - it is a truly disruptive force.

Trade barriers are going up across the globe. And cybercrime is on the increase. The link between the two? The value of trade secrets. As countries become increasingly protectionist as regards international trade, so their IP law has been changing, with the result that companies that previously would have sought protection through patents are opting to go down the trade secret route instead. But is this a high-risk strategy? Technology is changing and this is having an impact on forms of commercial co-operation. Collaborative or open forms of innovation by their very nature involve the sharing of intellectual property (IP), and in many instances this IP is in the form of valuable confidential business information (ie, trade secrets). Little surprise, then, that trade secrets disputes have increased accordingly. At the same time, the changes in technology make trade secrets more vulnerable to attack, misappropriation, theft. So just how effective are the legal protections for trade secrets? How can organisations safeguard the value in their IP (increasingly, the single biggest line in their balance sheets)? This programme is designed to help you address these issues. Note: this is an indicative agenda, to be used as a starting point for a conversation between client and consultant, depending on the organisation's specific situation and requirements. This session is designed to give you a deeper understanding of: Emerging trends in trade secrets protection and exploitation The current situation in key jurisdictions Recent case law How leading companies are responding The importance of trade secret metadata Different external stakeholders and their interests Key steps for effective protection of trade secrets Note: this is an indicative agenda, to be used as a starting point for a conversation between client and consultant, depending on the organisation's specific situation and requirements. 1 What are trade secrets? Definitions Examples Comparison with other forms of IP (patents, confidential information, know-how, copyright) 2 Current trends The various changes taking place affecting trade secrets - legal changes, trade wars, cybercrime, technology, commercial practice The current position in the UK, Europe, USA, China, Japan, Russia Corporate best practice 3 Trade secret disputes - how to avoid them Trade secret policies, processes and systems Administrative, legal and technical protection mechanisms The role of employees The sharing of trade secrets with others 4 Trade secret disputes - how to manage them Causes Anatomy of a trade secret court case 'Reasonable particularity' 5 Related issues Insurance Tax authorities and investigations Investor relations 6 Trade secret asset management roadmap Maturity ladder First steps Pilot projects

This one-day programme explores the role of intellectual property (IP) in relation to innovation and creativity. It examines the different forms as well as the key processes, together with some of the oddities and idiosyncrasies of the legal regime that protects IP. It delves into the various IP models you should be aware of as well as key IP facts and figures and current IP trends across the global economy. This session is designed to give you a deeper understanding of: The main forms of intellectual property The importance of IP - both to your organisation and to the wider economy The key processes in the creation, commercial exploitation, and legal protection of IP The different models for the use of IP Some more advanced concepts for reviewing, valuing and managing IP 1 Main forms of intellectual property (IP) Patents Trademarks Copyright Design Trade secrets 2 Global IP business context Global IP facts and figures Figures for key jurisdictions Analysis of a company using IP data IP trends Overview of the key entities in the IP sector 3 Key IP processes IP creation IP portfolio management IP enforcement IP exploitation IP risk management 4 IP models IP models explained IP licensing IP litigation 5 IP concepts The IP maturity ladder Relative IP value and risk Axis of control 6 IP as an asset class Costs Valuation Financial perspective