3082 Courses in London

Strategic Thinking (In-Person) The goal of this course is to provide you with the building blocks and the motivation to develop the critical skill of strategic thinking. The participants will consider a four-part model that distinguishes strategic thinking from strategic planning and managing. With that understanding, you will investigate the critical components of strategic thinking and how to apply it effectively. What You Will Learn You will learn how to: Define strategic thinking and distinguish it from strategic planning and management Explain a high-level approach to gaining strategic thinking skills Integrate other interpersonal skills, such as self-awareness, systems thinking, leadership, constructive conflict, and collaboration, into the fabric of strategic thinking skills Select appropriate techniques to apply strategic thinking in specific situations Recognize and emulate effective strategic thinking behaviors Getting Started Introductions Course structure Course goals and objectives Foundation Concepts Interactive event: Define Strategic Thinking (ST) Interactive event: Discuss relationship of ST with Strategic Planning, Management and Decision Making Strategic Level Framework - Tying it all together Strategic thinking attributes Strategic Thinking Critical Success Factors Strategic Thinking Critical Success Factors - 5-part model Strategic Thinking and the Organization Critical Success Factors Model applied to an organization Tools Introduction (5): Environmental, 5 Forces, SWOT, Value Proposition, Integral Theory of Worldview Video: Fog of War Strategic Thinking and the Individual Critical Success Factors Model applied to an individual Tools Introduction (5): Thinking Styles, Six Thinking Hats, Reverse Thinking, Systems Thinking, Integral Theory of Worldview Strategic Thinking at the Interpersonal and Team Levels Emotional Intelligence - Self Awareness and Working With Others Team Leadership and Trust Constructive Conflict as the Gateway to Collaboration Interactive event: Testing the Models - Challenge Perspective; What's Missing Applying the critical skill of Strategic Thinking Worldview: Team versus client Trusted Advisor Interactive event: Doing what is asked (Case study, wherein participants review the default case scenario prepared for this workshop and add specific details to make the scenario more relevant to their experiences / needs. Teams develop an action plan for applying ST concepts and techniques they have learned here to the situation, then compare and contrast results.)

Emotional Intelligence: In-House Training Emotional Intelligence is a set of emotional and social skills that collectively establish how well we: Perceive and express ourselves Develop and maintain social relationships Cope with challenges Use emotional information in an effective and meaningful way It is a skill set that transfers across all categories of relationships. It is also a predictor of success - both in life and at work. This highly-interactive course delivers a practical approach to developing, improving, and sustaining effective and mutually beneficial relationships. The design of the course involves individual reflection and paired activities, interwoven with small and large group interactions. The EQ-i 2.0® assessment reports will be debriefed over the course of the two days. In addition, participants will delve into their personal strengths and blind spots, and will explore topics including: the neuroscience of emotion, the connection between empathy and performance, and how communication styles impact our perceptions of self and other. Role-play activities give participants the opportunity to try out new behaviors and techniques. The program includes: A personal behavioral profile, the results of which you will bring to your training 2-day highly interactive workshop and experiential learning Optional professional coaching activities initiated in class that can continue over the four months after class ends What you will Learn Recognize your interpersonal strengths and potential blind spots regarding Emotional Intelligence Identify the five domains within the EQ-i 2.0 assessment model Summarize what neuroscience research has discovered about emotions and actions Recognize ways that human beings are physiologically impacted by stress Articulate ways to develop and maintain strong working relationships Describe how emotional intelligence translates into high performance Make use of the EI model and associated competencies Employ strategies for enhancing leadership through Emotional Intelligence Foundation Concepts The biology of emotion Why Emotional Intelligence matters The impact of EI on performance The EQ-I 2.0 Model Overview of the EQ-i 2.0 framework Exploring your report Balancing your EI domains Self: Awareness and Sensitivity Self-awareness and empathy Perception vs. reality Acting by choice, not impulse Other: Communication and Relationship-Building Elements of effective communication Communication styles Communication techniques Neuroscience and Behavioral Change Insights from social neuroscience Making a change

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

Emotional Intelligence (In-Person) Emotional Intelligence is a set of emotional and social skills that collectively establish how well we: Perceive and express ourselves Develop and maintain social relationships Cope with challenges Use emotional information in an effective and meaningful way It is a skill set that transfers across all categories of relationships. It is also a predictor of success - both in life and at work. This highly-interactive course delivers a practical approach to developing, improving, and sustaining effective and mutually beneficial relationships. The design of the course involves individual reflection and paired activities, interwoven with small and large group interactions. The EQ-i 2.0® assessment reports will be debriefed over the course of the two days. In addition, participants will delve into their personal strengths and blind spots, and will explore topics including: the neuroscience of emotion, the connection between empathy and performance, and how communication styles impact our perceptions of self and other. Role-play activities give participants the opportunity to try out new behaviors and techniques. The program includes: A personal behavioral profile, the results of which you will bring to your training 2-day highly interactive workshop and experiential learning Optional professional coaching activities initiated in class that can continue over the four months after class ends What you will Learn Recognize your interpersonal strengths and potential blind spots regarding Emotional Intelligence Identify the five domains within the EQ-i 2.0 assessment model Summarize what neuroscience research has discovered about emotions and actions Recognize ways that human beings are physiologically impacted by stress Articulate ways to develop and maintain strong working relationships Describe how emotional intelligence translates into high performance Make use of the EI model and associated competencies Employ strategies for enhancing leadership through Emotional Intelligence Getting Started Foundation Concepts The biology of emotion Why Emotional Intelligence matters The impact of EI on performance The EQ-I 2.0 Model Overview of the EQ-i 2.0 framework Exploring your report Balancing your EI domains Self: Awareness and Sensitivity Self-awareness and empathy Perception vs. reality Acting by choice, not impulse Other: Communication and Relationship-Building Elements of effective communication Communication styles Communication techniques Neuroscience and Behavioral Change Insights from social neuroscience Making a change Summary and Next Steps

About this Virtual Instructor Led Training (VILT) The energy industry has started its journey to be more data centric by embracing the industry 4.0 concept. As a result, data management - which was considered until recently as a back-office service to support geoscience, reservoir management, engineering, production and maintenance - is now given the spotlight! To become an active stakeholder in this important transition in E&P data management, it is necessary to understand the new technical opportunities offered by the Cloud, Artificial Intelligence and how data governance can pave the way towards more reliable and resilient processes within E&P domain. Several key questions that need to be addressed: Why place more focus on data assets? Is data management just about serving geoscientists or engineers with fresh data? What is the value of data management in the E&P sector for decision making? How to convince the data consumers that the data we provide is reliable? Is the data architecture of my organization appropriate and sustainable? The purpose of this 5 half-day Virtual Instructor Led Training (VILT) course is to present the data challenges facing the energy organizations today and see how they practically solve them. The backbone of this course is based on the DAMA Book of Knowledge for Data Management. The main data management activities are described in sequence with a particular focus on recent technological developments. Training Objectives Upon completion of this VILT course, the participants will be able to: Understand why the data asset is now considered as a main asset by energy organizations Appreciate the importance of data governance and become an active stakeholder of it Understand the architecture and implementation of data structure in their professional environment Get familiarized with the more important data management activities such as data security and data quality Integrate their subsurface and surface engineering skills with the data managements concepts This VILT course is unique on several points: All notions are explained by some short presentations. For each of them, a set of video, exercises, quizzes will be provided to help develop an engaging experience between the trainer and the participants A pre-course questionnaire to help the trainer focus on the participants' needs and learning objectives A detailed reference manual A lexicon of terms for data-management Limited class size to encourage the interactivity Target Audience This VILT course is intended for: Junior/new data managers Geoscientists Reservoir engineers Producers Maintenance specialists Construction specialists Human resources Legal Course Level Basic or Foundation Training Methods The VILT course will be delivered online in 5 half-days consisting 4 hours per day, with 2 breaks of 10 minutes per day. Course Duration: 5 half-day sessions, 4 hours per session (20 hours in total). Trainer Your expert course leader is a geologist by education who has dedicated his career to subsurface data management services. In 2016, he initiated a tech startup dedicated to Data Management using Artificial Intelligence (AI) tools. He is heavily involved in developing business plans, pricing strategies, partnerships, marketing and SEO, and is the co-author of several Machine Learning publications. He also delivers training on Data Management and Data Science to students and professionals. Based in France, he was formerly Vice President, Sales & Marketing at CGG where he was in charge of the Data Management Services strategy, Sales Manager at Spie O&G Services where he initiated the Geoscience technical assistance activities and Product Manager of interactive seismic inversion software design and marketing at Paradigm.       POST TRAINING COACHING SUPPORT (OPTIONAL) To further optimise your learning experience from our courses, we also offer individualized 'One to One' coaching support for 2 hours post training. We can help improve your competence in your chosen area of interest, based on your learning needs and available hours. This is a great opportunity to improve your capability and confidence in a particular area of expertise. It will be delivered over a secure video conference call by one of our senior trainers. They will work with you to create a tailor-made coaching program that will help you achieve your goals faster. Request for further information about post training coaching support and fees applicable for this. Accreditions And Affliations

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