This course provides you with the tools you need to put data to work: how to set up experiments, how to collect data, how to learn from data, and make decisions to how to navigate the organizational, legal, and ethical issues involved in data-based decision making. The program teaches widely-used frameworks of business analytics: biases, experimentation, descriptive analytics, prescriptive analytics, predictive analytics. Participants then implement the frameworks they have learned through assignments.
Recognize different types of biases that give way to bad decision making and learn how to overcome them.
Avoid bias in decision making by asking questions critical to your business and identifying the data needed to answer those questions.
Learn about the sources of data, the intermediary software services that can fetch those data into your database, and then assess the quality of the collected data.
Explain the reasons behind past events by analyzing and summarising data.
Predict future outcomes by choosing the appropriate machine learning algorithm to use in a business context.
Learn the implementation challenges of creating a data-driven organization.
Understand the ethics and regulatory issues involved in making decisions using data
This course is designed for managers and employees across different functions who are interested in implementing analytics projects at their organization. It provides business managers with the techniques needed to transform their organization into a data-driven organization. The assignments and cases in the program focus on interpreting the results of analysis and taking decisions based on those analyses
Decision traps.
Benefits of analytics.
What is data mining?
Web scraping.
Application Programming Interface (API).
What data can you find?
What do you think about the data you found?
Amazon and APIs.
Data cleaning.
Descriptive statistics.
Normal and not normal distributions.
Effect size and confidence intervals.
Be able to collect, clean, and describe the data you have.
What does Big Data mean to you?
Introduction to Big Data.
What is Big Data?
Four Vs of big data – volume, variety, velocity, and veracity.
Challenges for big data.
Big Data opportunities.
Identify what big data means to you and what you can do with it.
Design experiments to gather meaningful data to make data-driven decisions.
Machine learning vs hypothesis testing.
Machine learning in practice.
Machine learning algorithms.
Supervised machine learning.
Interpret an analysis.
Machine learning in the real world
What is prescriptive analytics?
Connecting predictive analytics to a business objective.
Deep dive into a business model.
Making a business decision
Risk aversion.
Diversification.
Implementation challenges.
Setting up the right infrastructure.
Big data strategy.
Personal data.
Privacy and Anonymization.
Hacking and insider threats.
Making customers comfortable.
Identify Organisational issues that you will need to consider when making decisions.
identify the legal and ethical issues behind the gathering, storing, and using data.
Employee engagement is largely a business difficulty that contemporary firms are increasingly dealing with, rather than solely an HR one. After a protracted lockdown, modern businesses now place a high focus on employee engagement and retention. You will discover what employee engagement is all about, how to measure it, and most crucially, how to create and implement successful engagement initiatives that have an influence on overall business performance, in this online learning course.
Microsoft SQL Server is a relational database management system developed by Microsoft. As a database server, it is a software product with the primary function of storing and retrieving data as requested by other software applications—which may run either on the same computer or on another computer across a network.
This conference provides an understanding of the essential fundamentals of corporate finance, strategy, financial management, budgeting and costing. Contemporary practical examples are presented together with the theoretical principles to make the theory come to life. The overriding objective of this conference is to present a number of integrated and powerful principles and best practices to help develop analytical skills and the decision-making capacity of the participants.
This advanced-level leadership course is aimed at giving you the skills you need to manage and lead people to an advanced level - focusing on six key areas of leadership - Communication, Innovation, Vision, Inspiration, Enabling, and Encouragement.
You will have the opportunity to test your current skills and be challenged and coached to become the best leader you can be. Using case studies and examples from great historical leaders, and the elite of the modern business world, we will investigate leadership and human behavioral patterns, look at changes in business trends, study human motivation and work on modern practical leadership tools and methodologies.
At every point in this course, you will be encouraged to participate in discussions, group work, practical exercises, meetings, and experiments. This exciting and inspiring course will give you the challenge and the boost you need to move you onto the next level of leadership. In a world were staying the same, means falling behind, this could be the challenge you have been waiting for.
The decision to proceed with a project is often based almost exclusively on early conceptual cost estimates, and these estimates provide the basis for the cash flow projections and budget forecasts used during the project feasibility study. Unreliable cost estimates can result in significant cost overruns later in the project life when it is too late to contain them. As potential projects are considered, management not only requires cost estimates of high accuracy, they seek opportunities to reduce life-cycle costs, improve budget accuracy and optimize whole-life project value.
Oil and Gas Production in the form of accurate measurement and back-allocating volumes to the wells, efficient production deferment tracking, and enhanced integrated production planning process pose a challenge to proper management of an oilfield asset.
In the oilfield, it is a routine practice to carry out these activities (consciously or otherwise) without recognizing and adhering to best practices. The case study indicates that inaccurate measurements of crude oil & gas production represent about 10% revenue loss to an asset with attendant legal consequences or confidence impact in some instances.
This naturally cascades into unreliable business planning cycles and field reserve estimation. This Best Practice in Surface Production Operations Management training will go steps further to highlight current best industry practices with field experience including challenges and how to mitigate identified challenges. This training seminar will further show how an integrated production operations approach is applied in addressing these challenges including custody transfer and other terminal nodes.