Big Data Analysis

WABDA43
(Project Management)

Course Overview

This three-day program commences with an introductory overview of the use of big data in the energy sector. As the course unfolds, across the three days, our highly experienced instructors will balance the participants understanding between data science theories and models and how these are implemented to add value to project delivery and commercial success. Participants will be strongly encouraged to identify case studies within their own organisation. They will be guided by our instructor to apply these case studies alongside the course content as a means of ensuring direct knowledge transfer and value add.

You Will Learn How to

In this course, you will learn how to:

Recognise the importance of analytics in the energy sector

Execute data driven analytics projects

Recognise the common pitfalls and what usually works in data driven projects

Identify a list of related business case studies

Understand the fundamentals of data science and meaningfully relate data science problems to solution approaches

Gain practical understanding of data processing and modelling

Refine the ideated business case studies based upon their developed understanding

Apply solution implementation steps, control and monitoring mechanisms to ensure sustainability

Develop data driven concepts into concrete project plans

Present project ideas to business stakeholders

Topics

Using Big Data in project

Overview to Big Data and
Project/Program Management

Using Big Data in project

Introduction to Big Data Management

The Status of Big Data Management

State of performances of Big Data Management

Managing big data strategies

Effectiveness of big data management

Data Science Methods

Data mining

Machine learning

Artificial intelligence

Information retrieval

Statistical analysis

Gap analysis

Technical Practices for Big Data Management

Different forms and structures of data types

Storage policies for big data

Scales of big data that need to be managed

Corporation Practices for Big Data Management

Big Data ownership

Roles and responsibilities

Big data management configuration

Collaborative practices around big data management

Top Priorities of Big Data Management

Choosing the Best Strategy

Organizational Leadership

Course Details

DAY 1: Why – Understand the why and how of Big Data and Machine Learning Introduction, trends and value of Big Data and IoT in heavy asset industry: where is the value? Why now?Setting up and driving a Big Data Program – learnings, dos and don’ts: ambition setting, structuring and running a program, governance, organization, partnering, communication, metrics and targetsWorking session: Setting ambition and priorities for your organization or team DAY 2: What – Demystifying Big Data and Machine Learning: what it is and how it works Big Data and Machine Learning concepts and technology – theory and real applications in asset heavy industriesBig Data and Machine Learning process – how it works and how it is done in practice (real examples)Working session: Data Scientist for a day: set up and run a machine learning model DAY 3: Execution – Making it concrete for Saudi Electricity Company (Exercise session Working session: Shaping a digital transformation for your team or organisation – applying all learning from previous days: defining a vision, priorities, identifying use cases, estimating value, drafting a roadmap, organizational options, setting targets.

Course Length

3 Day Course

Course Schedule

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