Digitalisation

Essentials of Data and Analytics

Through the Essentials of Data and Analytics online course, you’ll gain insights into the critical role data plays in decision-making and everyday life. This course equips managers and professionals to make informed decisions by introducing key definitions and terminology, complemented by case studies and scenarios for deeper reflection. It provides a strong foundation in data and analytics, helping participants effectively apply these concepts in decision-making.

Price

350€

Workload

Up to 12 Hours

Type

Self-paced online

Languages

English

Benefits

During the online course, you will reflect on the importance of data, which, together with analytics, poses a strong base in any company. The course provides teams with a fundamental level of skill and assists the participants in making informed decisions.

In this course you will:

Grasp the benefits of data management combined with analytics.

Recognize the essential cornerstones of data and analytics and gain a better understanding of both strengths and weaknesses.

Learn how to make analytical decisions based on data.

Understand the importance of good quality data and what to consider when managing data.

Contents and Schedule

The online course covers the essentials of data and analytics. You will be provided with fundamental know-how in the field, including data strategy, field definitions of data and analytics, and case scenarios. You will get an overview of data and its importance and understand the essentials of analytics and how to use data and analytics in decision making.

The online course also includes a Course Workbook, where reflections from the course are gathered in one handy document. You can apply the findings to reflect on your learning journey and use the workbook to start working on a data and analytics project idea.

The course is structured into 11 online modules consisting of interactive video lectures, reflection tasks, and reading material, each covering data and analytics from a different perspective. The videos are accompanied by interactive questions to check your knowledge along the way, further reading material, and reflection prompts.

Each module contains

  • Introduction
  • Video lecture
  • A small reflection task
  • Knowledge check questions
  • Review of the key takeaways from the module

The course videos are subtitled in English.

The estimated study time of the course is 12 hours. The course allows flexible study patterns; you can decide on your schedule and the speed of your progress.
The recommended study schedule is 2-3 hours per week for 3-4 weeks.

Path 1: Data Strategy

The first learning path, Data Strategy, will delve into the concept of data. Data is everywhere, and we humans have been gathering data for many years. Data needs to be considered a valuable asset in the business environment as data has become a new productivity factor. The six modules will introduce:

Data strategy
Data as an economic good
Big data
Data sharing
Data governance and data quality management
Data and analytics culture

Instructor: Kari Hiekkanen, Research Fellow, Aalto University, School of Science

Path 2: Analytics

The second learning path, Analytics, will provide you with information on using data through analytics further and how to implement analytics projects based on data. To use analytics properly for the most benefit, it is necessary to go through the terminology and key concepts used. The five modules in this study path will introduce you to:

Field definitions of analytics and machine learning
The three types of learning
Typical case scenarios in analytics
Models, accuracy, and generalization
Case examples

Instructors: Jaakko Hollmén, Senior University Lecturer, Aalto University, School of Science

For

The course is aimed at experts and managers who want to learn the basics of data and analytics and how they can benefit from these areas in business. No previous experience in the topic is required.

The course is suitable for those who need to take a closer look at the essentials of data and analytics and who might take on a role close to data and/or analytics professionals. It also provides a good base for participation in other programs offered by Aalto EE.

Related content

  • Engineering

    Demystifying the Industrial Metaverse: Unlocking Value for Industry 5.0

    Masterclass

  • Digitalisation

    Cognitive Automation and its Impacts on Skill Erosion of Individuals

    Masterclass

  • Finance and economics

    Service Management

    Course

  • Digitalisation

    Digital Twins: Current State and Future Potentials

    Masterclass

  • Finance and economics

    Objectives and Key Results for Performance Management

    Course

  • Digitalisation

    Introduction to AI

    Course