Fundamentals of Data Analytics

Adding value with our service portfolio

Adding value with our service portfolio

ABOUT THE COURSE 

Numerous organisations and individuals today are embarking on the journey of digital and data transformation. The primary step in this process is data literacy, the ability to communicate, read and write about data in specific contexts and analyse the data effectively. Furthermore, both individuals and organisations need to know how to access and assess data, find meaning and derive actionable business insights.

Putting data to good use is the key for any business. Individuals should be able to use data to influence their daily activities as well as big-picture decisions. It is critical for everyone to know how to do the above, not just the data analysts or the data scientists. Being data literate will allow an employee or individual to experiment with the data and uncover new insights and generate opportunities. In addition, being data literate is a big part of data security and would reduce risks of data breaches and issues.

Our Fundamentals of Data Analytics course is designed to provide you with a solid foundation in the principles and practices of data analytics. You'll learn essential concepts such as data collection, validation, visualisation and analytics, storytelling, and data-driven decision-making.

Duration: 1 Day

Language: English

 
WHAT WILL YOU LEARN FROM THE COURSE?
At the end of the course, participants will learn:
  • What Data Literacy is all about and its importance
  • Fundamental elements of data
  • Overview of data sources, where data can be obtained from and how data can be collected
  • How to ask questions about data
  • Data Analytics – Foundations, Basic Statistics, Reasoning
  • Data Complexity, Relationships in Data and Inference
  • Importance of data storytelling and visualisation
  • Interpreting and gathering insights from visualisation
  • Logical and critical thinking to make data-informed decisions
  • Using data to see the future 

Topics to be covered in this course include:

 

  • 1: Exploring Data Literacy

    The first step before diving into the complex operations with data is to understand what data is all about and why it is important for any organisation or business to be data literate. This module explores those perspectives.

    • What does it mean to be Data Literate?
    • Data Literacy Roadmap and Adoption
    • Why data is important for any organisation?
    • What can be done with the data?
  • 2: Data Sources and Data Collection

    Data is the primary resource where things start. It is important to know where data can come from and how data should be collected. This module covers the in-depths of this process.

    • Data Touchpoints
    • Data Collection Methodologies
    • How clean should the data be made?
    • Typical Data Cleaning and Transformation techniques

     

  • 3: Asking Questions from Data

    Data is all about asking questions and building up the business value. This module covers how and what kind of questions should be asked from the data. It is important to ask critical questions which may help the business.

    • Defining a business problem
    • What parts of the data are important?
    • How do you formulate questions from the important part of the data?
    • Answering the questions through the data
  • 4: Data Analytics - Taking Data a Step Further

    In order to uncover insights using statistics and other techniques, it is imperative to know how it can be applied to the data and what it can give you. This module solely focuses on establishing foundational analytics and exploring relationships in data.

    • The Analytics Roadmap for a Business
    • What does Analytics consist of?
    • Does Analytics involve Statistics? Understanding important statistical concepts
    • Exploring relationships in the data using statistical and non-statistical methods
  • 5: Foundations of Data Visualisation

    Data in textual format is not the best way to derive insights and understand data. Visuals, Charts & Graphs always appeal to a wider audience because it makes the data easier to understand and comprehend. In this module, we will learn what data visualisation is all about and the best practices with data visualisation.

    • What are the various types of visualisations available?
    • How do we link data to visualisations? Choosing the right kind of visual for the right context
    • Deriving insights from visualisations
    • Best practices of data visualisations
    • Exploring business cases
  • 6: Telling a Data Story

    Communication is key with data. Being able to narrate a story with your data through your visuals and business insights is critical. This module focuses on how a story can be developed from dashboards and visuals and how this should be communicated to different audiences.

    • Why is Data Storytelling important?
    • How to Identify your Audience?
    • Key Elements of Data Storytelling
    • Pitfalls of Data Storytelling
    • Exploring Narrations

     

  • 7: Making Data-Informed Decisions

    The end goal with data is always to drive value and gather insights. Ultimately, any organisation would want to take decisions based on the gathered insights to help the business. This module enables you to understand, through various business cases, how that value can be derived and how decisions can be made based on the data.

    • Visual and data-informed decision making
    • Decision-making techniques
  • 8: Looking Into the Future

    There's a lot more that can be done with the data, especially by employing new techniques and advanced analytics. This module gives you an overview of how predictive analytics, machine learning and other technologies can help you maximise the use of your data.

    • Introduction to predictive analytics
    • Introduction to time series
    • What is machine learning all about?
    • Application of machine learning to business
    • What’s next with data?

WHAT IS THE COURSE METHODOLOGY?

Participants will learn through lectures, case studies, group exercises, hands-on exercises and discussions. The course will be conducted in face-to-face or virtual format with a duration of 8 hours. 

WHO SHOULD TAKE THE COURSE? 

This course is specially designed for:

  • Anyone interested to learn about Data Analytics and apply it in their day-to-day work

Prerequisite: No prior knowledge is required to take this course

WHO IS THE COURSE ADVISOR?

The course content and structure are designed by the domain experts from TÜV SÜD.

With immense experience and knowledge in the relevant standards, our team of product specialists and technical experts at TÜV SÜD, developed the course content based on current business landscape and market requirements.

  • What are the benefits of enrolling in this course?
    • World-class training – by learning from TÜV SÜD’s industry experts and training specialists
    • Interactive learning style – with interactive formats such as lectures, illustrations and simulations are used
    • Networking opportunity – where you can meet and build network with like-minded individuals at our instructor-led training
    • Gain a competitive edge – by getting trained by experts known in the fields of safety, security and sustainability.

 

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