
It’s one thing having data governance, but we need governance across the whole data value chain – from data capturing to data use and presentation. I won’t delve too much into the ethics of data presentation and visualisation. I will instead point you in the direction of some fantastic books on the topic, such as How Charts Lie: Getting Smarter about Visual Information by Alberto Cairo. It was one of my top Data Analytics Book Recommendations.
If there is one aspect of data analytics that I’ve realised in exceptionally important, it is the ability to tell a story with data.
These books are my go-to guides for beginner to advanced data heads (to steal a phrase from Jordan Goldmeier).
Podcast recommendations to learn more while listening.
A Data Science Training course for Executives is a course designed to provide business leaders with an understanding of the fundamental concepts and applications of data science. The course covers key topics such as data analysis, data visualization, machine learning, and big data technologies. The goal of the course is to equip executives with the skills and knowledge they need to make informed decisions about data-driven initiatives within their organizations.
Data Analytics is one of the most sought-after skills globally. Business Insider has even rated both Chief Digital Officers and Data Science Executives as two of the top six most in-demand executive jobs.
However, analytics knowledge isn’t just crucial for data scientists and analysts, but for anyone looking to navigate today’s world, make data-informed decisions and be able to predict and better react to market trends.
This Data Science for Executives course explains:
1. What Data Analytics is and why it is one of the most in-demand skills today.
2. The history of Data Analytics in helping companies become market leaders and how companies came to recognise data as an asset rather than a by-product of operations.
3. Why ethics is key for trusted analytics both for the organisation and for clients.
4. How to scale analytics across the organisation using data scientists and data engineers.
5. The core principles of data analytics, from exploratory data analysis and data visualisation to high-frequency analytics and alternative data.
This course covers analytics at a high level without any coding examples, by focusing on the various aspects of analytics and how they can be applied in practice. This course will enable executives and beginners alike to understand the power of analytics, what skills data science teams need, and why analytics needs to be broadly adopted to enable a data-driven organisation.
This course was developed by DMSA and is presented by Data Science leader Matthew Bernath.