Learn how to harness the power of storytelling and the science of human vision to create compelling reports, charts and dashboards that drive high quality, data-driven decisions.Get Trained
Any data visualization software package (e.g. Excel, Tableau, PowerBI, Qlik, R, Python) and Powerpoint
Either Mac or Windows operating system
I find Dominic’s like a really really good presenter and he can explain really complicated ideas in a clear way. Previously in my business we had a lot of trouble visualizing data and Dominic really helped us find a way to make clear dashboards and see data the easy way for our stakeholders and myself.
It’s really impactful, and the delivery, I really like the performance they’re delivering. The subtle things that we tend to forget in our day to day, they remind it in a very impactful manner because if I see the content from a different presenter I’d be like “nah, it’s common sense” and I’d walk away
I’m impressed on how this course had been conducted. After this 2-day course, What I learned, I’m going to practice and use it in my workplace.
Dom is very engaging, his message is very clear. The presentations are really good and they’re super relevant and he is open to questions.
I had no idea that data visualisation could be so fascinating and interesting. I really liked the part on the Gestalt principals of perception. Super applicable and what an engaging presenter. My visualizations will never be the same!
Isaac, thank you so much for the training course you delivered to our team. We’ve been through multiple trainings over the last year and this one was by far the best. The whole team is excited to apply their new data storytelling skills to our decks. Can’t wait for the next course!
The training is very amazing and easy to understand. The speakers are knowledgable on what they presenting and it give us a new insight on how we do a better presentation.
Anyone who is skeptical of the power of machine learning and AI needs to take this course. I left challenged, excited and honestly afraid of the predictive power of these models! I liked the emphasis on hold out test set error – after all, that’s the whole point of modelling. I also liked how the instructor related each model to a real project where they had used that model. Now I just need to convince management to let us use R!
I think the class has a right balance, they practice our knowledge which I appreciate because it’s stick with you when you practice what you just learn. Thank you DataSeer!
It was a very good experience, in fact I didn’t know anything about data storytelling, but I did not realizes that this is something I have been looking for the longest time. DataSeer thank you very much! you made my life, my work a lot easier.
This is how Isaac Reyes describes his decade long relationship with data. And with over 3,000 hours of data science training experience at the world’s leading institutions, the numbers certainly add up.
“Teaching is definitely a passion”, says Isaac. “I’ve always kept one foot in the education sector and one foot in the commercial sector. A trainer who is unfamiliar with the commercial application of his methods risks becoming too esoteric in his teaching. On the other hand, a practitioner who doesn’t teach misses out on the peer review process that occurs when presenting to a smart audience.”
Our Lead Data Storytelling Trainer and a TEDx speaker, Dom brings a wealth of data storytelling experience to DataSeer from his career at QBE, one of Australia’s largest
insurance companies. At QBE, he was a senior leader in analytics, procurement, and business improvement.
He has been responsible for negotiating multi-million dollar contracts with suppliers, presenting data driven strategy recommendations to the company’s senior
executives, and producing reporting for the Group Board of Directors.
Martin has gathered more than a decade of training and teaching experience at the Singapore Institute of Management Global Education (SIM GE) and Singapore Polytechnic (SP), specializing in the fields of data analytics and business IT.
He has consistently received feedback scores amongst the top 10% of his peers and is highly skilled in developing and delivering curriculum and materials that combine a mix of both theory and practical hands-on for both undergraduates and working professionals.
Our Lead Analytics Translator, Diedre is a former Wall St trader, college lecturer and NYC Department of Education program leader. Prior to DataSeer, she oversaw the operation, curation and data driven strategy of WeTeachNYC.org-the NYC Department of Education’s online space for curricular and professional learning materials supporting over 76,000 professional educators.
She is currently an Adjunct Lecturer at the City University of New York and holds a Master’s in Mathematics from Pace University
Today, we are confronted by more data than ever before. We have access to more data and information than ever before. However, all too often the insight from all this data and information is lost in a sea of noise. For example, social media and the rise of ubiquitous high-speed internet has made it easier than ever before for users to create and share content, ideas and data. However, often the key insight from this content is lost in a sea of noise.
The volumes of data that we have access today have only existed for a few hundred years. The first charts only started to appear in the late 1700’s and since then they have proliferated exponentially. It’s now easier than ever to create charts.
A common misconception is that in the age of big data everyone needs to be a data scientist or data engineer. Yet so often, the biggest positive impacts in the world are driven by making the insights from data simple and accessible. People don’t relate to numbers and data in isolatation. People relate to stories.
A 2011 report from McKinsey and Company identifies that “there will be a shortage of talent necessary for organizations to take advantage of big data. By 2018, the United States alone could face a shortage of 140,000 to 190,000 people with deep analytical skills as well as 1.5 million managers and analysts with the know-how to use the analysis of big data to make effective decisions.” One of the most valuable skills you can invest in is the ability to extract insights from data and share compelling stories with those insights.
Creating a story for the goal of informing others has been something that civilization has been reliant upon since the dawn of humankind. But with so many advances in technologies and expansion of our collective imaginations, the power of storytelling has grown exponentially more vital, particularly as marketplaces grow more crowded and the importance of finding and reaching an audience grows exponentially more difficult as our attention spans grow shorter.
A good story is something that everyone remembers. We may not recall every last narrative element and a few details might get forgotten in the re-telling of the story over time, but the major plot points, the themes, and the structure of the narrative are typically recognized and well-memorized by those who have engaged with a compelling story.
This should all be considered when it comes to the gathering and analysis of data in the day to day operations of your business. Data is an essential tool in the toolbox of any enterprise, regardless of size or industry. That’s what makes data storytelling such an effective and compelling solution for success.
Understanding Data Storytelling is growing increasingly essential in today’s fast-paced digital arena because of the sheer amount of data that is now available. Storytelling brings a greater human element to the arena of data analysis and makes the data easier to digest.
The Key Components of Data Storytelling Data storytelling incorporates three specific methodologies for communication. Combining all of these together into one clear and concise format for disseminating information can make the task of assessing and transmitting data for wide consumption a lot simpler and more compelling.
The first of these key components lies in the field of data science. There are a number of pertinent technologies that work wonders in the background of data sciences, but on it’s own, the approach that data science takes towards leveraging data is mostly clinical, at best.
The data science component is tasked with the collection of data but is unable to tell a story about that data all on its own. This area is focused solely on the gathering of vital data but it typically does not delve much further value in truly dissecting it and gleaning new information from it for a more well-rounded and complete comprehension of it.
Consider all the ways in which you can analyze and try to make sense of data. We have countless types of charts and graphs and with the development of more complex online and digital resources, the dashboard has become something of an industry standard in just about every industry where data was paramount. With modern software packages, throwing together a fancy looking chart or dashboard is easier than ever. What differentiates an out of the box chart from a software package like Microsoft Excel, or PowerBI, from a chart that is ready for data storytelling is the configuration of that visualization to be simple, easy to consume, and enriched with techniques like highlighting and color to focus attention, so that your audience can easily and quickly determine the key takeaway that your data conveys.
So now we come to the third and arguably the most important component in the mix for creating a powerful story with data. Here is where the art of language comes into play and the words that are employed to create a narrative must be expertly selected.
The narrative component relies on identifying the most important insights from your data, supporting those insights with effective visualization, and then articulating what those insights are and how they fit together into a broader story with the use of clear language. The third component is centered around taking both of these factors into consideration in order to build a narrative that explains and offers some manner of insight or interpretation surrounding the key points of the data.
Now, how you convey that narrative and the purposes for building the story are entirely up to you and might be predicated upon the particular goals or objectives that your company might be trying to accomplish. As long as the data is accurate and correct, the visuals are properly organized so they can be shuffled into datasets, and the narrative is clear, simple, and conveyed in language that is easy to understand, you will find that data storytelling can bring your business a distinct advantage.
This has only been a brief introduction to the world of data storytelling, and for any business owner who is interested in unlocking its potential, there are courses that one can take to fully understand and take charge of this valuable tool for analysis. StoryIQ is an excellent resource for seeking out educational courses that teach data storytelling to novices and veterans in data analytics alike.
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