There are some amazing data science tools out there that can be used for the exploration and visualization aspects of data storytelling. The essentials, listed below, will allow you to dive in with a minimal amount of time and effort.
Exploration
To support the analytics side of data exploration, knowledge of statistics and data science fundamentals is important. Course providers like Udacity can get you up to speed with the basics, quickly and for free. (Intro to Statistics, Intro to Data Science)
Programming is a necessity for carrying out analyses, and Python is both easy to learn (check out Intro to Python) and has a wide variety of libraries that cover all the tools you need. It’s a consensus top choice for beginners and experienced data folk alike.
The easiest way to get started with Python is through Anaconda, an open-source distribution that includes both Python and supplemental packages for handling data frames (with Pandas) and plotting (with Matplotlib and Seaborn).
Visualization
If you want to go beyond basic plotting and think about visualizing your analyses in a more complex way, visual design tools and techniques are incredibly useful.
From a graphic design perspective, you can think about the design you want for your data story through techniques like mood boarding, color schemes and wire framing. General Assembly has a great in-person course on Visual Design, and free courses are also available online through sites like Udemy.
When visually conveying data and structured information, there are additional design considerations. Edward Tufte is a leading figure in information design whose seminars and books (if you read only one, make it The Visual Display of Quantitative Information) are packed with useful guidelines and techniques.
To actually get your hands dirty with design, software like Sketch or Photoshop are incredibly powerful. And they will allow you to finally put it all together—data, analysis, and design—into a complete visual narrative.