Now that you know
the five essential skills of a data analyst, you're ready to learn more about what it means to
think analytically. People don't often
think about thinking. Thinking is second nature to us. It just happens automatically, but there are actually many
different ways to think. Some people think creatively, some think critically, and some people think
in abstract ways. Let's talk about
analytical thinking. Analytical thinking
involves identifying and defining a problem and then solving it by using data in an organized, step-by-step manner. As data analysts, how do
we think analytically? Well, to answer that question, we will now talk about
a second set of five. The five key aspects to
analytical thinking. They are visualization,
strategy, problem-orientation, correlation, and finally, big-picture and
detail-oriented thinking. Let's start with visualization. In data analytics, visualization is the graphical
representation of information. Some examples include graphs, maps, or other design elements. Visualization is important
because visuals can help data analysts understand and explain information
more effectively. Think about it like this. If you are trying to explain
the Grand Canyon to someone, using words would be much more challenging than
showing them a picture. A visualization of the
Grand Canyon would help you make your
point much quicker. Now let's talk about
the second part of analytical thinking,
being strategic. With so much data available, having a strategic mindset is key to staying
focused and on track. Strategizing helps data
analysts see what they want to achieve with the data
and how they can get there. Strategy also helps improve the quality and usefulness
of the data we collect. By strategizing, we
know all our data is valuable and can help us
accomplish our goals. Next step on the analytical
thinking checklist: being problem-oriented. Data analysts use a problem- oriented approach in
order to identify, describe, and solve problems. It's all about keeping
the problem top of mind throughout the
entire project. For example, say a data
analyst is told about the problem of a warehouse constantly running
out of supplies. They would move forward with different strategies
and processes. But the number one
goal would always be solving the problem of keeping
inventory on the shelves. Data analysts also ask
a lot of questions. This helps improve
communication and saves time while
working on a solution. An example of that would be surveying customers about
their experiences using a product and
building insights from those questions to
improve their product. This leads us to
the fourth quality of analytical thinking: being able to identify a correlation between two
or more pieces of data. A correlation is
like a relationship. You can find all kinds
of correlations in data. Maybe it's the relationship
between the length of your hair and the amount
of shampoo you need. Or maybe you notice a
correlation between a rainier season leading to a high number of
umbrellas being sold. But as you start identifying
correlations in data, there's one thing you always
want to keep in mind: Correlation does not
equal causation. In other words, just
because two pieces of data are both trending
in the same direction, that doesn't necessarily
mean they are all related. We'll learn more
about that later. Now the final piece of the analytical thinking
puzzle: big-picture thinking. This means being able to see the big picture as
well as the details. A jigsaw puzzle is a great
way to think about this. Big-picture thinking is like looking at a complete puzzle. You can enjoy the
whole picture without getting stuck on every tiny piece that went into making it. If you only focus on
individual pieces, you wouldn't be able
to see past that, which is why big-picture
thinking is so important. It helps you zoom out and see possibilities
and opportunities. This leads to exciting
new ideas or innovations. On the flip side, detail-oriented
thinking is all about figuring out all of the aspects that will help you
execute a plan. In other words, the pieces
that make up your puzzle. There are all kinds
of problems in the business world
that can benefit from employees who have
both a big-picture and a detail-oriented
way of thinking. Most of us are naturally
better at one or the other. But you can always develop the skills to fit
both pieces together. Now that you know
the five aspects of analytical thinking, visualization, strategy,
problem-orientation, correlation, and big-picture and
detail-oriented thinking, you can put them to work for you when you're
working with data. As you continue through this
course, you'll learn how.