Intro to Data Science

Data is the new electricity - Satya Nadella

We live in a time where huge amount of data are generated every second through website visit, social media likes and posts, online purchase, gaming, and online movie streaming among others. With an estimated 2.5 quintillion bytes of data generated each day, it is now inevitable for individuals and businesses to strategize on ways to derive valuable insight from this huge data lying around.

Now that you have an idea about the data boom, let’s look at what data science is all about.

What is Data Science?

In summary...

  • Data science is an multidisciplinary field that involves the processes, tools, and techniques needed to uncover insight from raw data.
  • Data science plays a critical role in enabling businesses to leverage their data assets and stay competitive in today's data-driven economy.

Now that you have an idea of what data science is, let understand why data science is important, and its role in businesses.

Data science in today's business

Given its significance in modern-day organizations...

  • data science holds crucial importance to decision making and business success.
  • there is a growing need for professionals who are equipped with data science skills... could that be you?

Who is a data scientist?

As an important part of every business, the role of a data scientist includes the following:

  • Collecting, processing, and analyzing data to identify patterns and insights that inform decision-making processes.

  • Developing predictive models that can be used to forecast future trends or outcomes based on historical data.

  • Creating data visualizations that make complex data sets easy to understand and communicate to stakeholders.

  • Collaborating with cross-functional teams to identify business problems and opportunities that can be addressed using data-driven insights.

  • Developing and deploying machine learning algorithms and other advanced analytical techniques to solve complex problems and generate insights.

  • Ensuring the accuracy, integrity, and security of data throughout the data lifecycle.

  • Staying up-to-date with the latest trends and tools in data science, and continuously improving skills and knowledge through ongoing learning and development.

👩🏾‍🎨 Practice: Data and Businesses

  • Why is data science important for businesses?
  • Highlight 2 things a data scientist doesn't do in an organization.

Answer these questions in the padlett below.

https://padlet.com/curriculumpad/data-and-businesses

👉🏾 In the next section, we'll explore the building blocks and typical workflow of data science.