At first glance, data science seems to be just another business buzzword — something abstract and ill-defined. While data can, in fact, be both of these things, it’s anything but a buzzword. Data science and its applications have been steadily changing the way we do business and live our day-to-day lives — and considering that 90% of all of the world’s data has been created in the past few years, there’s a lot of growth ahead of this exciting field.
While traditional statistics and data analysis have always focused on using data to explain and predict, data science takes this further. It uses data to learn — constructing algorithms and programs that collect from various sources and apply hybrids of mathematical and computer science methods to derive deeper actionable insights. Whereas traditional analysis uses structured data sets, data science dares to ask further questions, looking at unstructured “big data” derived from millions of sources and nontraditional mediums such as text, video, and images. This allows companies to make better decisions based on its customer data.
So how is this all manifesting in the market? Here, we look at three real-world examples of how data science drives business innovation across various industries and solves complex problems.
In today’s digital age, we’re constantly bombarded with information about new apps, transformative technologies, and the latest and greatest artificial intelligence system. While these technologies may serve very different purposes in our life, all of them share one thing in common: They rely on data. More specifically, they all use databases to capture, store, retrieve, and aggregate data. This begs the question: How do we actually interact with databases to accomplish all of this? The answer: We use Structured Query Language, or SQL (pronounced “sequel” or “ess-que-el”).
Put simply, SQL is the language of data — it’s a programming language that enables us to efficiently create, alter, request, and aggregate data from those mysterious things called databases. It gives us the ability to make connections between different pieces of information, even when we’re dealing with huge data sets. Modern applications are able to use SQL to deliver really valuable pieces of information that would otherwise be difficult for humans to keep track of independently. In fact, pretty much every app that stores any sort of information uses a database. This ubiquity means that developers use SQL to log, record, alter, and present data within the application, while analysts use SQL to interrogate that same data set in order to find deeper insights.
Finding SQL in Everyday Life
Think about the last time you looked up the name of a movie on IMDB. I’ll bet you quickly noticed an actress on the cast list and thought something like, “I didn’t realize she was in that,” then clicked a link to read her bio. As you were navigating through that app, SQL was responsible for returning the information you “requested” each time you clicked a link. This sort of capability is something we’ve come to take for granted these days.
Let’s look at another example that truly is cutting-edge, this time at the intersection of local government and small business. Many metropolitan cities are supporting open data initiatives in which public data is made easily accessible through access to the databases that store this information. As an example, let’s look at Los Angeles building permit data, business listings, and census data.
Imagine you work at a real estate investment firm and are trying to find the next up-and-coming neighborhood. You could use SQL to combine the permit, business, and census data in order to identify areas that are undergoing a lot of construction, have high populations, and contain a relatively low number of businesses. This might be a great opportunity to purchase property in a soon-to-be thriving neighborhood! For the first time in history, it’s easy for a small business to leverage quantitative data from the government in order to make a highly informed business decision.
Leveraging SQL to Boost Your Business and Career
There are many ways to harness SQL’s power to supercharge your business and career, in marketing and sales roles, and beyond. Here are just a few:
Increase sales: A sales manager could use SQL to compare the performance of various lead-generation programs and double down on those that are working.
Track ads: A marketing manager responsible for understanding the efficacy of an ad campaign could use SQL to compare the increase in sales before and after running the ad.
Streamline processes: A business manager could use SQL to compare the resources used by various departments in order to determine which are operating efficiently.
SQL at General Assembly
At General Assembly, we know businesses are striving to transform their data from raw facts into actionable insights. The primary goal of our data analytics curriculum, from workshops to full-time courses, is to empower people to access this data in order to answer their own business questions in ways that were never possible before.
To accomplish this, we give students the opportunity to use SQL to explore real-world data such as Firefox usage statistics, Iowa liquor sales, or Zillow’s real estate prices. Our full-time Data Science Immersive and part-time Data Analytics courses help students build the analytical skills needed to turn the results of those queries into clear and effective business recommendations. On a more introductory level, after just a couple of hours of in one of our SQL workshops, students are able to query multiple data sets with millions of rows.
Michael Larner is a passionate leader in the analytics space who specializes in using techniques like predictive modeling and machine learning to deliver data-driven impact. A Los Angeles native, he has spent the last decade consulting with hundreds of clients, including 50-plus Fortune 500 companies, to answer some of their most challenging business questions. Additionally, Michael empowers others to become successful analysts by leading trainings and workshops for corporate clients and universities, including General Assembly’s part-time Data Analytics course and SQL/Excel workshops in Los Angeles.
“In today’s fast-paced, technology-driven world, data has never been more accessible. That makes it the perfect time — and incredibly important — to be a great data analyst.”
– Michael Larner, Data Analytics Instructor, General Assembly Los Angeles
It makes perfect sense that this job is both new and popular, since every move you make online is actively creating data somewhere for something. Someone has to make sense of that data and discover trends in the data to see if the data is useful. That is the job of the data scientist. But how does the data scientist go about the job? Here are the three skills and three tools that every data scientist should master.
Launching for the first time in San Francisco and Washington, D.C. on April 11, this full-time Immersive program will equip you with the tools and techniques you need to become a data pro in just 12 weeks.
The Data Journalists handbook defines data literacy as, “the ability to consume for knowledge, produce coherently and think critically about data.” It goes on to say that “data literacy includes statistical literacy but also understanding how to work with large data sets, how they were produced, how to connect various data sets and how to interpret them.”
At General Assembly, we’d like to imagine a world where you don’t need a Ph.D. in Statistics to have a data-informed conversation about your business, your health, or your life in general. Over the past year, we’ve embarked on the journey to build a more data literate world through education offerings that meet the diverse needs of our students.
In building these courses, we’ve sought advice from data scientists, analysts, and hiring managers to determine the critical skills you need to become data literate in today’s workforce. We discovered that it isn’t just a concrete list of skills, but a mindset geared towards data—a way of approaching problems beyond “gut instincts.”
Here, we’ve proposed a few simple questions that will help you start to view the world through the lens of data.
If you thought the introduction of the commercial Internet changed mass media, take a look at what’s in front of you today. Behind the sites of your favorite newspapers and blogs (yes, even this one), publishers are using data to create better audience experiences. For anyone who has ever considered working with data as part of their career, there are now more opportunities than ever to bring media and data together. Here are some of the most important technologies to have on your radar.
Big data is just what it sounds like; data so big that it’s not easily processed through conventional methods. However, once this large data set is eventually distilled down, user experience can play a huge role in making sense of the reports and leading the charge for user-centered solutions.
User experience (UX) is the bridge between big data analytics and the end user. The richness of big data being collected by all types of companies has unleashed a treasure trove of information for user experience designers. UX designers can create more robust solutions for users by analyzing these enormous data sets.
Can data improve the future of our humanity? You better believe it. “Big data” is more than just big businesses. Every day, social impact groups are finding new and creative ways to act upon the information that they’re generating. They’re using data to surface new information, uncover underserved communities, and track performance over time. Here are 5 very different organizations that are using data, in new and creative ways, to improve the lives of people around them:
For many people, data feels like an avalanche of information. No matter how proficient we are with Excel, statistical software, SQL, or Google Analytics, it’s often tough to know where and how to take your first steps. Should you create a chart? Should you try to find a correlation between the trend you’re observing and revenue? How do you know whether your findings are statistically significant—and for that matter, what the heck is statistical significance?
At the end of the day, these questions are less intimidating than they seem. Data is a tool that human beings created for other human beings. As a result, it’s up to you to create your own constraints for analysis. You choose your terms. You choose the questions you want to answer. You choose the techniques that you want to deploy. You’re in control.
Here are three tips to help you wrangle your next report.
Data visualization is a form of visual communication where data is presented in a pictorial or graphical format. By presenting complex data sets in a visual way, people can comprehend and analyze the information set faster and more clearly.