Areas to Understand in Data Science

Data science is one of the top five fastest growing fields for job growth. Companies and organizations continue to digitize operations, yielding mountains of valuable data. All of this information provides insight on user demographics, browsing patterns, industry trends, and more; it helps inform the direction of an organization and can identify areas of growth that are not immediately obvious. But for value to be realized, data science experts need to make sense of all of those stats. If you want to analyze and interpret statistical facts and figures, you need to understand these four areas of data science:

1. Database Management

Before you can become a data scientist you need to learn about databases. These are where data are stored, organized, and examined. If you know how databases function and how to leverage their features, you will be able to sift through, classify, and manage data efficiently. It is even better if you can build your own database, so you can customize the features that enhance your ability to request and integrate information from other databases, report aggregated information, and apply it to different aspects of the organization (e.g., customer relationship management, automation). Database management is all about making data collection quick and easy so you can find and use it.

2. Data Mining

Data mining has become a hot topic in the news as of late. Massive companies like Facebook and Uber are scrutinized for their data mining practices, putting together large sets of personal user data to sell to advertisers without the explicit knowledge of the user. So up front, it is important to know that there is an ethical component to data mining; it is not an inherently bad practice. In fact, it can be crucial to an organization’s success. Think of the applications: in a retail or grocery store, the collectively mined shopper data may determine product placement; movie and music streaming services will learn what you like to watch and listen to; in education, it can identify learning behaviors and student retention factors. Data mining best practices and techniques are vital for gathering and disseminating data patterns across industries.

3. Data Visualization

You need to be able explain data in a way that is easily digestible. Data visualization is the visual representation of compiled data. This makes data much easier to handle. For example, if want to determine the most effective SEO keywords for a blog post, a word cloud will clearly show which are the best; if you want to identify traffic patterns in major cities, area cartograms or geospatial maps will highlight which streets are most congested; if you want to compare wait times for hospital emergency rooms, a treemapping structure will rank and display the times. Data visualization especially helps to make large sets of data more comprehensible to more users. Your company’s CEO or COO doesn’t need to be an IT expert if s/he has data visualization tools and a data science expert like you.

4. Data Product

Now that you’ve obtained, stored, organized, and visualized your data, you can use it to create and enhance the products or services your organization offers. So what exactly do data products look like? They vary in size and scope but they all rely on collected information to generate revenue. For instance, a data product could be a job website that lists job postings, salary ranges, industry outlooks, and education requirements. To create a good data product, you must have knowledge of information technology and web applications, and be data savvy, as well as possess strong business acumen. It’s important that your product is of a high technological quality, but just as important that it is marketed to the right audience.

Once you come to understand these four important areas of data science, you will increase your marketability in IT Management. Organizations need people who are literate in data and their applications, who can also connect real-world functionality to varied data sets. Whether your career goal is to become a Chief Information Officer, an IT Director, or to merely enhance your current position, the ability to manipulate data is a major, sought-after skill.

If data science sounds like the career path for you, Claremont Graduate University’s online MS in Information Systems & Technology program will teach you how to hone your skills in the field. This program is designed to instill data concepts and skills, allow you to pursue your degree while you work, and prepare you for leadership roles that matter. Request more information from CGU today.

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