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Read on to explore five key benefits of making data analytics a priority in business.

1. Gain greater insight into target markets

When businesses have access to the digital footprints of their customers they can learn invaluable knowledge about their preferences, their needs, and their browsing and purchasing behavior. Analyzing data collected from targeted markets can also help companies more swiftly identify trends and patterns and then customize products or services to meet these needs. The more an organization knows about who its customers are and what they want, the better it will be able to grow the customers’ loyalty, ensure they are happy, and boost sales. If leaders don’t take notice, they run the risk of losing their consumer base to a competitor who does.

Whether you’re seeking an entry-level or leadership role, it’s increasingly apparent that to be successful in today’s job market, it is critical that you are able to analyze data and communicate the findings in a way that is easily understood. DATA 1010: Introduction to Data Analytics at Penn LPS Online introduces you to important concepts in data analytics across a wide range of applications using the programming language R. You’ll complete this course with a clear understanding of how to use quantitative data to identify problems in real-time, make decisions, and create solutions.

2. Enhance decision-making capabilities

Data analytics also gives companies the power to make faster, better-informed business decisions—and avoid spending money on ineffective strategies, inefficient operations, misguided marketing campaigns, or unproven concepts for new products and services. By using a data-driven decision-making model, leaders also set up their organizations to be more proactive in identifying opportunities because they can be guided by the validity of data rather than simple intuition or industry experience. However, it is also important that decision-makers understand that although data may show a certain pattern or suggest an outcome, a flaw in the analysis or collection process could potentially render it inaccurate or misleading.

Once you’ve completed the introductory course in data analytics, the next logical step is to enroll in DATA 2100: Intermediate Data Analytics. In this course, you will learn two fundamental skills: survey and experimental research. You’ll be trained in every step of the survey research process, including how to design good survey questionnaires, draw samples, weigh data, and evaluate the responses. By the end of this flexible online class, you’ll understand how to develop and analyze a randomized experiment and build upon your skills in R programming.

 3. Create targeted strategies and marketing campaigns

Businesses can also use data to inform their strategies and drive targeted marketing campaigns to help ensure promotions engage the right audiences. By analyzing customer trends, monitoring online shopping, and evaluating point-of-sale transactional data, marketers can create customized advertising to reach new or evolving consumer segments and increase the efficiency of overall marketing efforts. And by taking advantage of these insights on consumer behavior and desires in customer-oriented marketing, businesses can meet and exceed expectations, boost brand loyalty, and encourage growth.

If you are interested in developing targeted marketing or advertising campaigns, it’s critical you understand the process by which quantitative social science and data science research is conducted. And that’s where DATA 3100: Introduction to Statistical Methods at Penn LPS Online comes in. This course comprises three complementary tracks. In the first, you’ll learn the basic tools necessary to perform social science research including descriptive statistics, sampling, probability, and statistical theory. In the second, you’ll discover how to implement these basic tools using R. And in the third, you’ll study the fundamentals of research design, including independent and dependent variables, producing testable hypotheses, and issues in causality.

4. Improve operational inefficiencies and minimize risk

Another major benefit to data analytics is the ability to use insights to increase operational efficiencies. By collecting large amounts of customer data and feedback, businesses can deduce meaningful patterns to optimize their products and services. Data analytics can also help organizations identify opportunities to streamline operations, reduce costs, or maximize profits. Companies can use insights from data analytics to quickly determine which operations lead to the best results—and which areas are underperforming. This allows decision-makers to adjust their strategies accordingly and proactively anticipate problems, manage risks, and make improvements.

Predictive modeling of data is one of the most sought-after skills in data science because it can help companies strategize future investments, nonprofits organize fundraising drives, or political candidates decide where to focus their canvassing efforts. DATA 4010: Advanced Topics in Data Analytics at Penn LPS Online starts with a comprehensive discussion on basic regression analysis and progresses to more advanced topics in R, such as mapping, textual analysis, web scraping, and working with string variables. You will also learn about more advanced data visualization skills in the class, including how to create interactive data visualizations in an R tool called Shiny.