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The Modern Great Detectives: Data Analysis and Corporate Marketing Strategy

Data Analysis and Corporate Marketing Strategy

We live in the era of Big Data, as so many others rightly point out. We’re in an age where just about everything you could imagine is discoverable online. That is, if one knows how and where to look.

This is because more and more people are feeding the beast, so to speak, by posting on social media sites and surfing the web daily. ISP's track and record their activity. Then, it is sold to corporate bidders. Where every bit of information they post about their preferences, or the products they buy, or information about their personalities, gets saved as part of a massive historical database. Guess what? All of that information is also sold to companies regularly.

This data is precious and somewhat sensitive. And while corporations have competitive access to it as the information market is somewhat alarmingly thriving, they need people on staff who can read it. As such, companies are paying high salaries to people who have the qualifications. These people read and interpret this vast amount of data. Thus, it may be a fine time to switch careers.

Data Analysts: The Sherlocks of Our Time

These people are known as data analysts, and occasionally as data scientists, if the one posting the job doesn’t know about the distinction between the two. Data analysts have one job: to parse through massive data sets from multiple sources. They identify patterns that may prove helpful for their employers. Then, use those patterns to answer a set of specific questions. Using a variety of methods that vary from practice to practice, data analysts are responsible for providing marketing teams with insights. These then help them fine-tune their approach, ensuring their success and avoiding potential mistakes. As such, would-be data analysts need to be detail-oriented creative thinkers. Additionally, they must communicate their findings clearly.

While some companies use data scientists and data analysts interchangeably in their job postings, they are two different professions. Data scientists typically take large data sets and translate them into practicable models. Thus, developing hypotheses and testing them via these models to narrow down the best course of action. In short, they are much more big picture, whereas data analysts typically search for answers to more minor problems. Some positions will likely require aspects of both fields as they do often intersect. However, it’s essential to know the difference between the two fields when searching for a job.

No Mind Palace Necessary: How the Magic is Done

Data analysts have various tools to help them parse through this overwhelmingly large amount of data. Most have a simple process that they follow in their day-to-day work. Your typical data analyst will identify the question that needs answering. Then, go about gathering different kinds of data that may prove helpful. They use the tools at their disposal to “clean” and organize the data, correcting errors and organizing data in a useful fashion. The latter step, called “data cleaning,” will likely be done repetitively.

Once this is done, data analysts can read the data and use one of four analytic styles to answer their questions:

  • Descriptive analysis: drawing a summary of the dataset. This is often used as a means to further research, not an end in itself.
  • Prescriptive analysis: Usually involves using machine learning techniques. This form of analysis seeks to chart out an organization’s next steps.
  • Diagnostic analysis: This form of analysis seeks to help companies understand why something may be occurring.
  • Predictive analysis: Using previous trends in data to try and predict what will happen in the future.

A Teachable Skill

Fortunately, it’s rather easy to enter the data analysis field for those willing to put the effort in. You can learn advanced data analytics skills from an online master's program in data analysis. It is a cost-effective learning opportunity for the graduates in the technical stream. Instead of going to a four-year university and spending tens of thousands of dollars on another degree, you can go to an intensive data analytics bootcamp. These bootcamps aim to teach you everything you need to know to jump straight into a job in a matter of months. Usually, it's around the cost of a single semester at college. While not necessarily the right option for everyone, they can be a great resource for people looking to switch careers quickly. The variety of options available on the market should provide for any existing schedule.

A Firm Foundation for the Future

Careers in data analysis are likely to continue to appreciate in the future. With the labor shortage, there’s no shortage of opportunities to enter the field now. Take advantage of the opportunity and get the education you need to switch rapidly. Thus, preparing yourself for the future than many of your peers.

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