How To Become A Data Analyst With Web Scraping

Hannah Benson
February 15, 2021
Community

how to become a data analyst

“What do you want to be when you grow up?” is one of the first questions you are asked in school. Typical answers include rockstar, firefighter, and doctor. Ever since I was little, I wanted to be a writer. As we get older, this question becomes blurred by rent, groceries, phone bills, and other costs of living. In the past decade or so, there’s been a large push towards STEM-oriented careers because they pay well, and these jobs can be found across industries.

Data analysts must have knowledge of web scraping, data collection, and data analysis. Web scraping, the automatic extraction of public data from webpages, is an essential tool for data analysts because it helps them access good data sources and save valuable time. Data extracted through scraping can supplement both internally and externally collected data If you want to know how to become a data analyst and with web scraping to your advantage, check out our tips and essential skills below.

If you know the basics of becoming a data analyst, then use the table of contents to discover how to incorporate web scraping into your work.

Table of Contents

How to Become a Data Analyst with Web Scraping

web data analyst career

Data analysts are responsible for drawing meaningful insights from data through analyzing it. Therefore, data analysts can be found not only at most companies but also within multiple departments. For example, you might have a data analyst exclusively for marketing and have another analyst working on sales data. Because of this, there is no one path determining how to become a web analyst. Thankfully, it is a career that is only growing as data becomes more influential in decision making across industries.

For those no longer in school, you may be wondering how to become a data analyst with no experience. Thankfully, web scraping is a skill you can easily learn. Web scraping helps you extract data from web pages which you can then analyze for insights on how to grow as a business or solve operational issues.

Web Scraping and Data Analysis

 become a data analyst career path

Because data analysis is needed in many industries, there is also no one path for how to become a database analyst. As mentioned above, many larger companies have multiple departments that each have different data analysts. However, web scraping is a skill useful for anyone to learn, even local artists selling their jewelry online. Every business can use scraping to collect data on how to increase profit and better understand their target audience.

To work in a larger corporation as a data analyst, you will likely need a degree in the related field. If you want to do data analysis for a clothing brand, it is best to study fashion merchandising or related fields so that you have enough context for the industry to understand what types of data are most relevant. Many schools also have data analytics programs if your goal is to work in data regardless of the specific industry. Thankfully, web scraping is useful in every industry and at any position level.

Again, while being a data analyst can be a lifelong career, web scraping skills are necessary for even small business owners. There are ways to increase data literacy within your organization despite whether or not you hire a specific data analyst.

Skills You Need to Be a Web Data Analyst

how to become a data analyst with skills

There are many skills, technical and creative, that are required to be a successful data analyst. While you ask yourself, “How do I become a data analyst?” These are some skills you should master to help you get started.

Structured query language (SQL)

Structured query language, or SQL, helps you access, manage, and manipulate databases. Knowing structured query language especially helps when working with structured data, which is data in a fixed field in a file or record. These skills are crucial when extracting data from various data sources, whether it be internally collected or externally collected. While structured query language is one of the more technical skills necessary to become a data analyst, it is crucial to understanding the job and working with data. Web scraping is an easy way to access great data sources for organizations unable to conduct their own research.

Web scraping

Web scraping is used by data analysts worldwide to perform data analysis. Having scraping skills will set you apart from others and prove your ability to engage with data no matter your job. Knowing how to communicate data insights to your team is equally important. Web scraping makes data patterns more clear, which gives you more time to use your imagination and create the perfect presentation.

For smaller organizations, web scrapers can complete this task by helping you extract data from web pages without having to build your own program. Web scraping helps you save time and money. For larger organizations interested in developing their own data programs, web scraping is a great tool that can be used to gather supplemental data to help contextualize programmed data collection.

Data visualization

On the more creative side, data visualization skills are crucial to establishing a career as a data analyst. Data visualization is your ability to present data-based insights in a creative way that helps generate communal understanding within a team. As I mentioned earlier, understanding team goals and the purpose of data collection is essential to gathering insights for a specific project or problem.There are many data visualization tools that help you create presentations, charts, or other visual representations of data. Having the creative ability to understand how to present data to a team, specifically a group of people less versed in data collection, is an invaluable skill that goes beyond simply knowing technical skills.

If you’re more creatively oriented, learning how to use creative data can help separate you and your organization from those who focus too much of their energy on collecting data without properly using and presenting it.

Data Analyst Career Path

web scraping web data analyst

As I mentioned before, web scraping is an essential aspect of data analysis. Whether you are a small organization that heavily depends on scraping for data collection or you’re already a data analyst looking for supplemental sources, web scraping can strengthen your insights and help you grow. Below are examples of how to best use web scraping in data analysis.

Perform customer sentiment analysis

While many large organizations are focused on easily collectible data regarding sales, product details, or price, customer sentiment data is increasingly important. Especially for those unable to afford running in-person focus groups, online customer sentiment data is a way to collect sentiment data without creating new teams dedicated to it.

A primary way to collect customer sentiment data is to use review sites and review sections of eCommerce sites. You can always read through reviews yourself and try to gain insights, but scraping helps compile reviews across platforms to help you more easily detect patterns. With this information, you can recognize which parts of your process (product, advertising, shipping) needs the most improvement in the eyes of your customers.

For finding new customers or understanding what other products/services they may like, social media is full of useful data. When you scrape social media profiles, you learn about what accounts follow them, who they’re following, and what kind of content they enjoy. This information makes it easy to sell related products. For example, if you sell yoga mats and notice lots of your clients use essential oils then selling your own oils or essential oil diffusers is likely to be a success.

Track industry changes

Being able to recognize industry changes in a constantly shifting world is necessary for any organization trying to gain traction. Since industry-specific information is changing rapidly, it can be hard to continually manually collect this information. Web scraping helps you collect this data quickly and efficiently, ensuring it is up to date and useful the moment you analyze it. For other rapidly changing data fields, web scraping can help you track these changes without constantly shifting your built programs or having to create new ones.

Custom scraping solution

Many large or specific data projects require a custom scraping solution. At Scraping Robot, we help clients across industries create scraping solutions that help fit their specific needs whether that be scraping in large quantities (millions or billions) or finding very niche data. By working with our team, you do not have to worry about developing your own programs or managing them. While this solution is ideal for smaller organizations with less manpower, it is equally useful for large organizations looking to move beyond basic data and create a unique scraping solution. When your data analysis skills hit a wall or you have a project that requires more technical collaboration, the Scraping Robot team is a great source of support. If this solution sounds right for you and your organization, contact us to get started.

In addition to working directly with our team, our blog also has many articles about how to use scraping in different industries and scenarios. These posts will help guide you in your journey to becoming a data analyst.

Conclusion

 how to become a data analyst

While the question of how to become a data analyst can feel overwhelming in a world where the field is rapidly changing, there are skills needed across the board to generate unique data insights and share them in innovative ways. However, developing and managing an entire data analysis department isn’t feasible for many organizations large and small. Web scraping, the automatic extraction of data from web pages, is an essential tool to help you strengthen your data analysis skills and supplement the data you collect elsewhere. In order to properly analyze your data and grow, a combination of data analyst expertise and web scraping is your best bet.

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