Elevate Your Data Modeling Skills With These Top Certification Options


The Gist

  • Opportunities galore. The market is overflowing with opportunities for learning data literacy. There are free and paid resources available that can help improve your data modeling skills.
  • Manageable chunks. When selecting an online course, focus on the practical applications of the skills being taught and the course structure should be broken into manageable chunks of no more than 20 minutes each. The course should provide an A-to-B learning experience with a focus on the practical applications and the reasons for choosing certain techniques.

Analysts often feel extraordinarily overwhelmed when it comes to collecting data. Those feelings take on a new level when they are required to learn new skills for managing data. Marketers have more ways to process data, analyze data and report insights that support their organizational objectives. This can make it challenging to determine the best starting point for learning how to extract insights from data and develop data literacy with their current tool set.

Free and Paid Resources for Marketing Training

Fortunately, opportunities for learning data literacy are on the rise, with a growing number of online courses focusing on the key concepts that drive meaningful business outcomes. Many resources exist now for marketing training (some are covered here). There are further resources that can increase your data literacy. Some courses are free certifications, while others are training supplements for tools and mentorship programs for concepts associated with data such as cybersecurity, agile development and other cloud services.

Excel: Widely-Used Tool for Business Intelligence

Excel remains a widely used tool, so learning resources exist seemingly everywhere, such as LinkedIn’s Education Center and continuing education programs such as University of Delaware Professional & Continuing Studies. One great course for touching up your Excel skills is Analyzing Data with Excel from IBM. This five- week course covers several features in the tool. Another is from a developer bootcamp called freeCodeCamp. The course, called MS Excel Tutorial for Beginners, offers the basics for using Excel, including the latest features. 

SQL: A Workhorse for Querying Databases

When it comes to databases, marketers are more than familiar with SQL. Data has reinvigorated ways to query databases. Yet despite the overwhelming variety of database options, many firms rely on data hosted within SQL tables. SQL has been around the corporate tech block, so in a fast-paced tech world, it is a workhorse as familiar as Excel. It is no wonder people are rediscovering the logic of SQL joins and queries in their training choices. 

There are numerous platforms for learning SQL. Microsoft, for example, offers Azure SQL Fundamentals, a course featuring free certification vouchers for participants in its cloud-based SQL labs and learning paths. The course is one of five modules Microsoft offers in support of its Azure services. There are other live training and certifications available from Microsoft (You can click here for schedules and information). The free CodeCamp bootcamp also offers an SQL course online.

Python: Versatile Language for Constructing Apps, Websites, and Data Models

Python has become extremely popular in business because of its broad use for constructing apps, websites, chatbots and data models for machine learning. Created 20 years ago, it quickly caught on with programmers due to its readability and ease of use. Python is as adept at solving issues in mathematics, engineering and deep learning as it is in manipulating and visualizing data.

Like SQL, there are sources aplenty for strengthening your data modeling skills in Python. Many are aimed at developer audiences, but many more are offering courses straightforward enough to allow a marketing analyst to understand what can be done with data brought into a Python environment. They include IBM Data Science Professional Certification (which also includes SQL in its sessions) and Datacamp, which specializes in courses for data engineers, programmers and data scientists (Python for Marketing) .

R Programming: Limitless Possibilities for Data Analysis

When it comes to R Programming, the sky’s the limit for what kinds of courses exist. The use of R has been dramatically extended, thanks to data practitioners who found applications for research and very academic statistics through R, and then created packages to expand the usability of the language. Now there is an R course tailored for many subjects and providing compelling applications in real world cases.

Marketers can start with a DataCamp certification program called the DataCamp Career Track, which includes hands-on projects and quizzes. Another resource is DataQuest (Data Analyst in R). Additionally, edX, which also hosts the IBM program, offers a MicroMasters Data Science program, which includes an R programming course. John Hopkins University offers a Data Science Specialization via Coursera that includes an R Programming course as well.

Marketers can also consider Posit, a development company that publishes the widely used integrated development environment (IDE), RStudio. Because RStudio is the go-to solution among data science practitioners, Posit provides resources through webinars, blogs and cheat sheets that summarize and explain functions from the most frequently used libraries like dplyr and ggplot2.

Related Article: Excel, SQL, Python: What’s Your Data Flavor for Customer Experience?

Tips for Selecting Online Courses to Enhance Your Data Literacy and Business Outcomes

Picking good courses or platforms to follow involves more than learning the latest technical steps. You can learn the definition of a task, but a course should answer key questions on why certain tasks or techniques are chosen, with lessons that teach a point A-to-point-B experience.

A good course should focus on the practical applications of the functions and dependencies being taught, which should spark ideas for you to apply in your workload or datasets. You’ll learn how to bring about change to your business operations, foster improved collaboration among your team and make data-driven decisions with enhanced optimization. 

A course should be broken into reasonable chunks of no more than 20-minutes each. This allows you to focus on each specific step and delve into the details of the code, gaining a comprehensive understanding of the functions and their creation. Most projects with data are an assembly of ideas, using data and code to achieve a specific goal. Breaking the course into manageable segments helps clarify the purpose and objectives.

While developing skills, you may have a nagging feeling of knowing and not knowing when it comes to the material. That feeling is perfectly OK — there are a lot of ways to apply programming syntax, so it is easy to get into the weeds of a topic. But a small amount of initial uncertainty is not a sign that you are not learning or extending your skills. It takes time to fully absorb and internalize what you’ve learned, even after completing a course.



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