What Is a Data Mining Specialist?
Are you interested in using data to solve organizational problems? Do you want to influence business strategy and help build stronger, more efficient and responsive operations? Data mining may be an opportunity to combine decision-making with strong analytical skills.
A data mining specialist analyzes information to find the relationships, patterns and insights that help drive businesses’ decision-making processes. They are experts in research, data collection, data cleaning and model deployment.
Continue reading to learn more about data mining specialists, what kinds of skills are necessary for this career and the different pathways to becoming a data mining specialist.
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What Is Data Mining?
Data mining is defined as “the process of uncovering patterns and other valuable information from large datasets,” according to IBM. This process is used to yield more efficient and effective business decisions, such as predicting customer churn to target offers or identifying product associations to better organize retail shelves.
IBM describes data mining as falling into two main categories: describing existing data and predicting future outcomes. The data mining process involves sifting through large amounts of information to find anomalies and points of interest that could prove useful.
What Does a Data Mining Specialist Do?
A data mining specialist’s day-to-day life will look different depending on the industry and company they work for. However, whether a data mining specialist works for a wireless company, grocery store or crime prevention agency, they likely will share many of the same fundamental processes and goals.
Data mining specialists’ responsibilities may include:
- Data cleaning to make datasets useful for internal and external stakeholders.
- Providing exploratory analysis to organizational leaders.
- Creating models, testing them against hypotheses and publishing those models for analytics or business intelligence projects.
- Deployment of models within the organization, to be shared with customers or to be used to generate a report for stakeholders to prove its reliability.
Skills for Data Mining Specialists
Just like their job responsibilities, the skills required for data mining specialists vary based on organizational and team needs. Microsoft’s data mining documentation details a process that requires soft skills, such as defining problems and communicating solutions, and hard skills, such as building effective models and describing data.
Some common data mining skills include:
- Problem identification and data selection. Data mining specialists should be able to critically analyze large datasets and discern what is and is not important to their primary question.
- Understanding of statistical methods. These professionals must accurately interpret reports, know how to validate data and produce statistically sound conclusions.
- Programmatically modeling internal data. Data mining specialists primarily utilize three types of models: descriptive, predictive and prescriptive modeling. Together, these provide a comprehensive understanding of an organization’s data, goals and potential decision outcomes.
- Communication of technical information to non-technical audiences. Data professionals should be able to share analysis with executives and external stakeholders. Data visualizations, presentations and written reports should be concise, clear and effective tools in the hands of a data mining specialist.
- Data engineering and organization. Data engineering is the ability to manage and organize data flows, pipelines and storage systems. A successful data mining specialist should be able to create a system that handles large amounts of data.
Common Ways to Study Data Mining
There is not just one pathway to becoming a data mining specialist. The skills required for this field can be acquired in a number of ways.
Earn a Bachelor’s Degree in a STEM field
Earning a four-year degree in data science or data analytics or a related field like computer science can be a comprehensive way to acquire data mining knowledge. For example, an online bachelor’s in computer science may help prepare students with many of the statistical, modeling and engineering skills used in data mining.
A bachelor’s program also provides a breadth of courses to help grow soft skills, such as communicating technical information to non-technical audiences and critically thinking through analytical problems.
Get Trainings in Bootcamp Programs
Tech bootcamps, multi-week training sessions that focus on a specific set of technical skills, can be a great way for students to explore data mining and determine if the career is right for them. The variety of bootcamps available means they can serve different kinds of students, such as those who need part-time learning or online opportunities.
Many bootcamp programs may help participants learn programming languages and statistical skills used in data mining. For example, coding bootcamps have a focus on developing web development skills; data science bootcamps or a similar bootcamp in data analytics may help data mining specialists build analytical skills.
Obtain an Advanced Degree in a STEM field
Students can also consider pursuing an advanced degree, such as a master’s in data science or an online master’s in data science. More advanced programs will be accompanied by more specific coursework and skill-building. They can also be useful for people who want to pivot career fields entirely and do not have an undergraduate degree in a STEM field.
Study Short-Term Online Courses
Short courses allow students flexibility and speed whereas a full degree program may not. For example, an online data science short course can help students learn the fundamentals of programming and statistics concepts, as well as skill-building toward a career in data mining.
Consider Certifications for Data Mining
Additionally, there are a few types of certifications in data science and data analytics that individuals interested in data mining can earn. Relevant data science certification programs could include a business analytics certificate or an online AI program that teaches model building. Overall, a certificate program can be useful for individuals looking to build specific skills and experience in a narrow discipline.
Data Mining Specialist FAQs
Pursuing a new field or area of expertise can create a lot of unknowns. Below are some frequently asked questions among those interested in a data mining career.
The amount of time it takes to become a data mining specialist can range from a few months to four years depending on the path you choose and your background. An undergraduate degree in data science or computer science typically takes four years, and a graduate degree takes one to two years. If you choose to enroll in a bootcamp, it may take a few months to a year.
For many, pursuing data mining may lead to a lucrative career, but it depends on the individual’s preferences and experience. Like other data science roles, earning potential is closely related to industry choice. For example, would you rather pursue a career in the nonprofit sector or a for-profit startup? Additionally, individuals may consider other factors beyond earnings, such as a company’s mission, to determine whether this career is worthwhile.
Data mining skills include technical (or “hard”) skills and non-technical (“soft”) skills. Technical skills could include an understanding of statistics, programmatic modeling and data engineering. Soft skills among successful data mining specialists could include strong communication abilities and creative problem solving.
Overall, a successful data mining specialist should be able to balance a strong technical understanding with the competency to act on and communicate those findings.
Compared with business intelligence or data analytics, data mining is a branch of data science, while business intelligence focuses on tracking key performance indicators for an executive audience.
Data mining is often focused on more specific business problems. Data mining also involves more open-ended exploration of data and pattern recognition than a field like data analytics, which focuses on hypothesis testing and analytical methods.
Last updated January 2022