Data mart tutorial curriculum

Are you interested in learning about data marts? Online courses can help get you up to speed.

An introductory data mart course can cover the basics, such as the purpose of a data mart and its role in data management and decision-making processes. You may have a chance to study data mart architecture, including dimensional modeling, subsets of data, logical and physical components, and retrieval and analytical methods. By reviewing data mart examples, you may also be able to better understand the differences between data marts, data warehouses, and data lakes. 

With a firm understanding of the basics, you can move on to an intermediate course. These courses can cover the elements of designing a data mart, including business requirements, data resource identification, data subset definition, and logical and physical data mart structure creation. Study the steps involved in the data mart construction process, such as creating the physical database and storage structures, creating schema objects like tables and indexes, and optimizing table setup. You may also learn how to translate database structures into business terms for user interaction. 

For even more experienced learners, advanced level courses may explain how to make a data mart in SQL, along with the correct statements and queries for its creation and implementation. You can also potentially learn how to ensure the long-term viability of a data mart, including providing secure access, managing data growth, optimizing system performance, and ensuring data availability in the event of system failures.

edX offers a variety of educational opportunities for learners interested in studying data science, as well as a host of other disciplines. A boot camp can provide flexible, hands-on learning for those who want to upskill quickly, while executive education courses are designed for busy professionals. You can also pursue a more comprehensive curriculum by way of a bachelor’s degree program or, for more advanced learners, a master’s degree program. Find the right learning path for you with edX.

Explore data mart jobs

Knowledge of how to effectively utilize data marts can be beneficial for a number of professionals roles, including: 

• Technical lead: Oversees software solutions' design, development, and implementation. They lead a team of developers, conduct technical reviews, ensure adherence to guidelines, and collaborate with stakeholders to gather requirements and deliver high-quality solutions.^{Footnote 3}

• QA tester: Ensures the quality and reliability of software applications. They design and execute test plans, identify and report defects or issues, and work closely with developers and stakeholders to address and resolve them.^{Footnote 4}

• ETL tester: Validates the Extract, Transform, Load (ETL) processes involved in data integration. They design and execute test cases to ensure data accuracy, integrity, and completeness throughout the ETL pipeline.^{Footnote 5}

• Application programmer: Develops and maintains software applications. They write code, design user interfaces, implement functionality, and ensure applications' smooth operations.^{Footnote 6}

Each of these roles will have different education and skill requirements. For example, you may be able to build job-ready skills in a coding boot camp. However, some employers may seek candidates with a degree in computer science or data science, depending on the role. Before deciding on a specific learning path, research the positions you hope to pursue and align your coursework with your career goals.

How to use data mart in your career

Professionals in various roles can use their knowledge and skills to implement and manage data marts successfully. 

For example, technical leads can leverage their understanding of data mart concepts and architectures to guide the development team, make design decisions, ensure scalability, and align the data mart solution with business requirements.

Similarly, as a QA tester, you can use the knowledge of data mart structures and functionalities to design and execute test scenarios, validate data integrity, and ensure the quality of the data mart solution before its deployment.

If you are an ETL tester, you can apply your expertise in ETL processes to validate the accuracy, completeness, and performance of data extraction, transformation, and loading operations in the data mart. 

An application programmer utilizes their understanding of data mart integration and APIs to develop and maintain applications interacting with the data mart. They work on implementing data extraction and transformation routines, creating user interfaces, and ensuring seamless data integration and flow.

Are you interested in making a career switch? Start building the skills you need today with edX.