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Learn how to leverage data marts to make informed decisions. Start using this valuable data storage technique to enhance your data analysis skills.

What is a data mart?

A data mart is a simplified form of a data warehouse that serves a single business unit rather than the whole organization. It helps a particular team or department gain insights quickly without dealing with the complexity of a data warehouse. At the same time, it enables you to avoid the manual data consolidation process, which can be error-prone, time-consuming, and costly.1

Data marts can help a department make informed decisions backed by data. For example, a marketing team can leverage data marts to analyze how customers react to their marketing campaigns. A data mart is designed based on the specific requirements of a department.2

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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.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.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.5
  • Application programmer:Develops and maintains software applications. They write code, design user interfaces, implement functionality, and ensure applications' smooth operations.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.

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    Frequently Asked Questions

    What are the primary differences between a data warehouse and a data mart?

    Data marts and data warehouses differ in size, range, and sources. A data mart is smaller, serves a particular business unit, and consolidates data from a few sources. On the contrary, a data warehouse is larger in scale, serves multiple business units of the organization, and integrates data from numerous sources across the enterprise.

    What is an example of a data mart?

    A retail company may have a data warehouse storing all sales, inventory, and customer data. They can create data marts for each region, like "North Region Sales Data Mart" or "South Region Inventory Data Mart." These data marts hold region-specific data, enabling managers to analyze and make decisions based on localized information. Alternatively, they might make a data mart for the marketing department, sales department, or human resources.

    How can you build a data mart?

    You can build a data mart following these five steps: design, construct, data transfer, data access, and manage. First, gather requirements, identify data sources, and create a logical and physical design for the data mart. Then, create the physical database, including tables, indexes, and access controls. After that, set up a procedure for cleaning, formatting, and transferring data to your data mart. Now you can use data to generate insights or develop interfaces for non-technical users. Last, define user access controls, optimize performance, and ensure system availability.

    How does a data mart work?

    A data mart helps a business unit, whether a team or a department, make informed decisions based on insights generated by data. It receives data from a data warehouse or external sources through ETL processes, and business analysts use analytical tools to retrieve and analyze data from the data mart.

    Why use a data mart?

    Data marts help a business unit make informed decisions while avoiding the complexity of data warehouses. Also, they offer various advantages over manual data consolidation, such as convenience, fewer human errors, and low cost.

    What are the three types of data mart?

    The three types of data marts are dependent, independent, and hybrid data marts. Dependent data marts extract some portion of data from an existing enterprise data warehouse. On the other hand, independent data marts are stand-alone systems without a data warehouse. And a hybrid data mart uses data from a data warehouse as well as its own system.

    1. What is a Data Mart?Oracle. Retrieved on May 22, 2023.

    2. What is a Data Mart? IBM. Retrieved on May 22, 2023.

    3. What is a Tech Lead? The 4 Worst Things About This Promotion. (2020). Clockwise. Retrieved on May 22, 2023.

    4. Skills Required to Become a QA Tester. (2023). BrowserStack. Retrieved on May 22, 2023.

    5. 8 Tips to Becoming a Great ETL Tester. Panoply. Retrieved on May 22, 2023.

    6. How to Become an Application Developer: Everything You Need to Know. (2023). Kinsta. Retrieved on May 22, 2023.