Data Warehousing Specialists
Do you remember what the e-commerce site Amazon looked like ten years ago? Do you remember how products used to be displayed on the site, or the types of products that were available on it? Do you remember what shipping costs used to be, or which payment methods were allowed? Is everything on it still the same, or have new features and capabilities been introduced? You've surely noticed that there are always updates happening across various e-commerce platforms, or even in social media apps — for example, Reels weren't among Facebook's features a few years ago, and some e-commerce sites didn't used to allow returning a product after purchase, or offer a way to track a product after ordering it from their platform. These changes to how these sites and apps operate don't happen randomly — they're the product of years of in-depth studies and analysis. You should understand that everything that happens on these platforms gets saved and recorded in specific databases — there are databases for storing users' personal data, other databases for recording transactions and the dates products are ordered, shipped, and delivered, and others for logging calls and emails related to complaints and inquiries. Even the ways and patterns in which customers browse the sections of these platforms are recorded. These various databases, where everything is logged, are combined together into other, much larger databases called "data warehouses," which make it possible to record and analyze the huge volumes of data collected over the years. They're specifically designed to help data scientists track, understand, and analyze data and draw conclusions that are later turned into decisions to roll out new features or develop business strategies. This isn't limited to e-commerce companies or social platforms — nearly every sector and industry needs data warehouses to develop its operations. Data warehouses are specific technologies, systems, and computer programs designed by specialists called "data warehousing specialists" — they're responsible for building, developing, maintaining, and fixing these warehouses if anything goes wrong with them. So today we'll be talking about the profession of "data warehousing specialist," one of the most important jobs in our world today.
Meet the Writer: Waleed Abo Omiraa
What You'll Actually Do
The core tasks and responsibilities that fill a typical day.
- Test software systems or applications for software enhancements or new products.
- Review designs, codes, test plans, or documentation to ensure quality.
- Provide or coordinate troubleshooting support for data warehouses.
- Prepare functional or technical documentation for data warehouses.
- Write new programs or modify existing programs to meet customer requirements, using current programming languages and technologies.
- Verify the structure, accuracy, or quality of warehouse data.
- Select methods, techniques, or criteria for data warehousing evaluative procedures.
- Perform system analysis, data analysis or programming, using a variety of computer languages and procedures.
- Map data between source systems, data warehouses, and data marts.
- Implement business rules via stored procedures, middleware, or other technologies.
- Develop and implement data extraction procedures from other systems, such as administration, billing, or claims.
- Develop or maintain standards, such as organization, structure, or nomenclature, for the design of data warehouse elements, such as data architectures, models, tools, and databases.
- Design and implement warehouse database structures.
- Create supporting documentation, such as metadata and diagrams of entity relationships, business processes, and process flow.
- Create plans, test files, and scripts for data warehouse testing, ranging from unit to integration testing.
- Create or implement metadata processes and frameworks.
- Develop data warehouse process models, including sourcing, loading, transformation, and extraction.
- Design, implement, or operate comprehensive data warehouse systems to balance optimization of data access with batch loading and resource utilization factors, according to customer requirements.