A primer to the world of data

Data plays a crucial role in guiding business decisions and powering AI products. The process of transforming raw data into useful knowledge involves several stages, including gathering, extracting, processing, and using the data. Modern data stacks are hosted in the cloud, which offers accessible, cheap, performant, and scalable off-the-shelf solutions to a range of IT infrastructure needs. The cloud enables organizations to easily scale their operations up and down without the need for proprietary IT infrastructure. Data sources can originate from various sources such as sensor inputs, manual data entry, digital documents, and software triggers. Organizations use a wide range of cloud applications to provide services like customer relationship management, payment processing, and enterprise resource planning. The centralization of data is achieved through data warehouses or data lakes, which store both structured and raw, unstructured data. Data pipeline tools are used for extraction and loading processes. Processing the data involves transformations such as cleaning, summarizing, and pivoting tables. Automating the ETL process requires careful coordination of different pieces of transformation software called orchestration. The rise of cloud technology has made the labor-intensive ETL approach obsolete, with ELT being a more efficient alternative. Data governance is an important concern that arises alongside centralizing and processing data to ensure proper usage, integrity, and security of data. Ultimately, the data from a data stack is meant to guide decisions at every level of an organization and power AI products through analytics or business intelligence platforms.