Data is a collection of raw information or facts that is designed to be processed and analyzed in order to gain useful intel. These facts come in various forms, i.e. numbers, text, images, sound, etc. and is either structured or unstructured. Data is often used to support business decisions and can be processed using different tools and techniques, such as statistical analysis and machine learning (ML) algorithms. Data is messy but when it’s properly turned into visualizations using graphs, charts and 3D models it makes the information more digestible.
What is a Database?
A database is a collection of organized data that is typically sorted into rows (entries) and columns (attributes). They are typically used to store transactional data like customer profiles, product details, and sales transactions. Databases are intended to be queried and updated right away, making them the simplest and easiest way to manage real-time data.
What is a Data Warehouse?
A data warehouse is a centralized repository of data that is semi-organized and readily available for reporting and analysis. Unlike a database, which is designed for transaction processing, a data warehouse is optimized for data storage and organization. It typically contains a large amount of historical data that has been cleaned, transformed, and integrated from multiple sources. Data warehouses are engineered to support business intelligence (BI) operations and help augment decision-making activities and operational strategies.
What is a Data Lake?
A data lake is a collection of raw, unstructured data that is stored for later formatting. Unlike a database or data warehouse, which are structured and organized, a data lake is designed to hold aggregated data in its original, unprocessed form (think raw 1’s and 0’s). This allows businesses to continuously collect and store all of their data, regardless of its structure or format, for future use. Data lakes are often leveraged by large organizations who collect large quantities of data from multiple sources; allowing for advanced analysis and future machine learning activities.
Tl;DR: A database is a pool of structured, transactional data that can be accessed and updated in real-time. A data warehouse is a collection of historical data optimized for reporting, analysis, and 3d modeling. Lastly, a data lake is a repository of raw, unstructured data that is used for big data analytics, statistical analysis and to feed machine learning algorithms. Each type of system is equally important in the Business Intelligence (BI) landscape and has its own unique characteristics and applications.
