Data never sleeps. According to a combination of many statistics, forecast experts predict that around 7 million Terabytes of data will be produced by online users in 2023 alone. Any online actions are used for analytics, statistics, tracking, reporting, machine learning, etc. Data is a pivotal production factor, holding significant importance in developing products and services across all contemporary enterprises. However, it is essential to note that data alone cannot create value for companies. Companies are expanding by collecting, storing, processing and analysing data to effectively use data as a production factor to gain insights and knowledge that help improve business processes. As Data availability, quality and transparency increase business valuation. One of the ways to become smarter with data handling comes with Data Lakehouse. Implementing a Data Lakehouse empowers companies to attain superior data accessibility, streamline data infrastructure, and trim expenses. This is achieved by eliminating the need to oversee various distinct data storage, integration, and analysis systems. The concept of a Data Lakehouse combines data warehousing and data lakes, offering a unified platform that harmonises these functionalities within a singular system. A Data Warehouse is a central database designed specifically for analysis and reporting. A data lake is a scalable data platform on which structured and unstructured data can be stored, managed and analysed. Unlike traditional databases, which are usually limited to a specific schema, a data lake is more flexible and can store large amounts of data of different types and sources. As data usage is evolving, so will its need for new tech standards.
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