Nowadays, data is very important, it helps the companies, business owners, other individuals, or even the government use the data when it comes to decision making. Because data can produce a better result. But when the data becomes bigger, confusing, and unreliable, the data you have can't be trusted, which does not help you to decide whatever purpose of your data is. This is the reason why data catalogs come into the picture, to help you to organize the data and help you analytically or business.
What is Data Catalog?
A data catalog is a detailed inventory of all data assets in an organization, designed to help data professionals quickly find the most appropriate data for any analytical or business purpose.
What is a metadata catalog?
A metadata catalog is nothing but a collection of all the data about your data. Metadata can include the data source, origin, owner, and other attributes of a data set. These help you learn more about a data set and evaluate if it is well-suited for your use case.
What is Data Swamp, Data Warehouse, & Data Lake?
Data Swamp is a little organization or business that has no system, no curation, no active management throughout the data life cycle, and no contextual metadata and Data Governance. Data Swamps have the problem of being of little use or unusable and frustrating.
Data Warehouse is a type of data management system that is designed to enable and support business intelligence (BI) activities, especially analytics. Data warehouses are solely intended to perform queries and analysis and often contain large amounts of historical data. In computing, a data warehouse, also known as an enterprise data warehouse, is a system used for reporting and data analysis and is considered a core component of business intelligence.
Data Lake is a centralized repository that allows you to store all your structured and unstructured data at any scale. Also, can be established "on premises" (within an organization's data centers) or "in the cloud" (using cloud services from vendors such as Amazon, Microsoft, or Google).
Let's dive into the data catalog for a moment, imagine that you got a new project that has huge data. But before you can use the data you need to validate if the data is accurate and reliable. Also, a need to study the data what the relevant tables and how to use them to make your job more efficient. But you have to spend days or even months doing it. Especially compared to set of table, which is the right tables, can you combine both tables, and so on. These are some of the examples you might be experiencing without a data catalog. Data catalog can help you with data discovery, search, organizing, collaborate, and be able to use query tools to make everything efficient and reliable when it comes to data. It can simplify the extensive process of learning, maintaining, and sharing data. Which can give you more time to discover more valuable answers from your data and gives you more focus on doing other work. Data catalog learn from the data collected from human, then human learn the result from the data catalog. Its never-ending loop, where machine learning from human, human learn from the machine and restart the process again. The more data collected the more it will be accurate and efficient for delivering the result. Let say that your company has a lot of sold products, data catalog will organize this data and let you see which product is in demand and has a better result. This helps you to know which product needed to be restocked and which product is not selling. This is an example of how data can help you in your decision-making. While the metadata catalog can help your team discover, manage and understand all your data assets in one place. This is important because the consumers of data are quickly increasing. Companies are increasingly investing in setting up data lakes, big data initiatives, and creating self-service data analytics ecosystems.
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