{"id":2220,"date":"2022-07-04T03:57:44","date_gmt":"2022-07-04T08:57:44","guid":{"rendered":"https:\/\/www.dpriver.com\/blog\/?p=2220"},"modified":"2022-07-23T06:00:20","modified_gmt":"2022-07-23T11:00:20","slug":"a-step-by-step-guide-to-metadata-management","status":"publish","type":"post","link":"https:\/\/www.dpriver.com\/blog\/2022\/07\/a-step-by-step-guide-to-metadata-management\/","title":{"rendered":"A Step-by-Step Guide to Metadata Management"},"content":{"rendered":"

### Why do you need metadata management?<\/h3>\n

Effective metadata management<\/strong><\/a> in an organization provides the correct context and description for data. Furthermore, in order to understand and trust data, one needs to understand its context – how the data is produced and how it is used. In addition, you need to know what decisions are made based on this data and how to use it to gain a better competitive advantage.<\/p>\n

To succeed in this new digital age, organizations need to create granular data products. A data product is not just a report or analysis, but a comprehensive solution. Deliver analytical, comparative, insightful information to the right people at the right time and on the right device.<\/p>\n

It is difficult to create these data products without a complete metadata management solution. As data volumes grow and big data technologies explode, CDOs (Chief Data Officers) must look to manage their data more efficiently through metadata. According to the latest estimates, the metadata management industry size will reach around 7.85 billion by 2022 and will grow by 27% year-on-year. In this article, we’ll give you a step-by-step guide to metadata management.<\/p>\n

### What is metadata?<\/h3>\n

Metadata<\/strong><\/a> is “data [information] that provides information about other data. This understanding comes from setting data in context, allowing it to be reused and retrieved for multiple business purposes and times.” According to the University of India, “Metadata is data about data, descriptive information about a particular data set, object or resource, including its format, when it was collected and who collected it. Although metadata most commonly refers to network resources, it can also be physical or electronic resources. It can be created automatically using software or manually entered.”<\/p>\n

Some typical metadata elements of structured or unstructured data are: title, description and abstract; tags and categories; created time and creator; last modified by and time; who can access or update.<\/p>\n

In addition to this, metadata in an organization is categorized as:<\/strong><\/p>\n

\n
1. Metadata for structured data: Includes column structure for database tables, header rows for CSV files, column definitions from JSON, XML, and Avro files.<\/li>\n
2. Business metadata: Includes security level, privacy level, and acronym level. Both IT and business require high-quality metadata to understand the information at hand. Without useful metadata, organizations risk making bad decisions based on bad data.<\/li>\n<\/ol>\n

   ### What is metadata management?<\/h3>\n

   Library catalogs are one of the classic and oldest examples of metadata management. Next is the Yahoo search engine, where all the metadata from the various websites is indexed. Finally, the revolution happened when Google designed metadata by working with actual data. It provides users with an unprecedented in-depth search experience, enabling users to search in the desired context.<\/p>\n

   Metadata Management<\/figcaption><\/figure>\n

   However, enterprise metadata management is still at the library catalog level (done manually) or at the Yahoo level (done through the use of various metadata management products).<\/p>\n

   An ideal metadata management program should be data-driven and derived from context. Providing answers to all common questions such as who, what, when, where and why about the data is metadata management.<\/p>\n

   ### How to do effective MDM?<\/h3>\n

   Here are a few steps to ensure it:<\/p>\n

   Placement Policies and Procedures:<\/strong> Effective metadata management begins with the policy, procedures, tools, and manual management of metadata. Employees are the center of metadata management. Companies must have tools for smooth interaction between employees on data and metadata. The following should be roles for effective metadata management:<\/p>\n

   \n
   - The role of CDOs and executives: Define metadata management rules and use some tools to enforce them. These rules should include various security aspects and methods of changing metadata.<\/li>\n
   - The role of analysts and other data citizens: Analysts<\/strong><\/a> should follow metadata management rules. Additionally, if they ask deep questions about data and metadata, those questions and comments can be saved. Later, this can benefit other analysts working on the same data.<\/li>\n<\/ul>\n

     Features of MDM Tools: <\/strong>There should be robust tools to provide access to metadata, and they should enforce all the rules defined by executives. Some of the features these tools can provide include:<\/p>\n

     \n
     - Sample data: Here, we open the table on the data that generated the sample data, providing the data context for the metadata. Thus, we enrich our understanding of metadata.<\/li>\n
     - Data statistics (configuration file): Statistics provide answers to common questions such as counts, distinct values, most common values, empty counts, maximum and minimum values.<\/li>\n
     - Lineage<\/strong><\/a>: It helps to understand the source of the data, how it is transmitted, and the various transformations that take place before it arrives. In addition, it is possible to understand other uses of the data.<\/li>\n
     - Previous communication: Communication is key to effective metadata management, so it’s important to keep all metadata-related conversations in one place. Additionally, all comments and comments about that metadata should also be available here.<\/li>\n
     - Relationship to other metadata: It is critical for MDM tools to find relationships between data to make data search possible. There are multiple ways to do this – manually, manually curated, automatically through metadata semantic matching, or automatically through data matching.<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"

       Why do you need metadata management? Effective metadata management in an organization provides the correct context and description for data. Furthermore, in order to understand and trust data, one needs to understand its context – how the data is produced and how it is used. In addition, you need to know what decisions are made based on this data and how to use it to gain a better competitive advantage. To succeed in this new digital age, organizations need to create granular data products. A data product is not just a report or analysis, but a comprehensive solution. Deliver analytical,\u2026<\/p>\n","protected":false},"author":3,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[66],"tags":[26,60,52],"blocksy_meta":{"styles_descriptor":{"styles":{"desktop":"","tablet":"","mobile":""},"google_fonts":[],"version":5}},"yoast_head":"\nA Step-by-Step Guide to Metadata Management<\/title>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\t\n\t\n\t\n