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Metadata Management Fundamentals

      Author: Baturi   |   14 September 2022   |   comments: 0

Metadata Management Fundamentals
Last updated 10/2019
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.05 GB | Duration: 2h 48m


Back to Basics
What you'll learn
What is Metadata?
Learn about the importance of Metadata to an Enterprise
The Business Value of Metadata for an Enterprise
Types of Metadata
Real Time Use Case 1: How to fetch Metadata from different Data Layers of an Enterprise Data Warehouse?
Real Time Use Case 2:How to fetch Metadata from different Data Layers of a Hybrid Enterprise Data Warehouse involving Big Data?
How does the different data layers of an application connect via Metadata?
What problems does the Metadata Management Solves?
What business questions does the Metadata Management answer?
What are Data Assets?
What is Data Lineage?
What is Data Stewardship?
What are the different domains from which Metadata can be fetched and liked for trace-ability?
How does Metadata Management relate to Data Management?
Requirements
Data Warehouse Concepts
BigData Concepts
Data Management Concepts
Description
Let's get started with the basics of Metadata Management. Setting up the Metadata Management initiative at the enterprise level serves a variety of purposes. Data Asset discovery, effective cataloging, identifying resources, defining them by criteria, bringing similar resources together and the most important of them all is to have a Self Service approach to the enterprise assets. It also is an effective means of organizing enterprise data assets, which is the need of the hour considering the huge variety and volumes of data and new ways of doing business online. Typically, all the metadata is stored in documents or excel sheets which are not usually up to date just for the namesake and these documents do not really have what one needs. A more efficient way is to use metadata to define, build lineage, relationships and create trace-ability so that the enterprise data citizens can easily find the data, the systems in which the data resides and the owners or stewards of the data. Investing in metadata management/development have a lot of benefits:Simplify data discovery and history of the data with a record of content-rich data across the enterprise. Most of the enterprises have to manage increasingly complex systems in various locations and on varied platforms. By managing metadata effectively, organizations can create an inventory of its data and learn about its transformation across the life cycle, along with the variety of meaning and formats, and locations of each data object.Drive consistency through data reuse, to increase productivity and reduce time needed for project implementation. A managed metadata environment serves as the most effective way to identify the appropriate data elements / objects needed for any use. Metadata Management allows companies to retire unused storage, reducing costs, and reducing time that was spent in deciding among "possibly correct" variations of an attribute.Retain staff knowledge that is lost when business rules, definitions and other forms of metadata are not documented. Often, business metadata remains only in the minds of certain employees. When these individuals leave the company, this knowledge disappears with them. Implementing an enterprise approach to managing metadata preserves this knowledge and reduces the risk of losing valuable contextual knowledge.Increase confidence in the data delivered to business users. Tracking data lineage provides important context to business users. Profiling data in source systems by business data stewards and IT staff can resolve data errors, which will result in accurate, reliable, high-quality data presented in reports, queries and analytics.Improve IT performance in development, impact analysis, data integration, change management, etc. All of these enhancements will enable greater cooperation between business and IT, and ultimately lower total costs of any systems initiative. Metadata helps IT understand what data exists, where it is located, and what it means, minimizing information complexity. The ability to assess the impact of potential changes based on improved knowledge of the data can help managers estimate project duration and resource costs more accurately.
Overview
Section 1: Introduction
Lecture 1 What is Metadata?
Lecture 2 Common Metadata Examples from our day to day work/activities
Lecture 3 Why do we need to manage Metadata?
Lecture 4 What questions does Metadata Management helps us to answer?
Lecture 5 What are the common Questions specific to an attribute in a real time project?
Lecture 6 How does Metadata help with the Business Processes and Procedures?
Lecture 7 How does Metadata help with the Regulations and compliance like GDPR and CCPA?
Section 2: Types of Metadata
Lecture 8 Introduction to different types of Metadata
Lecture 9 Business Metadata
Lecture 10 Technical Metadata
Lecture 11 Difference between Technical Metadata and Business Metadata
Lecture 12 Operational Metadata
Lecture 13 Governance Metadata
Lecture 14 Summary of different types of Metadata
Lecture 15 Descriptive, Structural and Administrative Metadata Types
Section 3: Metadata Origins in an Enterprise
Lecture 16 Where does Metadata exists in the Organization?
Section 4: Real Time Use Case : Using Enterprise Data Warehouse Applications
Lecture 17 The Architecture
Lecture 18 What is happening now at an Enterprise level?
Lecture 19 What are the common questions we get on a daily basis?
Lecture 20 Metadata Repository is the answer
Lecture 21 How do we access the Metadata Repository Tool?
Lecture 22 Self Service Metadata Management
Lecture 23 Data Lineage/ Data Traceability
Lecture 24 Relationships within Metadata
Lecture 25 Enterprise View of Metadata
Section 5: Real Time Use Case : How to fetch Metadata from BigData Tools and Technologies?
Lecture 26 The Hybrid BigData Warehouse Architecture
Lecture 27 Where to start the Metadata Ingestion?
Lecture 28 Metadata from the Source Layer
Lecture 29 Metadata from JSON format
Lecture 30 Metadata from Relational tools and technologies
Lecture 31 Metadata from HDFS Layer
Lecture 32 Metadata from EDW/Data Marts/Hive/Analytics Layer
Lecture 33 Metadata from Analytics/Reporting Layer
Lecture 34 Metadata from Data Science and Transformation Logic
Lecture 35 How does all the Metadata tie up?
All roles which involves and works with data on a daily basis from a Developer to the CDO or a CIO


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