July 2017
Intermediate to advanced
68 pages
1h 28m
English
Content preview from Implementing a Smart Data Platform
Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.
Chapter 4. Data Management, Data Engineering, and Data Science Overview
Data Management
Data management refers to the process by which data is effectively acquired, stored, processed, and applied, aiming to bring the role of data into full play. In terms of business, data management includes metadata management, data quality management, and data security management.
Metadata Management
Metadata can help us to find and use data, and it constitutes the basis of data management.
Normally, metadata is divided into the following three types:
-
Technical metadata refers to a description of a dataset from a technical perspective, mainly form and structure, including data type (such as text, JSON, and Avro) and data structure (such as field and field type).
-
Operational metadata refers to a description of a dataset from the operation perspective, mainly data lineage and data summaries, including data sources, number of data records, and statistical distribution of numerical values for each field.
-
Business metadata refers to a description of a dataset from the business point of view, mainly the significance of a dataset for business users, including business names, business descriptions, business labels, data-masking strategies.
Metadata management, as a whole, refers to the generation, monitoring, enrichment, deletion, and query of metadata.
Data Quality Management
Data quality is a description of whether the dataset is good or bad. Generally, data quality should be assessed ...
Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
and much more.
Read now
Unlock full access
More than 5,000 organizations count on O’Reilly
O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.