Data Architect

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This is the welcome lesson of the course.

This lesson will cover basic data architecture characteristics, data governance and business requirements.

This lesson will cover model, schema and normalization

This lesson will cover conceptual, logical and physical ERD, and how to create ERDs

This lesson will cover how to create and populate a database and run CRUD command

In this lesson, we will take a 30000-foot view of Designing Data Systems. We will meet the instructor and hear about the components of the course, including the final project.

In this lesson, we will look at the importance of, benefits of, and artifacts of Designing Data Systems using Data Architecture. We will also introduce Snowflake, the software we will be using.

In this lesson, we will take a look at the important step of Staging Data. We will look at the theory behind it, study the steps involved, and then actually do it in Snowflake.

In this lesson, we will look at what an ODS is and how it is an important step in building a data warehouse. We will also take a look at how to manage, cleanse, and transform the data.

In this lesson, we will take a look at the final step of building a data warehouse. We will also look at reporting, the primary reason for a data warehouse.

In this lesson, we will take a 30000 foot view of Big Data and see why it is so important. We will meet the instructor and hear about the components of the course, including the final project.

In this lesson you will learn about the main characteristics of Big Data, called the 4Vs. You will also start to explore the Big Data ecosystem.

In this lesson, you'll take a look at several of the layers that make Big Data possible, We will also look at some of the tools that help implement those layers.

In this lesson, we will look at the differences between NoSQL and SQL. We will also see why and how NoSQL databases provide capabilities that allow Big Data to be possible.

In this lesson, we will see what a Data Lake storage implementation of Big Data looks like. In addition to the benefits, we will see what considerations, risks, and challenges organizations face.

This lesson will give you an introduction to data governance and a high level overview of the course. You will be introduced to the importance of data governance, stakeholders and some tools you will be using in the course.

In this lesson, you will learn principles of metadata management such as concepts of metadata, metadata management system and enterprise data models. We will learn how to build an enterprise data model and a metadata management system as well as the different people and processes involved in the effective setup and maintenance of a Metadata Management System.

This lesson covers all aspects and best practices for Data Quality Management. You will learn techniques for profiling data and identifying data quality issues, how to perform data cleansing and how to prevent data errors from occuring in the first place in the source systems. You will also learn how to set up targets, measure data quality and create data quality dashboards and trend reports.

In this lesson we will learn about what is master data, master data management lifecycle and different types of master data management architectures. You will also learn how to define and create a golden record and how to manage reference data. We will also cover the role of data stewards which is key to the set up and maintenance of a master data management solution.

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