Data Silos, Lakes, & Streams Introduction
Amazon Web Services
| Intermediate
- 12 videos | 1h 19m 1s
- Includes Assessment
- Earns a Badge
This 11-video course discusses the transition of data warehousing to cloud-based solutions using the AWS (Amazon Web Services) cloud platform. You will examine various implications involved in storing different types of data from different sources within an organization. You will need to be familiar with provisioning and working with resources on the cloud, basic big data architecture, distributed systems, using shell commands, and a Linux terminal prompt. You will learn that an organization may have data silos which may prevent access to other teams within an organization. You will learn how to use data lakes, a centralized repository to store data at scale, and as a viable solution to data silos that might exist within an organization. You will learn the difference between a data lake which stores all kinds of raw data in a native format before the data has been processed, and a data warehouse which contains data that can be used so directly to generate business insights. Finally, this course demonstrates storing data with AWS Redshift data warehouse.
WHAT YOU WILL LEARN
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Recall the characteristics and drawbacks of data silos
Specify what a data lake enables
Recognize the advantages of using data lakes to store data
Describe the architecture of a data lake and identify challenges in its design
Recall the characteristics of a data warehouse
Specify the differences between data warehouses and data lakes -
Distinguish between batch and streaming data and recognize the stream-first architecture
Describe how data can be moved from on-premise to the aws cloud platform
Recognize the technologies used to build data lakes on aws
Describe various use cases and architectures of working with data lakes on aws
Recall characteristics of data silos, data lakes, and data streams
IN THIS COURSE
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2m 10s
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9m 40sUpon completion of this video, you will be able to recall the characteristics and drawbacks of data silos. FREE ACCESS
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3. Data Lakes8m 32sAfter completing this video, you will be able to specify what a data lake enables you to do. FREE ACCESS
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4. Characteristics of Data Lakes9m 6sUpon completion of this video, you will be able to recognize the advantages of using data lakes to store data. FREE ACCESS
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5. Data Lake Architecture, Features, and Challenges7m 33sAfter completing this video, you will be able to describe the architecture of a data lake and identify challenges in its design. FREE ACCESS
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6. Data Warehouses8m 4sAfter completing this video, you will be able to recall the characteristics of a data warehouse. FREE ACCESS
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7. Data Warehouses vs. Data Lakes5m 19sAfter completing this video, you will be able to specify the differences between data warehouses and data lakes. FREE ACCESS
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8. Data Streams9m 7sIn this video, you will learn how to distinguish between batch and streaming data and recognize the Stream-First Architecture. FREE ACCESS
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9. Migrating Data to AWS5m 2sUpon completion of this video, you will be able to describe how data can be moved from on-premises to the AWS cloud platform. FREE ACCESS
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10. Data Lakes on AWS6m 10sAfter completing this video, you will be able to recognize the technologies used to build data lakes on AWS. FREE ACCESS
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11. Working with Data Lakes on AWS3m 21sAfter completing this video, you will be able to describe various use cases and architectures for working with data lakes on AWS. FREE ACCESS
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12. Exercise: Data Silos, Lakes, and Streams4m 57sAfter completing this video, you will be able to recall characteristics of data silos, data lakes, and data streams. FREE ACCESS
EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE
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