Enterprise Database Systems
New Age Data Infrastructures
New Age Data Infrastructures: Factors Driving Data Infrastructures
it_dlnaddj_01_enus
New Age Data Infrastructures: Factors Driving Data Infrastructures
Lesson Objectives
New Age Data Infrastructures: Factors Driving Data Infrastructures
- discover the key concepts covered in this course
- briefly describe traditional data and data warehousing architecture
- list and describe the limitations of traditional data architecture, including limitations on speed, scalability, compatibility, and consumption
- list and describe the limitations of using ETL systems when working with data, including limitations on performance, scalability, and structure
- compare key differences in ETL (extract, transform, load) and ELT (extract, load, transform) systems and describe how ETL is used with traditional data architectures and ELT with modern ones
- specify the advantages and importance of utilizing multi-model data platforms
- describe the system and principles of work for a multi-model database
- list the most commonly used data sources and formats
- specify why real-time processing is advantageous when dealing with large amount of data
- describe how business intelligence analytics has developed from traditional to modern approaches
- outline the evolution of data analytics, the changing perspectives with respect to it, and what's meant by descriptive, diagnostic, predictive, and prescriptive analytics
- summarize the key concepts covered in this course
Overview/Description
As technology advances, new ways to store, process, and analyze data emerge. For example, large database systems, which require a lot of storage space, have been moved to the cloud and made remotely accessible to many users. These kinds of data infrastructures require business leaders to understand modern data systems and their working principles fully. Use this course to get to grips with the key differences between legacy data systems and modern infrastructures and explore crucial concepts related to modern data infrastructures. By the end of the course, you'll be able to argue why new age data infrastructures are necessary and traditional data systems are limited.
As technology advances, new ways to store, process, and analyze data emerge. For example, large database systems, which require a lot of storage space, have been moved to the cloud and made remotely accessible to many users. These kinds of data infrastructures require business leaders to understand modern data systems and their working principles fully. Use this course to get to grips with the key differences between legacy data systems and modern infrastructures and explore crucial concepts related to modern data infrastructures. By the end of the course, you'll be able to argue why new age data infrastructures are necessary and traditional data systems are limited.
Target
Prerequisites: none
