Discussion - Data Science and Data Analytics

Data Science and Data Analytics Discussion

Discussion Requirements: (Points = 20)

Participants must create a thread in order to view other threads in this forum.

Read Chapter 11 - “Adv. Anal. - Technology and Tools: In-Database Analytics”

Chapter 11 discussed the MADlib which is an open-source library for scalable in-database analytics. It offers data-parallel implementations of mathematical, statistical, and machine learning methods for structured and unstructured data. The concept of Magnetic/Agile/Deep (MAD) analysis skills.

• • Magnetic: Traditional Enterprise Data Warehouse (EDW) approaches “repel” new data sources, discouraging their incorporation until they are carefully cleaned and integrated.
  • Agile: Data Warehousing orthodoxy is based on long-range and careful design and planning.
  • Deep: Modern data analyses involve increasingly sophisticated statistical methods that go well beyond the rollups and drill-downs of traditional business intelligence (BI).

Initial Post:

1. Research and identify three companies where each utilize one of the Traditional Enterprise Data Warehouse (EDW) approaches which apply to the MAD concept of (a) Magnetic (b) Agile, (c) Deep analysis skills.
2. Provide examples of each MAD concepts with examples.
3. Compare and contracts the three companies identified their impact on the MAS concept they implemented.
4. Support your ideas and examples with applicable outside sources according to APA guidelines.

Peer Response:

Select at least two (2) other students' threads and post substantive comments on those threads. Your comments should extend the conversation started with the thread.

Note: All original posts and comments must be substantive. (original post deliverable length is about 250 - 300 words). All sources should be cited according to APA guidelines.