This 14-page document outlines an assignment for a DBM 502 week 6 big data paper. The paper is a consolidation of individual assignments from previous weeks covering database fundamentals, data architecture, transactional databases, data warehousing, and administration. For this assignment, students are asked to write a 1-2 page paper discussing how predictive analytics and big data techniques could help management by predicting customer, product, or system behaviors from internal and external data sources. Students should propose what data sources and tools like data management, statistical analysis, or visualization software could enable these predictions and why they are suitable to the organization's needs.

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DBM 502 Week 6 Big Data Paper (14 Pages) NEW
This assignment reflects an accumulation of the
individual assignments from Weeks One through
Five, which included creating an ERD, exploring
database fundamentals, Data Architecture for
Transactional Databases, Interacting with a
Transactional Database, Data and Database
Administration for Transactional Databases,
Data Warehouses and Historical Data.
Write an additional 1- to 2-page paper based on
the following information:
Management is happy with the operational work
you have done and with your support of their
strategic investigation of the situation and
trends over time through the data warehouse.
But they have heard that new techniques called
analytics (or even “big data”) can be used to find

2. unexpected gems in all of the data that they have
been collecting, whether or not it is structured.
Are there kinds of behavior (e.g., by customers
or products or their own systems) that might be
valuable to be able to predict What are they
What data (either internal sources described in
the materials or external data sources available
for free or purchase) might help make these
predictions What tools would you use for
management of the data, for statistical analysis,
or for visualization Why is it appropriate to meet
the organization’s needs
Review and consolidate the individual
assignment papers you have written throughout
Weeks One through Six, along with any feedback
you received from your instructor, and ensure
you have included the following:
Explained the role of data in information
systems and business
Distinguished between the three types of data
management in modern organizations
Explained the meaning of key data management
questions and the importance of the answers
Explained the environment, roles, and skills
needed to support transactional data
management, including relational database
environment, database designers, database
developers, and database administrators
Explained and applied techniques for deciding

3. what data you need for transactional data
management, including: entity relationship
modeling and conceptual design
Demonstrated how to use DML to enter
information into relational databases
Explained how to use SQL to extract rows and
columns of data from tables and combine data
from multiple tables, using SELECT
Distinguished between different approaches for
managing data in relational databases, and
explained when each might be used, including
applications with embedded SQL, stored
procedures, and triggers
Explained why database and information
security is important to an organization
Explained how database administrators and
developers can protect the integrity and
confidentiality of data against internal and
external attacks
Explained how database administrators can
protect data integrity against system and
hardware outages
Explained the roles, skills, and tools needed for
managing historical data via data warehouses
Explained how to select, clean, and bring data of
interest into a data warehouse
Demonstrated techniques for designing an
effective data warehouse, through star database
structures, selecting and organizing fact and

4. dimension tables, and specialized indexing (e.g.,
bitmap indexes)
Explained the skills and environments required
for analytic data
Described how those tools are used
Explained the business value of analytic results,
such as data visualization and finding and
applying patterns