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2 pages/≈550 words
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APA
Subject:
Business & Marketing
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Coursework
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English (U.S.)
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Final Submission of Assignments and Big Data Paper. Kinds of Behavior to Aid in Prediction (Coursework Sample)

Instructions:

Attached are previous assignments..
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 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, with corrections, 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 what data you need for transactional data management, including: entity relationship modeling (ERD) 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 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

source..
Content:


Business and Marketing
Student’s Name
Institution
Kinds of Behavior to Aid in Prediction
Marketing campaigns predict the way a certain trend looks like. Marketing campaign influences the way customers buy. In the case when a given product is marketed through many channels or at many times, customers may change their decision when it comes to buying. The marketing campaign, when done well, can make customers shift their choice on one product and move on the other (Maniatis, 2016). Therefore marketing campaign becomes handy in the prediction of trends.

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