Big data is defined by Oracle (n.d.) as large and more complex data sets, mostly coming from new data sources. These data sets are of high volume, which makes them impossible to be processed by traditional applications. However, this data becomes meaningful depending on the needs and use by the organizations processing it since it provides them with more information. That said, AT& T is a service-based multinational company that handles a vast volume of data. Therefore, the traditional tools and technologies are incapable of handling or processing. This project proposal focuses on how AT& T can use big data analytics to collect key information about consumers' video entertainment subscription service for enhanced customer retention. The key parameters of focus while collecting this data will be based on specific shows: whether the customer posed, watched to the end, and how long it takes the subscriber to watch the show. This will help gain insights into patterns and trends that can be used to predict consumer behaviors.
Choice of Technologies and Tools
The technologies and tools chosen will have to address the 3Vs of big data, namely:
Volume: high volumes of data handled
Velocity: the rate at which the data is received. Technologies needed should capture data in real-time or near real-time.
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Variety: data types in big data are; structured, semi-structured, and unstructured.
The big data technologies and tools that will be used are:
Data Storage and Management
A NoSQL database ("not only SQL") will be required. MongoDB will be used for this project. Any non-relational database falls in this category. According to MongoDB, 2019), such databases “provide flexible schemas and scale easily with large amounts of data and high user loads” (p.1). Other features of this database are, it is secure, which guarantees information security.
Data Cleaning
Data collected will be transformed into meaningful datasets. Data inconsistencies, duplications, and irrelevant data will be removed before analysis using tools such as Drake, MS Excel, and OpenRefine.
Data Mining
This is the process by which large batches of raw data are transformed into meaningful information for companies (Twin, 2019). Tools, such as Terra Data software, will be used for data mining.
Data Visualization
The data mined is conveyed to users in graphical representations, which makes it easier to understand. Tools such as tableau are used.
Data Reporting
The acquired data is reported to relevant users for actions to be taken.
Technology Selection Process
The economic viability of any project is partly determined by the technologies selected. Therefore, before technologies to be used for a project can be selected, an organization needs to consider several factors. Among the factors to be considered include whether the technology will suit the company’s business strategy. Likewise, a review of the vendors will be conducted to determine whether the technologies meet the specs, support services, robustness, and reliability of these technologies, as well as security. This review process will involve key technical experts, the finance manager, programmers to create algorithms, testers, and integrators. Moreover, security experts will also be required to test the penetration level with the integrated system.
Effective implementation in the acquisition of these technologies will be crucial to the execution of the proposed project. With big data, the company will identify patterns and trends useful to predict consumer behaviors.
References
MongoDB. (2019). NoSQL Databases Explained . MongoDB. https://www.mongodb.com/nosql-explained
Oracle. (n.d.). What Is Big Data? | Oracle Singapore . Www.oracle.com. https://www.oracle.com/sg/big-data/what-is-big-data/
Twin, A. (2019). Data Mining: How Companies Use Data to Find Useful Patterns and Trends . Investopedia. https://www.investopedia.com/terms/d/datamining.asp
