Business Requirement And Project Plan: Business Requirements

BUSINSS REQUIREMENT AND PROJECT PLAN 4 Business Requirements Necosa Hollie

Describe the project and scope of the project: The company named SOMAR AND CO. DATA COLLECTION COMPANY is a data collection and analysis company that has been operating for less than two years. It aims to create a comprehensive data repository and expects to increase its database by 20% annually. The company seeks to adopt best practices in data gathering for its warehouse. The scope of the project includes full planning of data collection and analysis processes, including features, functions, project goals, tasks, and deadlines. Proper scope control is essential to ensure the business functions correctly, involving understanding project objectives, team training, and effective communication among involved personnel.

The features of the assumed data collection and analysis system include hiring dedicated experts, utilizing advanced tools and techniques, training staff for timely evaluation and insights, and filtering raw data for meaningful analysis. The project goals encompass creating a data repository, analyzing collected data, implementing effective warehousing practices to ensure an annual 20% data growth, and eliminating redundant or irrelevant data.

Deadlines are set according to task complexity; for instance, establishing data warehouse practices should be completed within a year to prevent data pile-up and maintain operational efficiency. Data analysis tools such as R, Python, SAS, Apache Spark, Hadoop, and Excel will be utilized. Risks include security threats, constraints involve system tools and warehousing techniques, and assumptions include the use of sampling methods like random sampling, normal distribution, and independence tests to validate system accuracy.

The relationship between the system and infrastructure emphasizes both physical and virtual components, such as hardware (cooling systems, data centers) and internet infrastructure (fiber optics, satellites, antennas). Security measures like physical access controls, cameras, and restricted data access are critical, as well as cloud infrastructure services providing scalable and flexible computation and storage options.

The data warehouse characteristics include managing both physical and logical data, establishing relationships with existing systems, segmenting data by departments, supporting online analytical processing, and embedding tools like Apache Spark and Hadoop to manage big data via the 3V model (Volume, Velocity, Variety). Outsourcing security functions to a CSIRT (Computer Security Incident Response Team) and business processes like data collection, analysis, warehousing, and infrastructural management are recommended for strategic focus and efficiency.

Resources needed include publicly available data collection tools such as interviews, observations, questionnaires, records, and focus groups. Key terms include data collection, data analysis, outsourcing/offshoring, and warehouse management. The organization should leverage analytics to improve decision-making, utilizing cloud-based analytics services to minimize infrastructure investments.

Strategic issues involve reputation management, market positioning, customer account management, identifying opportunities, and monitoring performance. The project’s timeline involves specific tasks like outsourcing, hardware procurement, and staff training with clearly defined start and end dates, ensuring timely project completion.

Paper For Above instruction

In today’s rapidly evolving business landscape, data has become a crucial asset for organizations seeking competitive advantage and operational efficiency. For a data collection company like Somar and Co., establishing a robust data management system is vital to support business growth, informed decision-making, and strategic planning. The project’s scope involves creating an integrated data repository, adopting best practices in data warehousing, and implementing advanced analytics techniques. These initiatives aim to facilitate scalable data growth, efficient storage, and insightful analysis, aligning with the company’s goal of increasing data volume by 20% annually.

The scope of this project encompasses detailed planning of data collection, storage, analysis, and security protocols. Ensuring that the business functions as intended requires an understanding of project objectives, training personnel, and establishing clear communication channels among stakeholders. The project emphasizes developing a reliable system where raw data is collected systematically, processed accurately, and analyzed effectively to produce actionable insights. Employing skilled data analysts and leveraging cutting-edge tools such as Apache Spark, Hadoop, R, and Python ensures that the platform can handle massive datasets with high velocity and variety, complying with the 3V principles of big data management.

Controlling the project scope involves setting precise objectives, defining deliverables, and monitoring progress to prevent scope creep. Regular training sessions for staff are essential in equipping them with the necessary skills to evaluate and interpret large datasets accurately. Effective communication is equally critical to ensure that all team members and external partners are aligned on project goals, timelines, and responsibilities. A strategic approach encompasses the careful selection of hardware, software, and security measures—such as implementing physical and electronic access controls, surveillance, and encryption—to protect sensitive information from external threats.

The infrastructure supporting the data warehouse must meet both physical and virtual requirements. Physical components include cooling systems, server hardware, and data centers, while virtual elements involve cloud services offering Infrastructure as a Service (IaaS). Cloud adoption provides flexibility, scalability, and cost-efficiency, enabling the company to store and analyze large datasets without significant capital expenditure. Integration of tools like Apache Spark and Hadoop adheres to the 3V model, ensuring storage capacity, high velocity processing, and handling of heterogeneous data formats such as images, videos, and structured records.

Security considerations are paramount; sourcing a CSIRT team ensures ongoing monitoring and rapid response to potential incidents. Outsourcing certain functions, like security management and IT support, enables the company to focus on core activities and leverage specialized expertise. The project timeline includes phases such as outsourcing, hardware procurement, installation, and staff training, outlined with specific deadlines to ensure timely delivery.

Strategic issues surrounding this initiative include managing the company's reputation, market position, and compliance with data privacy regulations. The project aligns with broader organizational goals of enhancing decision-making capabilities, expanding market reach, and maintaining data integrity. By integrating advanced analytics and robust infrastructure, Somar and Co. aims to become a leader in data-driven insights within the industry.

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