DQ 1 Shared Practice Data Resources And Processes

DQ 1shared Practicedata Resources And Processes That Matter To Your O

Shared Practice—Data Resources and Processes That Matter to Your Organization When you are collaborating with others to make decisions in your professional life, the more you understand the thought processes and paradigms that lie behind your organization's business and IT decisions, the better equipped you will be to propose ways to enhance its information infrastructure to better support its business goals in the future. This week's Discussion will focus on the various types of data resources, processes, and storage systems currently utilized in business IT. You will begin with your own Internet and/or Walden Library search for 1 or 2 current and credible articles on the various types of data resources, processes, and/or storage systems used in information systems in businesses big and small in various industries.

If you are not sure where to start, you may want to ask your peers in this course or your colleagues at your current organization for additional guidance and tips. Because these technologies change and evolve so rapidly, you may also want to explore credible blogs where individuals in IT and business are talking about these same subjects and issues. Some examples include: · HBR Blog Network, Harvard Business Review ( ) · CIO Journal, Wall Street Journal ( ) · CloudTweaks ( ) There are many popular, relevant periodicals to search from as well. Some examples include: · Information Week · Wired · Business 2.0 · Business Week · Fast Company · Wall Street Journal · CIO.com By Day 2 Post your research findings: · Identify and briefly describe 3–4 various types of data resources, data processing, and/or storage systems used in today's business environments that you think are most relevant and important.

Explain your rationale. · Describe 2–3 examples of how each of these tools, processes, or systems is used or could be used within your organization. Identify 2–3 short-term and 2–3 long-term issues that could potentially arise from your examples (e.g., dealing with legacy systems; breach of data; compatibility, privacy, security, or ethical issues, etc.). Then, offer at least one recommendation that might enable your organization to formulate a response to at least one of the issues. Assignment. Assignment: Final Project—Business Memo—Selecting and Using Data Resources and Systems This week you will continue to work on your Final Project, which is due in Week 7.

By Day 7 , you will submit a business memo, written to your Instructor, that explains how you plan to incorporate your learning from the week into your Final Project. This will not be a "perfect" synopsis at this point, but it should capture the main themes and important ideas from the week. Your memo should include the following: · Your preliminary summary of how you are planning to incorporate this week’s learning into your Final Project · Your ideas and recommendations for how your organization can mitigate the short-term and long-term issues that can arise when selecting and using data resources and systems · Brief descriptions of the types of data resources, data processing, and storage systems chosen · An explanation of how the organization might manage the potential implications of those selections, while taking advantage of the opportunities they afford to sustain the business or gain a competitive advantage · Other relevant recommendations or issues that you identified, with a brief analysis of why they are important Note: If you are unable to find relevant information, you may want to look for similar information at /for other similar publically traded companies.

You may find relevant information that will enable you to make appropriate inferences about your organization and make reasonable assumptions so you can proceed with your project. If you have questions about how to apply what you are learning or how to find the most relevant information for your organization’s needs, please discuss your choice with your Instructor using the Contact the Instructor link in the classroom. General Guidance on Assignment Length: Your Week 3 Assignment will typically be 1.5–3 pages (0.75–1 page(s) if single spaced), excluding a title page (not required for this Assignment) and references. As a best practice for this course, as you engage and complete your weekly activities, you will capture notes on your learning for each week and add them to your Final Project Portfolio , which you will use to formulate your Final Project.

Paper For Above instruction

This assignment centers on understanding and analyzing the core data resources, processing techniques, and storage systems that are crucial in contemporary business information systems. In the rapidly evolving landscape of IT, organizations leverage a diverse array of data infrastructure components to support decision-making, operational efficiency, and strategic initiatives. This paper explores key data management tools and processes, their applications within organizations, and potential challenges associated with their deployment.

Firstly, cloud storage services, such as Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform, have become fundamental to modern business IT architectures. They provide scalable, flexible, and cost-effective data storage solutions. Companies utilize cloud storage for backing up critical data, hosting applications, and facilitating remote access to information assets (Marston et al., 2011). The rationale for their adoption lies in their ability to support rapid scalability, disaster recovery, and remote collaboration, which are vital for business continuity. For instance, retail companies depend on cloud systems to manage inventory data and customer information across multiple locations seamlessly.

Secondly, data processing systems like Enterprise Resource Planning (ERP) and Customer Relationship Management (CRM) systems are integral in automating and streamlining business operations. ERP systems, such as SAP and Oracle ERP, integrate core business processes—finance, supply chain, manufacturing—into a unified platform. CRM tools like Salesforce enable organizations to analyze customer interactions, enhance sales efforts, and improve customer satisfaction (Chen et al., 2012). These systems facilitate real-time data collection and analysis, supporting strategic decision-making. For example, manufacturing firms utilize ERP to synchronize production schedules with inventory levels, reducing lead times.

Thirdly, big data technologies including Hadoop and Apache Spark allow organizations to process vast amounts of structured and unstructured data. These systems are crucial for gaining insights from diverse data sources such as social media, IoT sensors, and transactional databases. The ability to analyze big data helps organizations identify trends, optimize operations, and create competitive advantages (Mayer-Schönberger & Cukier, 2013). For instance, marketing firms analyze social media data to gauge brand sentiment and tailor campaigns.

Additionally, data warehouses serve as repositories that consolidate data from multiple sources, enabling complex analysis and reporting. Data integration tools like Talend or Informatica facilitate ETL (Extract, Transform, Load) processes to ensure data consistency and quality (Kimball & Ross, 2013). These tools support strategic analytics, forecasting, and business intelligence, which are essential for informed decision-making. For example, financial organizations use data warehouses to aggregate transaction data for risk analysis.

Each of these tools and systems addresses specific organizational needs and contributes to the overall data ecosystem that supports operational efficiency and competitive advantage. However, their deployment introduces several challenges. Short-term issues include data migration complexities, integration difficulties, and resistance to change among staff. Long-term issues involve data security breaches, compliance with privacy regulations like GDPR, legacy system compatibility, and ethical concerns relating to data usage (Kshetri, 2017).

To mitigate these issues, organizations should adopt comprehensive data governance frameworks ensuring security, privacy, and ethical handling of data. Regular staff training and change management strategies are essential to facilitate smooth transitions during system upgrades or migrations. Investing in scalable and flexible cloud solutions can alleviate legacy system integration issues and optimize disaster recovery mechanisms. Additionally, continuous monitoring of data access and activity can prevent breaches and ensure regulatory compliance (Sambasivan et al., 2017).

In conclusion, understanding and strategically managing data resources, processes, and storage systems are vital for modern organizations seeking to leverage data for strategic advantage. By carefully selecting appropriate technologies and implementing robust governance and security measures, companies can navigate emerging challenges while capitalizing on data-driven opportunities to sustain growth and competitive positioning.

References

• Chen, I. J., Seow, P. S., & Huang, T. M. (2012). ERP implementation success factors: A case study of a Taiwanese manufacturing company. International Journal of Production Economics, 140(2), 562–573.
• Kshetri, N. (2017). 1 Blockchain’s roles in meeting key supply chain management objectives. International Journal of Information Management, 39, 80–89.
• Kimball, R., & Ross, M. (2013). The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling. John Wiley & Sons.
• Mayer-Schönberger, V. & Cukier, K. (2013). Big Data: A Revolution That Will Transform How We Live, Work, and Think. Eamon Dolan/Houghton Mifflin Harcourt.
• Marston, S., Li, Z., Bandyopadhyay, S., Zhang, J., & Ghalsasi, A. (2011). Cloud computing—The business perspective. Decision Support Systems, 51(1), 176-189.
• Sambasivan, R., Koller, M., & Badrinarayanan, V. (2017). Data security governance: A comprehensive framework. Journal of Data Security, 14(4), 245–259.