Large Companies Have Been Using The Power Of Business Analyt ✓ Solved

Large Companies Have Been Using The Power Of Business Analytics For Qu

Design a four to six (4-6) page document supporting the need for analytics and cloud technology within a company interested in leveraging these tools. Create a workflow diagram illustrating how analytics and cloud technology align with the company's business processes. Develop three to five (3-5) screen layouts demonstrating the interface that organizational users will utilize. Recommend one (1) solution provider that can give the company a competitive advantage through analytics and cloud technology. Additionally, update the project plan from a previous deliverable in Microsoft Project by adding three to five (3-5) new project tasks, each with five to ten (5-10) sub-tasks.

Sample Paper For Above instruction

Introduction

In the rapidly evolving landscape of modern business, large companies are increasingly harnessing the power of business analytics and cloud technology to gain competitive advantages. These tools enable organizations to delve into historical data, derive actionable insights, and streamline operations through scalable and flexible solutions. The integration of analytics and cloud technology is not merely a trend but a strategic imperative for companies aiming to optimize decision-making, improve performance, and foster innovation.

Justification for Using Business Analytics and Cloud Technology

Business analytics allows companies to analyze vast amounts of data to identify patterns, trends, and correlations that inform strategic decisions. By leveraging historical performance data, organizations can set realistic performance goals, forecast future trends, and personalize customer experiences. Cloud technology complements analytics by providing scalable infrastructure that reduces the need for substantial capital investment in hardware and software. Cloud services facilitate rapid deployment, ease of access, real-time processing, and collaboration, which are essential for modern analytics applications.

Implementing these technologies offers several tangible benefits. Firstly, they enhance decision-making processes, making them data-driven rather than intuition-based. Secondly, they improve operational efficiencies by automating redundant tasks and optimizing resource allocation. Thirdly, they support innovation by enabling experimentation with new business models and products without significant upfront costs. Furthermore, the cloud provides disaster recovery capabilities, ensuring business continuity and data security.

Workflow Diagram Illustration

A workflow diagram depicting the integration of analytics and cloud technology would illustrate a cycle beginning with data collection from various sources, moving into data storage within cloud-based data warehouses, followed by data processing and analysis using cloud analytics tools. Results would then feed into dashboards and reports accessible to decision-makers. The process would also include feedback loops for continuous improvement and real-time monitoring, aligning with overarching business strategies.

Screen Layouts for User Interface

Three sample interface layouts for organizational users could include:

  • Dashboard View: An executive dashboard displaying KPIs, graphical summaries, and alert notifications.
  • Data Query Screen: An interactive interface allowing users to run custom queries, filter data, and view detailed reports.
  • Performance Analysis Page: Visualization tools such as charts and heatmaps for in-depth analysis of specific business metrics.
  • User Management Panel: An administrative interface for managing user privileges, roles, and access to different data sets.
  1. Settings and Customization: Options for configuring personalized dashboards, alert thresholds, and report schedules.

Solution Provider Recommendation

One reputable solutions provider to consider is Microsoft Azure. Microsoft Azure offers comprehensive cloud analytics services, including Azure Synapse Analytics and Power BI, which enable scalable data integration, machine learning, and real-time data visualization. Azure's security features and compliance certifications provide robust data protection, giving firms a competitive edge by ensuring reliable and secure analytics capabilities.

Updated Project Plan

In the updated Microsoft Project plan, the following new tasks and sub-tasks would be added:

Task 1: Data Integration and Preparation

  1. Identify data sources
  2. Design data extraction processes
  3. Implement ETL workflows
  4. Validate data quality
  5. Document data pipelines

Task 2: Cloud Infrastructure Deployment

  1. Select cloud service providers
  2. Configure cloud storage solutions
  3. Set up network security and permissions
  4. Test cloud environment stability
  5. Optimize cloud resource allocation

Task 3: Analytics Tool Integration

  1. Choose analytics platforms
  2. Develop data models
  3. Configure dashboards and reports
  4. Implement user access controls
  5. Train staff on new tools

Task 4: User Interface Development

  1. Design wireframes
  2. Develop front-end interfaces
  3. Conduct usability testing
  4. Refine interface based on feedback
  5. Deploy interfaces to operational environment

Task 5: Training and Change Management

  1. Develop training materials
  2. Schedule training sessions
  3. Manage stakeholder expectations
  4. Establish support resources
  5. Conduct post-implementation reviews

Conclusion

Embracing business analytics and cloud technology is vital for large companies seeking to remain competitive in today's data-driven economy. The strategic implementation of these tools enhances operational efficiency, enables smarter decision-making, and fosters innovation. A comprehensive plan coupled with a well-structured project roadmap will facilitate a smooth transition and sustainable success.

References

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  • Zikopoulos, P., Parasuraman, K., Deutsch, T., Giles, J., & Corrigan, D. (2012). harnessing the power of big data: The next frontier for innovation, competition, and productivity. McGraw-Hill.
  • Verhoef, P. C., et al. (2021). Digital transformation and business analytics: Strategy, developments, and future directions. Journal of Business Research, 124, 607-615.
  • Fosso Wamba, S., Akter, S., Edwards, A., Chopin, G., & Gnanzou, D. (2015). How 'big data' analytics can improve responsiveness and operational efficiency. International Journal of Production Economics, 165, 234-246.
  • Chaudhuri, S., Dayal, U., & Narasayya, V. (2011). An overview of business intelligence technology. Communications of the ACM, 54(8), 88-98.
  • Sharma, S. K., & Mithas, S. (2019). Developing and deploying business analytics: Practical insights from industry experts. Journal of Business Analytics, 3(2), 129-148.
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  • McAfee, A., Brynjolfsson, E. (2012). Big data: The management revolution. Harvard Business Review, 90(10), 60-68.

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