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Data Analytics and Management in Data-Intensive Domains: Empowering Data-Driven Enterprises

Tyrone Powell

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Published in Data Analytics And Management In Data Intensive Domains: XIX International Conference DAMDID/RCDL 2024 Moscow Russia October 10 13 2024 Revised Selected Computer And Information Science 822)

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Data Analytics and Management in Data Intensive Domains: XIX International Conference, DAMDID/RCDL 2024, Moscow, Russia, October 10–13, 2024, Revised Selected ... Computer and Information Science Book 822)

by Michael Palmer

4.8 out of 5

Language	:	English
File size	:	14180 KB
Text-to-Speech	:	Enabled
Screen Reader	:	Supported
Enhanced typesetting	:	Enabled
Print length	:	296 pages

In today's digital age, data has become an indispensable asset for organizations across industries. With the proliferation of data-generating devices and IoT (Internet of Things),businesses are drowning in an ocean of unstructured and structured data. Harnessing the full potential of this vast data requires a systematic approach to data analytics and management.

This comprehensive guide delves into the realm of data analytics and management in data-intensive domains, providing a roadmap for organizations to navigate the challenges and unlock the transformative power of data.

Chapter 1: Data Analytics and Data-Intensive Domains

This chapter introduces the fundamental concepts of data analytics and its relevance in data-intensive domains. We explore various data types, data sources, and the challenges associated with managing and analyzing large volumes of data.

Chapter 2: Data Management Best Practices

Effective data management is crucial for ensuring data integrity, accessibility, and security. In this chapter, we cover data governance frameworks, data quality management techniques, and best practices for data storage and retrieval in data-intensive environments.

Chapter 3: Data Analytics Techniques and Algorithms

Data analytics involves a vast array of techniques and algorithms to extract meaningful insights from data. This chapter covers descriptive analytics, predictive analytics, and prescriptive analytics. We explore supervised and unsupervised learning algorithms, machine learning models, and their applications in various domains.

Chapter 4: Data Visualization and Communication

Data visualization plays a critical role in communicating data insights effectively. This chapter explores different types of data visualizations, principles of visual design, and strategies for creating impactful dashboards and reports.

Chapter 5: Cloud Computing for Data Analytics

Cloud computing has revolutionized data analytics by providing scalable, cost-effective, and on-demand access to computing resources. In this chapter, we discuss the benefits of cloud computing for data analytics, cloud data services, and best practices for cloud deployment.

Chapter 6: Case Studies and Real-World Applications

To illustrate the practical applications of data analytics, this chapter presents real-world case studies across different industries. We showcase how organizations have leveraged data analytics to solve business problems, improve decision-making, and gain a competitive edge.

Chapter 7: Ethical Considerations and Future Trends

As data analytics becomes more pervasive, ethical considerations and future trends become increasingly important. This chapter explores the ethical implications of data collection and use, privacy regulations, and the impact of data analytics on society.

Data Analytics and Management in Data-Intensive Domains provides a comprehensive and practical guide for organizations to embrace the power of data. By understanding the principles of data analytics, implementing effective data management practices, and leveraging cutting-edge technologies, enterprises can transform data into a valuable asset and drive data-driven decision-making.

Call to Action

Empower your organization with the knowledge and skills to harness the transformative power of data. Free Download your copy of Data Analytics and Management in Data-Intensive Domains today and unleash the potential of data-driven insights!

by Michael Palmer

4.8 out of 5