Database systems BB
.docx
School
Technological University of Peru**We aren't endorsed by this school
Course
QUIMICA 12
Subject
Information Systems
Date
Jan 13, 2025
Pages
4
Uploaded by BrigadierCrocodilePerson1245
Sai Baba Angonti Week 8 Discussion CollapseWeek 8 DiscussionBig data is defined as the vast amount of structured and unstructured data generated at high speeds from various sources, which traditional database management systems cannot efficiently process. The term encapsulates the challenges and opportunities associated with managing and analyzing these massive datasets to derive actionable insights. The Gardner Group introduces three critical industry trends—Volume, Velocity, and Variety—that further define big data's landscape.Volumerefers to the immense amount of data generated daily. The exponential growth in data creation, particularly through social media, IoT devices, and digital transactions, has led to unprecedented data volumes. As data continues to expand, businesses face challenges in storage, processing, and analysis, yet the potential to gain valuable insights from these large datasets is immense (Chen et al., 2019). The capability to handle and analyze vast volumes of data allows organizations to make more informed decisions, identify trends, and personalize customer experiences.Velocitydescribes the speed at which data is generated and processed. In today's fast-paced digital environment, the ability to analyze real-time data is crucial for businesses to stay competitive. Rapid data processing enables timely decision-making and enhances the responsiveness of businesses to market changes. For example, in e-commerce, analyzing consumer behavior in real-time can lead to dynamic pricing strategies that maximize revenue (Xu et al., 2019).
Varietyrefers to the diverse types of data, including structured, semi-structured, and unstructured data. This variety presents both challenges and opportunities, as businesses must develop advanced analytical tools to process different data formats, such as text, images, and videos. Successfully managing data variety allows businesses to gain comprehensive insights and develop more accurate predictive models, which are essential for strategic planning.In summary, the three V's—Volume, Velocity, and Variety—present both challenges and opportunities for businesses. By effectively managing these aspects of big data, organizations can unlock significant value, enhance decision-making, and maintain a competitive edge in their respective industries.ReferencesChen, C. P., & Zhang, C. Y. (2019). Data-intensive applications, challenges, techniques and technologies: A survey on Big Data. Information Sciences, 275, 314-347.Xu, Z., Qin, Z., & Zhao, J. (2019). Data-driven decision making in e-commerce: Insights from a big data analytics framework. Journal of Business Research, 102, 291-299.Mounika Perugu Mounika Perugu CollapseBig data consists of large, complex data sets from various digital sources, marked by their size, rapid generation, and diverse formats. Traditional storage and processing methods often struggle with big data,
requiring new technologies. It is commonly defined by the Three V’s—Volume, Velocity, and Variety—highlighting the challenges and opportunities in managing these data sets.Volume indicates the massive amount of data generated every moment from sources like social media, IoT devices, and financial transactions. Organizations now gather and store terabytes or even petabytes of data, making it essential to create scalable storage solutions and effective processing systems. Analyzing large amounts of data helps businesses find patterns and insights that were not visible before, fostering innovation and gaining a competitive edge (Laney, 2001).Velocity refers to how quickly data is produced and needs to be processed. In a time when data flows continuously from many sources, the ability to analyze it in real-time is crucial. For instance, banks must quickly identify fraudulent transactions, and marketers need to react to consumer behavior immediately. The fast pace of data processing and analysis drives the need for real-time analytics and processing capabilities.Variety highlights the different types of data that organizations need to handle. Data is no longer just in organized formats like databases; it now includes unstructured data such as emails, videos, social media posts, and sensor information. This mix creates challenges in integrating, storing, and analyzing data, which requires advanced tools and methods to gain valuable insights from various data types (Marr, 2015).The Three V’s significantly impact industries, prompting companies to improve their data management, processing, and analysis. Successfully addressing Volume, Velocity, and Variety enables better decision-making, enhanced customer experiences, and increased operational efficiency.References:Marr, B. (2015). Big data: Using smart big data, analytics and metrics to make better decisions and improve performance. Wiley.
Laney, D. (2001). 3D data management: Controlling data volume, velocity, and variety. Gartner. Retrieved from https://www.gartner.com/doc/1034215