Download PDFOpen PDF in browser

Data Symphony: Harmonizing AI and Big Data for Optimal Performance

EasyChair Preprint no. 11897

7 pagesDate: January 29, 2024


Data Symphony is a groundbreaking initiative that seeks to orchestrate a harmonious integration of artificial intelligence (AI) and big data to achieve optimal performance in diverse domains. In this innovative paradigm, the vast and intricate datasets become the musical notes, and AI algorithms function as the conductors, guiding the symphony toward a crescendo of insights and efficiency. By seamlessly blending the analytical capabilities of big data with the cognitive prowess of AI, Abstract Data Symphony aims to create a synergistic relationship where each element complements and enhances the other. This approach holds the promise of revolutionizing decision-making processes, uncovering hidden patterns, and propelling advancements in fields ranging from healthcare and finance to manufacturing and beyond. The symphony metaphor underscores the importance of precision, collaboration, and coherence in extracting meaningful melodies of information from the vast data landscapes, ultimately leading to unparalleled performance in the ever-evolving realm of technology.

Keyphrases: Big Data, Data Symphony, Optimal performance

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Murat Ayaz and Smith Milson},
  title = {Data Symphony: Harmonizing AI and Big Data for Optimal Performance},
  howpublished = {EasyChair Preprint no. 11897},

  year = {EasyChair, 2024}}
Download PDFOpen PDF in browser