Big Data Is Not Just About “Huge Data”
Big Data encompasses more than just the storage of large datasets; it involves managing the complexities that arise as data sources multiply. As systems scale, inefficiencies can lead to significant production issues, making engineering discipline crucial. The intersection of data engineering and AI highlights the importance of reliable systems that can handle complexity effectively.
- ▪Big Data is not solely about large volumes of data, but also about managing diverse data sources and complexities.
- ▪Small inefficiencies in data processing can escalate into major issues when datasets grow significantly.
- ▪Data engineering plays a critical role in modern AI systems, emphasizing the need for reliable and scalable data pipelines.
Opening excerpt (first ~120 words) tap to expand
try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3943868) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Amit Mishra Posted on May 21 Big Data Is Not Just About “Huge Data” When I first started learning about Big Data, I used to think it was mainly about storing massive amounts of information. But after working around real enterprise systems and large-scale pipelines, I realized the real challenge is not simply the size of the data. It’s everything that comes with it.
…
Excerpt limited to ~120 words for fair-use compliance. The full article is at DEV.to (Top).
Discussion
0 commentsMore from DEV.to (Top)
