The online world we interact with today is increasingly powered by data and by insights extracted from that data. Our ever-growing thirst for data insights and data-driven behavior (e.g. ML-based systems) is driving our industry to collect data more often from an increasingly varied set of sources. With increased amounts of data, scale becomes a challenge. To complicate matters further, customers want reliable access to high-quality data and insights. This adds availability and data quality to our list of requirements. More often than not, customers require low-latency as well, often referring to the time it takes raw data to be converted into usable insights or production-grade models. Last but not least, access patterns and use-cases dictate the form data will take when being served!
Depending on how the data will be used, the medium used to store and serve it will vary widely. OLTP/OLAP DBs, caches, object stores, search engines, graph DBs, data streams, vector DBs, and the like represent the many forms data takes to be suitable to its many uses. Come to this track to learn about new technologies, practices, and trends shaping the way you will work with data.
