Archive for the Big Data category
bigvis2020
March 20, 2020
Big Data Visualization and Analytics: Future Research Challenges and Emerging Applications – Part 1
Data visualization and analytics are nowadays one of the cornerstones of Data Science, turning the abundance of Big Data being produced through modern systems into actionable knowledge. Indeed, the Big Data era has realized the availability of voluminous datasets that are dynamic, noisy and heterogeneous in nature. Transforming a data-curious user into someone who can […]
Read more
Ihab Ilyas
April 18, 2018
Data cleaning is a machine learning problem that needs data systems help!
When dealing with real-world data, dirty data is the norm rather than the exception. We continuously need to predict correct values, impute missing ones, and find links between various data artefacts such as schemas and records. We need to stop treating data cleaning as a piecemeal exercise (resolving different types of errors in isolation), and […]
Read more
Melanie Herschel and Yannis Velegrakis
March 22, 2018
On Data Exploration in the era of Big Data
We are witnessing data of unprecedented volume, variety and velocity. Such data is collected from almost every aspect of human activity and stored in large repositories in order to be later analyzed and turned into useful insights. The storage model is not any more the one in which data is placed in predefined structures with […]
Read more
Azza Abouzied and Paolo Papotti
February 14, 2018
Courting ML: Witnessing the Marriage of Relational & Web Data Systems to Machine Learning
The web is an ever-evolving source of information, with data and knowledge derived from it powering a great range of modern applications. Accompanying the huge wealth of information, web data also introduces numerous challenges due to its size, diversity, volatility, inaccuracy, and contradictions. This year’s WebDB 2018 theme emphasizes the challenges and opportunities that arise […]
Read more
Surajit Chaudhuri
May 12, 2017
Approximate Query Processing – Where do we go from here?
I think we need to take a hard look at approximate query processing. Don’t get me wrong. The vision of approximate query processing is indeed compelling. In the age of Big Data, the ability to answer analytic queries “approximately”, but at a fraction of the cost of executing the query in the traditional way, is […]
Read more