Name
Abstract | ||
|---|---|---|
Exploratory analysis on big data requires us to rethink data management across the entire stack -- from the underlying data processing techniques to the user experience. We demonstrate Stat! -- a visualization and analytics environment that allows users to rapidly experiment with exploratory queries over big data. Data scientists can use Stat! to quickly refine to the correct query, while getting immediate feedback after processing a fraction of the data. Stat! can work with multiple processing engines in the backend; in this demo, we use Stat! with the Microsoft StreamInsight streaming engine. StreamInsight is used to generate incremental early results to queries and refine these results as more data is processed. Stat! allows data scientists to explore data, dynamically compose multiple queries to generate streams of partial results, and display partial results in both textual and visual form. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1145/2463676.2463683 | SIGMOD Conference |
Keywords | Field | DocType |
data scientist,multiple processing engine,big data,partial result,microsoft streaminsight,exploratory analysis,analytics environment,underlying data,interactive analytics environment,dynamically compose multiple query,data management,analytics,interactive,visualization | Data mining,User experience design,World Wide Web,Data processing,Computer science,Visualization,Analytics,Big data,Data management,Database | Conference |
Citations | PageRank | References |
16 | 0.79 | 7 |
Authors | ||
8 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mike Barnett | 1 | 613 | 29.03 |
| Badrish Chandramouli | 2 | 522 | 42.85 |
| Robert DeLine | 3 | 2957 | 210.35 |
| steven m drucker | 4 | 2399 | 286.15 |
| Danyel Fisher | 5 | 1913 | 120.44 |
| Jonathan Goldstein | 6 | 1686 | 142.21 |
| Patrick Morrison | 7 | 42 | 1.86 |
| John Platt | 8 | 6611 | 1100.14 |