Paper Info
Title
Data Preparation: A Survey of Commercial Tools
Abstract
AbstractRaw data are often messy: they follow different encodings, records are not well structured, values do not adhere to patterns, etc. Such data are in general not fit to be ingested by downstream applications, such as data analytics tools, or even by data management systems. The act of obtaining information from raw data relies on some data preparation process. Data preparation is integral to advanced data analysis and data management, not only for data science but for any data-driven applications. Existing data preparation tools are operational and useful, but there is still room for improvement and optimization. With increasing data volume and its messy nature, the demand for prepared data increases day by day.To cater to this demand, companies and researchers are developing techniques and tools for data preparation. To better understand the available data preparation systems, we have conducted a survey to investigate (1) prominent data preparation tools, (2) distinctive tool features, (3) the need for preliminary data processing even for these tools and, (4) features and abilities that are still lacking. We conclude with an argument in support of automatic and intelligent data preparation beyond traditional and simplistic techniques.
Year
DOI
Venue
2020
10.1145/3444831.3444835
SIGMOD
Keywords
DocType
Volume
data quality, data cleaning, data wrangling
Journal
49
Issue
ISSN
Citations 
3
0163-5808
0
PageRank 
References 
Authors
0.34
0
2
Name
Order
Citations
PageRank
Mazhar Hameed101.35
Felix Naumann21900174.92