Cleaning Data with OpenRefine

نویسندگان
چکیده

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Research Statement Data Cleaning Algorithmic Data-cleaning Techniques

With the increasing amount of available data, turning raw data into actionable information is a requirement in every field. However, one bottleneck that impedes the process is data cleaning. Data analysts usually spend over half of their time cleaning data that is dirty — inconsistent, inaccurate, missing, and so on — before they even begin to do any real analysis. It is a time consuming and co...

متن کامل

Effective Data Cleaning with Continuous Evaluation

Enterprises have been acquiring large amounts of data from a variety of sources to build their own “Data Lakes”, with the goal of enriching their data asset and enabling richer and more informed analytics. The pace of the acquisition and the variety of the data sources make it impossible to clean this data as it arrives. This new reality has made data cleaning a continuous process and a part of...

متن کامل

Declarative XML Data Cleaning with XClean

Data cleaning is the process of correcting anomalies in a data source, that may for instance be due to typographical errors, or duplicate representations of an entity. It is a crucial task in customer relationship management, data mining, and data integration. With the growing amount of XML data, approaches to effectively and efficiently clean XML are needed, an issue not addressed by existing ...

متن کامل

Cleaning uncertain data with quality guarantees

Uncertain or imprecise data are pervasive in applications like location-based services, sensor monitoring, and data collection and integration. For these applications, probabilistic databases can be used to store uncertain data, and querying facilities are provided to yield answers with statistical confidence. Given that a limited amount of resources is available to “clean” the database (e.g., ...

متن کامل

Pattern-Driven Data Cleaning

Data is inherently dirty and there has been a sustained effort to come up with different approaches to clean it. A large class of data repair algorithms rely on data-quality rules and integrity constraints to detect and repair the data. A well-studied class of integrity constraints is Functional Dependencies (FDs, for short) that specify dependencies among attributes in a relation. In this pape...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: The Programming Historian

سال: 2013

ISSN: 2397-2068

DOI: 10.46430/phen0023