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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

The data refinery tool, which can be accessed through IBM Watson® Studio and Watson™ Knowledge Catalog, significantly reduces the time spent on data preparation by swiftly converting extensive volumes of raw data into high-quality, usable information suitable for analytics. Users can interactively discover, clean, and transform their data using more than 100 pre-built operations without needing any coding expertise. Gain insights into the quality and distribution of your data with a variety of integrated charts, graphs, and statistical tools. The tool automatically identifies data types and business classifications, ensuring accuracy and relevance. It also allows easy access to and exploration of data from diverse sources, whether on-premises or cloud-based. Data governance policies set by professionals are automatically enforced within the tool, providing an added layer of compliance. Users can schedule data flow executions for consistent results and easily monitor those results while receiving timely notifications. Furthermore, the solution enables seamless scaling through Apache Spark, allowing transformation recipes to be applied to complete datasets without the burden of managing Apache Spark clusters. This feature enhances efficiency and effectiveness in data processing, making it a valuable asset for organizations looking to optimize their data analytics capabilities.

Description

PySpark serves as the Python interface for Apache Spark, enabling the development of Spark applications through Python APIs and offering an interactive shell for data analysis in a distributed setting. In addition to facilitating Python-based development, PySpark encompasses a wide range of Spark functionalities, including Spark SQL, DataFrame support, Streaming capabilities, MLlib for machine learning, and the core features of Spark itself. Spark SQL, a dedicated module within Spark, specializes in structured data processing and introduces a programming abstraction known as DataFrame, functioning also as a distributed SQL query engine. Leveraging the capabilities of Spark, the streaming component allows for the execution of advanced interactive and analytical applications that can process both real-time and historical data, while maintaining the inherent advantages of Spark, such as user-friendliness and robust fault tolerance. Furthermore, PySpark's integration with these features empowers users to handle complex data operations efficiently across various datasets.

API Access

Has API Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Apache Spark Yes 
Amazon SageMaker Data Wrangler No 
Comet LLM No 
Feast No 
Fosfor Decision Cloud No 
IBM Cloud Yes 
IBM Cloud Pak for Watson AIOps Yes 
IBM Watson Yes 
IBM Watson Discovery Yes 
IBM Watson Language Translator Yes 
IBM Watson Recruitment Yes 
IBM watsonx Assistant Yes 
Tecton No 
Union Pandera No 

Integrations

Apache Spark Yes 
Amazon SageMaker Data Wrangler Yes 
Comet LLM Yes 
Feast Yes 
Fosfor Decision Cloud Yes 
IBM Cloud No 
IBM Cloud Pak for Watson AIOps No 
IBM Watson No 
IBM Watson Discovery No 
IBM Watson Language Translator No 
IBM Watson Recruitment No 
IBM watsonx Assistant No 
Tecton Yes 
Union Pandera Yes 

Pricing Details

No price information available.
Free Trial Yes 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours Yes 
Live Rep (24/7) Yes 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

IBM

Founded

1911

Country

United States

Website

www.ibm.com/products/data-refinery

Vendor Details

Company Name

PySpark

Website

spark.apache.org/docs/latest/api/python/

Product Features

Data Preparation

Collaboration Tools No 
Data Access No 
Data Blending No 
Data Cleansing No 
Data Governance No 
Data Mashup No 
Data Modeling No 
Data Transformation No 
Machine Learning No 
Visual User Interface No 

Product Features

Application Development

Access Controls/Permissions No 
Code Assistance No 
Code Refactoring No 
Collaboration Tools No 
Compatibility Testing No 
Data Modeling No 
Debugging No 
Deployment Management No 
Graphical User Interface No 
Mobile Development No 
No-Code No 
Reporting/Analytics No 
Software Development No 
Source Control No 
Testing Management No 
Version Control No 
Web App Development No 

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