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Description

Parquet was developed to provide the benefits of efficient, compressed columnar data representation to all projects within the Hadoop ecosystem. Designed with a focus on accommodating complex nested data structures, Parquet employs the record shredding and assembly technique outlined in the Dremel paper, which we consider to be a more effective strategy than merely flattening nested namespaces. This format supports highly efficient compression and encoding methods, and various projects have shown the significant performance improvements that arise from utilizing appropriate compression and encoding strategies for their datasets. Furthermore, Parquet enables the specification of compression schemes at the column level, ensuring its adaptability for future developments in encoding technologies. It is crafted to be accessible for any user, as the Hadoop ecosystem comprises a diverse range of data processing frameworks, and we aim to remain neutral in our support for these different initiatives. Ultimately, our goal is to empower users with a flexible and robust tool that enhances their data management capabilities across various applications.

Description

Sliq is an innovative platform powered by artificial intelligence that swiftly cleans up disorganized raw datasets, making them ready for analysis within minutes by automatically identifying and resolving prevalent quality concerns such as format discrepancies, absent values, schema variations, and formatting mistakes. This efficiency allows analysts and engineers to minimize time spent on tedious maintenance tasks and focus more on deriving insights and building models. By utilizing context-sensitive intelligence, Sliq comprehends the semantic context of the uploaded datasets—whether they pertain to finance, e-commerce, or healthcare—and devises a customized cleaning strategy tailored specifically for each dataset instead of relying on generic solutions. Users have the flexibility to either upload files directly or connect programmatically with existing workflows, and Sliq is compatible with popular data formats like CSV, JSON, and Parquet, ensuring smooth integration into current data environments. Additionally, this platform enhances productivity by streamlining the data preparation process, allowing teams to drive more impactful decision-making through improved data quality.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

APERIO DataWise
Amazon Data Firehose
Apache DataFusion
Astera Dataprep
CSViewer
Google Sheets
Gravity Data
Hadoop
JSON
Mage Sensitive Data Discovery
Meltano
QuerySurge
SDF
SSIS Integration Toolkit
Tictable
Timbr.ai
Tonic Ephemeral
Visplore
Warp 10
pandas

Integrations

APERIO DataWise
Amazon Data Firehose
Apache DataFusion
Astera Dataprep
CSViewer
Google Sheets
Gravity Data
Hadoop
JSON
Mage Sensitive Data Discovery
Meltano
QuerySurge
SDF
SSIS Integration Toolkit
Tictable
Timbr.ai
Tonic Ephemeral
Visplore
Warp 10
pandas

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

$30
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

The Apache Software Foundation

Founded

1999

Country

United States

Website

parquet.apache.org

Vendor Details

Company Name

Sliq

Country

United States

Website

sliqdata.com

Product Features

Product Features

Data Cleansing

Address/ZIP Code Cleaning
Charting
Data Consolidation / ETL
Data Mapping
Multi Data Format Support
Phone/Email Validation
Raw Data Ingestion
Sample Testing
Validation / Matching / Reconciliation

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Alternatives

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