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What is Spectrum Quality?

Gather, normalize, and standardize your information from various sources and formats. It is vital to ensure that all forms of data, whether related to companies or individuals, are normalized, irrespective of being structured or unstructured. This task utilizes sophisticated supervised machine learning techniques grounded in neural networks to grasp the complexities and variations found in different types of information while automating the parsing of data. Spectrum Quality stands out as a reliable partner for international clients who require comprehensive data standardization and transliteration across various languages, including culturally nuanced terms in Arabic, Chinese, Japanese, and Korean. Our advanced text-processing capabilities enable the extraction of insights from any natural language input and efficiently classify unstructured text. By leveraging pre-trained models in conjunction with machine learning algorithms, you can pinpoint entities and tailor your models to clearly define specific entities pertinent to any domain or category, thereby boosting the overall adaptability and applicability of the data processing solutions we provide. Consequently, clients can enjoy a more streamlined and effective approach to data management and analysis, leading to improved decision-making processes. This holistic approach not only enhances data quality but also fosters better insights, driving business success.

What is Aggua?

Aggua functions as an AI-enhanced data fabric platform aimed at equipping both data and business teams with easy access to their information, building trust, and providing actionable insights for more informed decision-making based on data. With just a few clicks, you can uncover essential details about your organization's data framework instead of remaining unaware of its complexities. Obtain insights into data costs, lineage, and documentation effortlessly, allowing your data engineers to maintain their productivity without interruptions. Instead of spending excessive time analyzing how changes in data types affect your pipelines, tables, and overall infrastructure, automated lineage facilitates your data architects and engineers in reducing the time spent on manual log checks, allowing them to concentrate on implementing necessary infrastructure improvements more effectively. This transition not only simplifies operations but also fosters better collaboration among teams, leading to a more agile and responsive approach to tackling data-related issues. Additionally, the platform ensures that all users, regardless of their technical background, can engage with data confidently and contribute to an organization's data strategy.

Media

Media

Integrations Supported

Amazon Redshift
Google Cloud BigQuery
Snowflake

Integrations Supported

Amazon Redshift
Google Cloud BigQuery
Snowflake

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Precisely

Date Founded

1968

Company Location

United States

Company Website

www.precisely.com/product/precisely-spectrum-quality/spectrum-quality

Company Facts

Organization Name

Aggua

Date Founded

2020

Company Location

United States

Company Website

www.aggua.io

Categories and Features

Data Quality

Address Validation
Data Deduplication
Data Discovery
Data Profililng
Master Data Management
Match & Merge
Metadata Management

Categories and Features

Data Fabric

Data Access Management
Data Analytics
Data Collaboration
Data Lineage Tools
Data Networking / Connecting
Metadata Functionality
No Data Redundancy
Persistent Data Management

Data Governance

Access Control
Data Discovery
Data Mapping
Data Profiling
Deletion Management
Email Management
Policy Management
Process Management
Roles Management
Storage Management

Data Lineage

Database Change Impact Analysis
Filter Lineage Links
Implicit Connection Discovery
Lineage Object Filtering
Object Lineage Tracing
Point-in-Time Visibility
User/Client/Target Connection Visibility
Visual & Text Lineage View

Data Management

Customer Data
Data Analysis
Data Capture
Data Integration
Data Migration
Data Quality Control
Data Security
Information Governance
Master Data Management
Match & Merge

Data Quality

Address Validation
Data Deduplication
Data Discovery
Data Profililng
Master Data Management
Match & Merge
Metadata Management

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