Learn More

Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Average Ratings 6 Ratings

Description

The BiG EVAL platform offers robust software tools essential for ensuring and enhancing data quality throughout the entire information lifecycle. Built on a comprehensive and versatile code base, BiG EVAL's data quality management and testing tools are designed for peak performance and adaptability. Each feature has been developed through practical insights gained from collaborating with our clients. Maintaining high data quality across the full lifecycle is vital for effective data governance and is key to maximizing business value derived from your data. This is where the BiG EVAL DQM automation solution plays a critical role, assisting you with all aspects of data quality management. Continuous quality assessments validate your organization’s data, furnish quality metrics, and aid in addressing any quality challenges. Additionally, BiG EVAL DTA empowers you to automate testing processes within your data-centric projects, streamlining operations and enhancing efficiency. By integrating these tools, organizations can achieve a more reliable data environment that fosters informed decision-making.

Description

Big Data Quality must always be verified to ensure that data is safe, accurate, and complete. Data is moved through multiple IT platforms or stored in Data Lakes. The Big Data Challenge: Data often loses its trustworthiness because of (i) Undiscovered errors in incoming data (iii). Multiple data sources that get out-of-synchrony over time (iii). Structural changes to data in downstream processes not expected downstream and (iv) multiple IT platforms (Hadoop DW, Cloud). Unexpected errors can occur when data moves between systems, such as from a Data Warehouse to a Hadoop environment, NoSQL database, or the Cloud. Data can change unexpectedly due to poor processes, ad-hoc data policies, poor data storage and control, and lack of control over certain data sources (e.g., external providers). DataBuck is an autonomous, self-learning, Big Data Quality validation tool and Data Matching tool.

API Access

Has API Yes 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Teradata VantageCloud Yes 
AWS Glue No 
Amazon S3 No 
Amazon Web Services (AWS) No 
Apache Airflow No 
Azure Cosmos DB No 
Azure SQL Database No 
Cloudera No 
Databricks No 
Google Cloud BigQuery No 
Google Cloud Dataflow No 
Google Cloud Platform No 
Kylo Yes 
Microsoft Azure No 
PostgreSQL No 
SAP Cloud Platform Yes 
SQL Server No 
Snowflake No 

Integrations

Teradata VantageCloud Yes 
AWS Glue Yes 
Amazon S3 Yes 
Amazon Web Services (AWS) Yes 
Apache Airflow Yes 
Azure Cosmos DB Yes 
Azure SQL Database Yes 
Cloudera Yes 
Databricks Yes 
Google Cloud BigQuery Yes 
Google Cloud Dataflow Yes 
Google Cloud Platform Yes 
Kylo No 
Microsoft Azure Yes 
PostgreSQL Yes 
SAP Cloud Platform No 
SQL Server Yes 
Snowflake Yes 

Pricing Details

No price information available.
Free Trial Yes 
Free Version No 

Pricing Details

Consumption-based and annual fixed licensing fee are both 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 Yes 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux Yes 
Chromebook No 

Customer Support

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

Customer Support

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

Types of Training

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

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) Yes 
In Person Yes 

Vendor Details

Company Name

BiG EVAL

Founded

2010

Country

Switzerland

Website

bigeval.com/platform/

Vendor Details

Company Name

FirstEigen

Founded

2015

Country

United States

Website

firsteigen.com/databuck/

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 

Data Quality

Address Validation No 
Data Deduplication No 
Data Discovery No 
Data Profililng No 
Master Data Management No 
Match & Merge No 
Metadata Management No 

Product Features

Big Data

Collaboration No 
Data Blends No 
Data Cleansing No 
Data Mining No 
Data Visualization No 
Data Warehousing No 
High Volume Processing Yes 
No-Code Sandbox No 
Predictive Analytics No 
Templates No 

Data Governance

Access Control No 
Data Discovery No 
Data Mapping No 
Data Profiling No 
Deletion Management No 
Email Management No 
Policy Management No 
Process Management No 
Roles Management No 
Storage Management No 

Data Management

Customer Data No 
Data Analysis No 
Data Capture No 
Data Integration No 
Data Migration No 
Data Quality Control No 
Data Security No 
Information Governance No 
Master Data Management No 
Match & Merge No 

Data Quality

Address Validation No 
Data Deduplication No 
Data Discovery No 
Data Profililng Yes 
Master Data Management No 
Match & Merge No 
Metadata Management No 

Alternatives

Alternatives

DeepEval Reviews

DeepEval

Confident AI