Average Ratings 6 Ratings
Average Ratings 0 Ratings
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.
Description
IBM watsonx.data integration is an enterprise data integration platform built to help organizations deliver trusted, AI-ready data across complex environments. The solution provides a unified control plane that allows data engineers and analysts to integrate structured and unstructured data from multiple sources while managing pipelines from a single interface. Watsonx.data integration supports multiple integration styles including batch processing, real-time streaming, and data replication, enabling businesses to move and transform data based on their operational needs. The platform includes no-code, low-code, and pro-code interfaces that allow users of varying skill levels to design and manage pipelines. Built-in AI assistants enable natural language interactions, helping teams accelerate pipeline development and simplify complex tasks. Continuous pipeline monitoring and observability tools help teams identify and resolve data issues before they impact downstream systems. With support for hybrid and multi-cloud environments, watsonx.data integration allows organizations to process data wherever it resides while minimizing costly data movement. By simplifying pipeline design and supporting modern data architectures, the platform helps enterprises prepare high-quality data for analytics, AI, and machine learning workloads.
API Access
Has API
Yes
API Access
Has API
No
Integrations
Amazon S3
Yes
Amazon Web Services (AWS)
Yes
Apache Airflow
Yes
Databricks
Yes
Google Cloud BigQuery
Yes
Microsoft Azure
Yes
PostgreSQL
Yes
Snowflake
Yes
AWS Glue
Yes
Azkaban
No
Integrations
Amazon S3
Yes
Amazon Web Services (AWS)
Yes
Apache Airflow
Yes
Databricks
Yes
Google Cloud BigQuery
Yes
Microsoft Azure
Yes
PostgreSQL
Yes
Snowflake
Yes
AWS Glue
No
Azkaban
Yes
Pricing Details
Consumption-based and annual fixed licensing fee are both available.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
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
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)
No
Online Support
Yes
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
FirstEigen
Founded
2015
Country
United States
Website
firsteigen.com/databuck/
Vendor Details
Company Name
IBM
Founded
1911
Country
United States
Website
www.ibm.com/products/watsonx-data-integration
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
Product Features
Data Lineage
Database Change Impact Analysis
No
Filter Lineage Links
No
Implicit Connection Discovery
No
Lineage Object Filtering
No
Object Lineage Tracing
No
Point-in-Time Visibility
No
User/Client/Target Connection Visibility
No
Visual & Text Lineage View
No
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
Data Visualization
Analytics
No
Content Management
No
Dashboard Creation
No
Filtered Views
No
OLAP
No
Relational Display
No
Simulation Models
No
Visual Discovery
No
