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
Papermap is an innovative data analytics platform that leverages artificial intelligence to assist teams in gathering, processing, examining, and visualizing business data without the challenges associated with conventional business intelligence tools. It allows users to seamlessly connect various data sources—including databases, spreadsheets, and external platforms—and automatically creates data pipelines and dashboards in mere seconds, enabling immediate analysis of information. The platform prioritizes real-time data processing, ensuring users have access to the latest insights as they become available, and accommodates advanced analytics that range from straightforward dashboards to intricate data modeling efforts. With its user-friendly conversational AI interface, individuals can pose questions in everyday language and receive prompt responses, including charts and insights, which removes the necessity for SQL queries or any technical know-how. Papermap's AI command center further enhances its capabilities by generating visual representations, identifying trends, and revealing anomalies, correlations, and opportunities directly from raw data, making it an essential tool for informed decision-making in any organization. Ultimately, Papermap empowers teams to harness their data effectively and efficiently, transforming the way they approach analytics.
API Access
Has API
Yes
API Access
Has API
No
Integrations
PostgreSQL
Yes
Amazon Web Services (AWS)
Yes
Apache Airflow
Yes
Azure Cosmos DB
Yes
Cloudera
Yes
Databricks
Yes
Google Analytics
No
Google Cloud Dataflow
Yes
Google Cloud Platform
Yes
Google Sheets
No
Integrations
PostgreSQL
Yes
Amazon Web Services (AWS)
No
Apache Airflow
No
Azure Cosmos DB
No
Cloudera
No
Databricks
No
Google Analytics
Yes
Google Cloud Dataflow
No
Google Cloud Platform
No
Google Sheets
Yes
Pricing Details
Consumption-based and annual fixed licensing fee are both available.
Free Trial
No
Free Version
No
Pricing Details
$19 per month
Free Trial
Yes
Free Version
Yes
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
No
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)
Yes
In Person
No
Vendor Details
Company Name
FirstEigen
Founded
2015
Country
United States
Website
firsteigen.com/databuck/
Vendor Details
Company Name
Papermap
Founded
2025
Country
United States
Website
www.papermap.ai/
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
Big Data
Collaboration
No
Data Blends
No
Data Cleansing
No
Data Mining
No
Data Visualization
No
Data Warehousing
No
High Volume Processing
No
No-Code Sandbox
No
Predictive Analytics
No
Templates
No