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What is RDC Platform?

The RDC Platform significantly augments human expertise with sophisticated AI capabilities, providing financial institutions a competitive edge in the lending industry. Prioritizing ethical AI practices for regulatory adherence, our solutions allow lenders to visualize and understand the rationale behind each AI-generated model and decision-making process. By integrating traditional, alternative, and latent data with state-of-the-art AI techniques, we enable accurate predictions and enhance decision-making outcomes. Acknowledging the critical need for safe AI integration, we have introduced a unique method called the Self-describing decision, which promotes confidence and transparency in meeting safety standards. This groundbreaking idea consolidates all elements into a single data object, clarifying every factor involved. It produces a comprehensive log of all model features, predictions, reference data, and the rules activated during the decision-making journey. With built-in governance and explainability, we guarantee that these components are always present, bolstering the trustworthiness of AI-driven decisions. This holistic approach not only aids in maintaining compliance but also fosters trust in AI solutions across the financial landscape, ultimately paving the way for more informed and responsible lending practices. As the financial sector continues to evolve, embracing these advancements will be crucial for long-term success.

What is Apache Kudu?

A Kudu cluster organizes its information into tables that are similar to those in conventional relational databases. These tables can vary from simple binary key-value pairs to complex designs that contain hundreds of unique, strongly-typed attributes. Each table possesses a primary key made up of one or more columns, which may consist of a single column like a unique user ID, or a composite key such as a tuple of (host, metric, timestamp), often found in machine time-series databases. The primary key allows for quick access, modification, or deletion of rows, which ensures efficient data management. Kudu's straightforward data model simplifies the process of migrating legacy systems or developing new applications without the need to encode data into binary formats or interpret complex databases filled with hard-to-read JSON. Moreover, the tables are self-describing, enabling users to utilize widely-used tools like SQL engines or Spark for data analysis tasks. The user-friendly APIs that Kudu offers further increase its accessibility for developers. Consequently, Kudu not only streamlines data management but also preserves a solid structural integrity, making it an attractive choice for various applications. This combination of features positions Kudu as a versatile solution for modern data handling challenges.

Media

Media

Integrations Supported

Apache Flink
Apache NiFi
Apache Spark
BigBI
Cloudera Data Warehouse
E-MapReduce
Hadoop
nCino Cloud Banking Platform

Integrations Supported

Apache Flink
Apache NiFi
Apache Spark
BigBI
Cloudera Data Warehouse
E-MapReduce
Hadoop
nCino Cloud Banking Platform

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

Rich Data Co

Date Founded

2016

Company Location

Australia

Company Website

www.richdataco.com

Company Facts

Organization Name

The Apache Software Foundation

Date Founded

1999

Company Location

United States

Company Website

kudu.apache.org/overview.html

Categories and Features

Categories and Features

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Modeller

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