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What is CUBOT?

We created an all-encompassing business intelligence platform designed to enable business users to extract meaningful insights from their data. CUBOT Business Intelligence acts as a consolidated solution that brings together data and provides crucial intelligence to those who need it. The platform allows for the importation of ETL-processed tables, facilitating the development of robust data models. Through CUBOT Designer, analysts can connect transaction tables with relevant master tables, effectively bridging gaps in information across different silos. CUBOT is meticulously crafted to maximize the effective use of organizational data. The process of setting up scheduling actions and configuring performance metrics is user-friendly, ultimately supporting the tracking and promotion of business growth. Analysts have the ability to specify variables for more in-depth analysis. The CUBOT Configurator manages data aggregations, calculates measures, organizes dimension values, and much more. By providing CUBOT with any geographic or time-series information you have, you can unlock further analytical capabilities in the future. Additionally, users are empowered to analyze figures across various data attributes and drill down to the most intricate levels of detail, allowing for a comprehensive exploration of their data ecosystem. This integrated approach not only simplifies data management but also significantly improves decision-making processes throughout the organization, fostering a culture of data-driven strategies. Ultimately, as users become more adept at leveraging this platform, they will find themselves better equipped to navigate the complexities of their analytical needs.

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

Integrations Supported

Apache Flink
Apache NiFi
Apache Spark
BigBI
Cloudera Data Warehouse
E-MapReduce
Hadoop

API Availability

API Availability

Has API

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

Windows
Mac
On-Prem
Linux

Customer Service / Support

24 Hour Support
Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
On-Site Training

Training Options

Documentation Hub

Company Facts

Organization Name

Vizualytics

Date Founded

2001

Company Location

India

Company Website

www.vizualytics.com/Technology/CUBOT.html

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

Business Intelligence

Ad Hoc Reports
Budgeting & Forecasting
Dashboard
Key Performance Indicators
Performance Metrics
Profitability Analysis
Strategic Planning
Trend / Problem Indicators
Visual Analytics

Business Performance Management

Ad Hoc Reports
Ad hoc Analysis
Budgeting & Forecasting
Dashboard
Key Performance Indicators
Quantitative Analysis

Categories and Features

Columnar Databases

Not specified

Distributed Databases

Not specified

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