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What is PanBI?

Discover vital business insights by delving into your structured, semi-structured, and unstructured data via captivating visual platforms. Tailored interactive dashboards provide profound insights into your information. Collections can be organized and accessed according to user preferences and permissions. Users have the ability to comment on datasets and decide whether to share them publicly or maintain their privacy. Furthermore, you can easily generate visually appealing and informative charts and maps to enrich your data presentation. This capability promotes enhanced collaboration among teams and supports informed decision-making grounded in thorough data analysis. Ultimately, leveraging these tools can significantly improve overall business performance and strategic planning.

What is Cloudera Data Warehouse?

Cloudera Data Warehouse is an analytics platform designed for the cloud that enables IT teams to rapidly enable BI analysts with querying capabilities, allowing a swift transition from having no query options to being able to perform queries in just minutes. It supports all data types including structured, semi-structured, unstructured, real-time, and batch data, and is capable of scaling from gigabytes to petabytes based on user requirements. The solution integrates effortlessly with numerous services, such as streaming, data engineering, and AI, while ensuring a unified framework for security, governance, and metadata management across various cloud environments, whether they are private, public, or hybrid. Each virtual warehouse, which can be a data warehouse or mart, is independently configured and optimized to ensure that different workloads do not interfere with each other. Cloudera employs a variety of open-source engines, including Hive, Impala, Kudu, and Druid, supported by tools like Hue, to enable a wide range of analytical functions, from dashboard creation to operational analytics and the investigation of large-scale event or time-series data. This holistic methodology not only improves data accessibility but also significantly enhances the effectiveness of data analysis across multiple industries, ultimately driving better decision-making processes. Additionally, the platform's user-friendly interface allows analysts to focus on deriving insights rather than getting bogged down by complex technicalities.

Media

Media

Integrations Supported

Amazon Web Services (AWS)
Apache Druid
Apache Hive
Apache Impala
Apache Kudu
Hue
Microsoft Azure
SQL

Integrations Supported

Amazon Web Services (AWS)
Apache Druid
Apache Hive
Apache Impala
Apache Kudu
Hue
Microsoft Azure
SQL

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

PanApps

Company Location

India

Company Website

panapps.co/products/business-intelligence-app

Company Facts

Organization Name

Cloudera

Date Founded

2008

Company Location

United States

Company Website

www.cloudera.com/products/data-warehouse.html

Categories and Features

Business Intelligence

Ad Hoc Reports
Benchmarking
Budgeting & Forecasting
Dashboard
Data Analysis
Key Performance Indicators
Natural Language Generation (NLG)
Performance Metrics
Predictive Analytics
Profitability Analysis
Strategic Planning
Trend / Problem Indicators
Visual Analytics

Categories and Features

Data Warehouse

Ad hoc Query
Analytics
Data Integration
Data Migration
Data Quality Control
ETL - Extract / Transfer / Load
In-Memory Processing
Match & Merge

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