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Average Ratings 0 Ratings

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ease
features
design
support

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Description

Cloudera Data Warehouse is a cloud-native, self-service analytics platform designed to empower IT departments to quickly provide query functionalities to BI analysts, allowing users to transition from no query capabilities to active querying within minutes. It accommodates all forms of data, including structured, semi-structured, unstructured, real-time, and batch data, and it scales efficiently from gigabytes to petabytes based on demand. This solution is seamlessly integrated with various services, including streaming, data engineering, and AI, while maintaining a cohesive framework for security, governance, and metadata across private, public, or hybrid cloud environments. Each virtual warehouse, whether a data warehouse or mart, is autonomously configured and optimized, ensuring that different workloads remain independent and do not disrupt one another. Cloudera utilizes a range of open-source engines, such as Hive, Impala, Kudu, and Druid, along with tools like Hue, to facilitate diverse analytical tasks, which span from creating dashboards and conducting operational analytics to engaging in research and exploration of extensive event or time-series data. This comprehensive approach not only enhances data accessibility but also significantly improves the efficiency of data analysis across various sectors.

Description

Eliminate all manual procedures, potential error sources, and inefficiencies. Avoid the need to constantly re-engineer your data warehouse with every shift in business requirements. Implement automatic quality checks both between and within data sources and respond swiftly when issues arise, which is essential for numerous data users. It’s important to genuinely trust your data now. Create a “gold record” reference point to ensure that business teams always have access to the most up-to-date information available. Establish one unified version of the truth that can be accessed anytime, anywhere. Develop an intermediate model that organizes, stores, and preserves your data independently of how it will be used. Be agile in responding to evolving data sources and business inquiries. Seamlessly connect all your data sources—from data lakes and operational systems to spreadsheets and legacy tools—just like you would with the initial one. Ensure data is stored, preserved, and enhanced in quality to streamline data warehouse automation processes. Data should be organized, enriched, and thoroughly documented so that it is accessible in well-structured datasets (information marts). In doing so, you pave the way for more efficient decision-making across the organization.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Amazon Web Services (AWS)
Apache Druid
Apache Hive
Apache Impala
Apache Kudu
Google Sheets
Hue
Microsoft Azure
Microsoft Excel
Microsoft Power BI
Qlik Data Integration
SQL
Tableau
Toucan

Integrations

Amazon Web Services (AWS)
Apache Druid
Apache Hive
Apache Impala
Apache Kudu
Google Sheets
Hue
Microsoft Azure
Microsoft Excel
Microsoft Power BI
Qlik Data Integration
SQL
Tableau
Toucan

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Cloudera

Founded

2008

Country

United States

Website

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

Vendor Details

Company Name

dFakto

Founded

2000

Country

Belgium

Website

www.dfakto.com/datafaktory-data-warehouse-automation/

Product Features

Data Warehouse

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

Product Features

Data Management

Customer Data
Data Analysis
Data Capture
Data Integration
Data Migration
Data Quality Control
Data Security
Information Governance
Master Data Management
Match & Merge

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