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94% SW Score The SW Score ranks the products within a particular category on a variety of parameters, to provide a definite ranking system. Read more

Matillion ETL logo
ETL Tools

4.1 1,278 user ratings

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Overview

Description Matillion ETL is a purpose-built tool designed to transform various cloud data warehouses. The software enables its users to take advantage of the flexibility, economics, and power of the cloud as it integrates with Google BigQuery, Amazon Redshift, and Snowflake. Users can use the software to load valuable data regarding their business into their cloud data warehouse. They can also transform this data in the cloud in order to unveil the hidden insights within the company. One can extract data from frequently used data sources and also load them into a cloud data warehouse with ease as Matillion ETL supports various data source connectors. The software helps the users to perform powerful transformations to prepare their data for consumption by the leading analytics tools such as Looker, Tableau, etc. The intuitive GUI provided by this ETL platform helps users to visually arrange sophisticated data workflows without any SQL coding. Users can avail the advantage of resource capacity by scheduling the data arrangements to run whenever the resources are available. Read more Informatica Cloud Data Quality is an effective data quality management tool that allows clients to deliver trusted insights. The tool is essentially useful for managing, identifying and fixing data quality problems in the cloud as well as on-premise business applications. Data discovery is an important feature of Informatica Cloud Data Quality as it performs iterative data analysis to point out the exact problems and thereafter. The solution’s common data quality rules can be smoothly reused to save time and resources for increased productivity. Further, data quality transformations too are a useful part of an Informatica integration that includes data cleansing along with standardisation and address verification, parsing and enrichment capabilities. Spark processing enhances the rate of performance by ten times thanks to its serverless nature. Further, Informatica Cloud Data Quality keeps every bit of data under continuous monitoring and tracks quality across source systems over time. It further automates a handful of critical tasks and orders, enabling enhanced productivity. However, among all features, it is Informatica’s intensive lineup of business-grade data solutions that sets it apart from the crowd. Read more
Pricing Options
  • Free Trial Available
  • Starts at $1000.0. Offers Free-forever and Custom plan.
  • Free Trial Available
  • Offers Custom plan.
SW Score & Breakdown

94% SW Score The SW Score ranks the products within a particular category on a variety of parameters, to provide a definite ranking system. Read more

  • Features The Feature Score % is calculated using the weighted average method, where core features hold more weight in the final calculation. Read more
    91%
  • Reviews
    84%
  • Momentum
    72%
  • Popularity
    98%

Technical Details

Organization Types Supported
  • Large Enterprises
  • Medium Business
  • Small Business
  • Large Enterprises
  • Medium Business
  • Small Business
Platforms Supported
  • SaaS/Web/Cloud
  • SaaS/Web/Cloud
Modes of Support
  • 24/7 (Live rep)
  • Online
  • 24/7 (Live rep)
  • Online
API Support
  • Available
  • Available

Reviews & Ratings

User Rating
4.1/5 1,278 user ratings
4.3/5 18 user ratings
Rating Distribution
  • Excellent

    27.7%
  • Very Good

    53.8%
  • Average

    16%
  • Poor

    2.3%
  • Terrible

    0.2%
  • Excellent

    38.9%
  • Very Good

    55.6%
  • Average

    5.6%
  • Poor

    0%
  • Terrible

    0%
Pros & Cons
  • Purpose-built tool for transforming cloud data warehouses
  • Supports various data source connectors
  • Intuitive GUI for visual data workflow arrangement
  • Resource capacity optimization through scheduling
  • May require technical expertise for advanced transformations
  • Effective data quality management in cloud and on-premise applications
  • Iterative data analysis for problem identification
  • Reusable data quality rules for efficiency
  • Data quality transformations including cleansing, standardization, and enrichment
  • Continuous data monitoring and quality tracking
  • May require additional resources for complex data quality issues
  Read All User Reviews Read All User Reviews

AI-Generated from the text of User Reviews

Pricing

Pricing Options
  • Free Trial Available
  • Starts at $1000.0. Offers Free-forever and Custom plan.
  • Free Trial Available
  • Offers Custom plan.
Pricing Plans
Monthly Plans Annual Plans

Developer Free

Basic $1,000.00 $1,000.00 per month

Advanced $2,000.00 $2,000.00 per month

Enterprise Custom

Cloud Data Quality Custom

 
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View Detailed Pricing

Screenshots & Videos

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Vendor information

Company Details Located in: Denver, Colorado Located in: Redwood City, California
Contact Details

+1 (720) 930-4647

https://www.matillion.com/

(877) 463-2435

https://www.informatica.com/products/data-quality/cloud-data-quality-radar.html

Social Media Handles

Not available

FAQs

What are the key differences between Matillion ETL and Informatica Cloud Data Quality?

Matillion ETL focuses on data transformation in the cloud, while Informatica Cloud Data Quality emphasizes data quality management and data governance.

What are the alternatives to Matillion ETL?

The top alternatives to Matillion ETL are Talend Cloud Data Integration, ETLrobot, Etlworks Integrator, Talend Data Catalog, and Etleap.

Which SaaS products can Matillion ETL integrate with?

Matillion ETL integrates with Google Analytics, enabling you to track website traffic and user behavior.

What are the key features of Informatica Cloud Data Quality?

Informatica Cloud Data Quality offers data discovery, data quality transformations, and continuous data monitoring to ensure data accuracy and consistency.

How does Informatica Cloud Data Quality ensure data quality?

Informatica Cloud Data Quality uses iterative data analysis to identify data quality issues and provides common data quality rules for efficient problem resolution.

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