Run Data Quality Jobs Natively Within Hadoop With No Coding Required

The success of your data lake depends on its ability to drive new clarity and insight into your business. You must enable data scientists, analysts and managers not to only ask new questions and utilize advanced analytics, but also trust that the results are accurate and grounded in reliable, integrated, fit-for-purpose data.

Earning the trust of your data lake users requires agile, advanced data quality processing – as provided by Trillium Quality for Big Data.

Unlike other data quality tools, Trillium Quality for Big Data utilizes a “design once, run anywhere” strategy to rapidly deploy best-of-breed data quality processes at massive scale – with no coding and no Big Data framework skills required.

Trillium Quality for Big Data lets users visually define and locally test rules-based data quality jobs, which can be run automatically anywhere, including natively within Big Data frameworks such as Hadoop MapReduce or Spark. Using Syncsort Intelligent Execution technology, data quality processing is dynamically optimized at run-time based on the chosen compute framework and available resources. No changes or tuning are required, even if you change frameworks.

By enabling you to focus on the business logic of desired data quality processes while managing performance optimization for you, Trillium Quality for Big Data helps you gain new, actionable business value from your high-volume disparate data sets as rapidly as possible.

A massively scalable, multi-domain data quality solution for your global Big Data environment, Trillium Quality for Big Data is built upon innovation and expertise that has led the data quality market for over 20 years. Architected to run natively in Big Data environments, Trillium Quality for Big Data ensures all your business information is integrated, fit-for-purpose and accessible across the enterprise.

With Trillium Quality for Big Data You Can:

Build a true single view of the customer or any entity
Create a unified, comprehensive view of your customer, products, etc. to better detect fraud, personalize customer experiences, improve business processes and more

Optimize Your Big Data Investments
Expedite successful machine learning initiatives and analytics platforms by starting with reliable, fit-for-purpose data

Maximize Operational Efficiency
Minimize time spent on downstream data remediation efforts and ensure ongoing support for timely, accurate business decisions

Accelerate Time to Value
Repurpose your existing Trillium Software data quality processes and business rules to rapidly achieve the same enterprise data quality standards in your data lake

Easily Create Data Quality Process Flows Without MapReduce or Spark Coding

Trillium Quality for Big Data utilizes an easy-to-use platform lets you build, test and modify data quality processes prior to deployment into an operational environment. Integrate, parse, standardize, cleanse, and match new and legacy customer and business data from multiple disparate sources. Cleanse and match international data with postal and country-code validation and enrichment.

Easily extend existing Trillium data quality workflows and deploy them natively to Big Data environments, ensuring consistent data standards across the enterprise. Prebuilt process flows within the platform can be configured and customized to meet your specific business requirements.

Once a data quality job is ready for operational use, it is easily invoked using standard Hadoop job management and scheduling tools, ensuring consistency with existing operational procedures. Trillium Quality for Big Data configures the workflows as MapReduce or Spark jobs that run across all nodes in your Hadoop cluster, ensuring maximum speed and operational efficiency.

Key data quality features at Big Data scale include:

  • Parse data values to their correct fields
  • Standardize values to enable better matching
  • Verify and enrich global postal addresses using global postal reference sources
  • Match like records and eliminate duplicates for a true single view of the customer, products or any desired entity
  • Enrich data from external, third-party sources to create comprehensive, unified records, enabling 360-degree views of the customer and other key business entities
  • Identify records that belong to the same domain (i.e., household or business)

Learn More

Datasheet: Trillium for Data Quality

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eBook: Keep Your Data Lake Pristine with Data Quality

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Webinar: Applying Data Quality Best Practices at Big Data Scale

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