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SnapLogic Builds Automated Data Quality Into Cloud Integration

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SnapLogic Summer 2011 Release - expanded data quality in updated cloud integration platform SnapLogic Summer 2011 Release - expanded data quality in updated cloud integration platform

Enables seamless data cleansing, enrichment and governance to integration pipelines.

SnapLogic, the cloud connection company, announced today that it has expanded the data quality capabilities of its cloud integration platform with its Summer 2011 Release. SnapLogic now enables seamless data cleansing, data enrichment, and controls for data governance as part of its integration technology.

Historically, businesses have had to cleanse or enrich data via manual batch processing, or by pushing and pulling data out of heavy, on-premise tools. According to the Ventana Research Business Analytics Benchmark, when dealing with analytics, two thirds of organizations spend most of their time in data preparation rather than analysis.

With the increasing number of cloud-based applications and data sources, businesses can no longer afford to spend extra resources on data quality each time they add a new data source to their ecosystem. SnapLogic enables companies of all sizes to seamlessly incorporate data quality controls directly into their integration pipelines as the data moves between multiple, disparate on-premise and cloud-based systems.

News Highlights for SnapLogic's Summer 2011 Release
SnapLogic enables seamless data cleansing, data enrichment, and controls for data governance as part of an organization's data integration architecture. All capabilities apply to a wide range of data types and domains and can be configured without coding, including:

  • Matching and de-duplication - apply business rules when extracting data from a database, or identify and link duplicate records across multiple data sources
  • Rules-based configuration environment - create cascading, expression-based data operations for performing advanced data filtering and then output filtered data to any number of destinations
  • Data parsing and concatenation - extract data into individual components or merge individual data components into a single string
  • Data standardization and cleansing - ensure data is standardized and data located in the wrong field is moved to the correct field. Standards such as proper syntax (formatting) and semantics (values) can be applied to improve data matching and ensure compliance with company standards
  • Data enrichment services - correct and enrich global address data with census and geographic information to reflect local postal standards, change of address, demographics, longitude and latitude, and more
  • Data governance controls - automatically separate and remove exceptions for human intervention and send notifications and alerts

Additionally, SnapLogic is furthering its capabilities around big data and its high-performance run-time engine. The new release includes a leading NoSQL database, CouchDB, inside the SnapLogic Integration Platform, as well as the ability to leverage a new JSON Snap to help companies integrate large amounts of unstructured data. It also introduces in-memory optimization of data transformations, allowing increased performance and scalability without requiring upgraded hardware.

Supporting Quotes
"One of the key challenges that our company faces in on-boarding new clients is integrating data from legacy systems. SnapLogic lets us truly automate this process by cleansing and enriching that data before we move it into our Cloud." -- Jai Chawla, Co-Founder & Head of Projects, Paperwork Pro.

"Our benchmark research on data governance shows that inconsistent data and poor data quality have the highest impact on organizations. We see these issues ripple through to business analytic processes where organizations are forced to spend more time on data preparation than analysis as found in our business analytics benchmark. By extending their data integration platform with data quality capabilities, SnapLogic is helping organizations overcome these issues so they can maximize the value of their business data." -- David Menninger, Vice President and Research Director, Ventana Research

"Companies of all sizes realize the business benefit they gain by connecting CRM, business intelligence, social media and a whole host of other enterprise applications and data sources. But those connections go to waste if the data is bad. The huge influx of SaaS applications and cloud-based data sources has amplified data quality challenges for both large and midmarket companies. In order to realize the real business value of integration, data quality needs to happen at the earliest point of entry into the IT ecosystem and be an inherent part of the process to prevent bad data from polluting downstream applications."-- Gaurav Dhillon, Chairman & CEO, SnapLogic

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