Data Profiling: What you don’t know can hurt you

All business decisions rest on foundations of customer, product, sales and financial data. Companies spend millions on initiatives intended to manage data assets more effectively, such as CRM, MDM, and ERP. For these projects to be “successful”, the data within these systems must be of high quality. Data profiling, therefore, is not only a critical first step in evaluating the data that populates these applications, but also a requirement to manage, maintain, and monitor their lifetime value.

Understanding the structure, format, and accuracy of data and its relationship to other data elements helps businesses specify, control, and manage enterprise data assets.  Identifying, analyzing, and understanding the state of enterprise data upfront—what is present, absent, corrupted, and misfielded—before you begin any data migration or integration process from legacy systems, can predispose success or failure.  Upfront profiling mitigates data challenges that increase risk, undermine Key Performance Indicators (KPIs), and impede sound decision-making.

See what lurks beneath

Data profiling presents insights into the condition of the data that resides in data sources throughout the enterprise. Automated data profiling applies pre-crafted, out-of-the-box business rules to multiple data elements across disparate databases and applications to expose what would likely be unforeseen correlations. It reveals relationships between data elements (attributes) within a data source or across multiple data sources. It then applies statistical analysis to attributes to identify data issues including:

• Incorrect data

• Missing data

• Data anomalies
• Misfielded data
• Nulls

and points you to the places where those issues, inconsistencies and anomalies exist.

Capture a true profile of your data

By revealing complex relationships among scattered data sources within the enterprise and providing insight into the structure of data, data profiling and discovery imbue companies with the confidence to move forward with ambitious data architecture projects.

A thorough understanding of data structure and its overall condition improves results gleaned from any initiative.

• Data modeling: analyze schema relationships within data and metadata
• Data migration and integration: identify relationships for transformations
• Data quality: establish the validity and accuracy of data
• Data governance: understand data relationships for compliance and regulatory reporting
• Business Intelligence: validate data dependencies, such as valid product ids matching product items, for accurate enterprise reporting

The process of data discovery can be complex and resource intensive. Comprehensive data discovery capabilities from Trillium Software make the process easy. Trillium Software technology accomplishes in-depth data discovery and profiling to uncover the “unknowns” that might otherwise be overlooked and automatically captures a complete and true profile of enterprise data, its metadata, and related data quality assessment. We then deliver the power to cleanse and correct all the problems that emerge.

For a detailed discussion of the benefits of Data Profiling and Discovery, we invite you to download free Market Updates from Bloor Research from the related resources section.

Learn more about TS Discovery - the power of automated profiling