Seven Data Discovery Steps for Improving Information Delivery and Accuracy
Know your data: With today’s information-driven business projects, no maxim could be truer. Yet many organizations lack fundamental knowledge about their data – and the situation is getting tougher as “big data” sources grow in size and variety and manual documentation efforts can’t keep pace. Good data knowledge is critical to defining business objects such as customers and products within and across data sources. Clear understanding of data assets, data relationships, and how sources map to target schema can be a vital business accelerator. Poor understanding leads to higher costs, embarrassing mistakes, regulatory errors, and data quality problems that damage daily decision making.
Join this TDWI Webinar to find out how data discovery tools and procedures can help you improve information delivery and accuracy. You will hear how leading organizations are applying data discovery to reduce the time and costs involved in learning how different data items are defined and related within and across multiple data sources. This session will discuss how data discovery procedures can strengthen the data foundation for business object definitions that depend on information from multiple applications, databases, and platforms. It will address how data discovery can make it easier to consolidate sources, track data lineage, protect sensitive data, and apply data governance policies effectively.
In this Webinar, you will learn:
- Seven steps for applying data discovery to information-driven business projects
- How data discovery can enable you to identify and document critical data elements and transformations within and across sources for business objects such as customers and products
- How to use data discovery to overcome limitations in standard data profiling
- Best practices for applying data discovery and business object mapping to reduce cost and complexity in data consolidation and asset rationalization
- Discovery’s role in data governance, ETL, master data management, and the protection of sensitive data