Tag: data management

Data Management
Jim Harris 0
Modernization and data-driven culture – Part 2

Modernization is a term used to describe the necessary evolution of information technologies that organizations rely on to remain competitive in today’s constantly changing business world. New technologies – many designed to better leverage big data – challenge existing data infrastructures and business models. This forces enterprises to modernize their approach to data

Data Management | Programming Tips
Mary Kathryn Queen 0
Using Multiple Quality Knowledge Base Locales in a DataFlux Data Management Studio Data Job

In DataFlux Data Management Studio, the data quality nodes (e.g., Parsing, Standardization, and Match Codes) in a data job use definitions from the SAS Quality Knowledge Base (QKB).  These definitions are based on a locale (Language and Country combination).  Sometimes you would like to work with multi-locale data within the

Hartmut Schroth 0
Data Governance by a Standard Data Model for Insurance

  Using a standardized data model is an essential condition to achieve data governance in an enterprise. A standard data model supports data governance processes by implementing industry standards wherever possible: standards for contract and claims representation, mapping of data content with standard definitions (glossary function), use of code attributes

Data Management | Programming Tips
Mary Kathryn Queen 0
Improving matching results in DataFlux Data Management Studio with cluster comparison

Trusted data is key to driving accurate reporting and analysis, and ultimately, making the right decision. SAS Data Quality and SAS Data Management are two offerings that help create a trusted, blended view of your data. Both contain DataFlux Data Management Studio, a key component in profiling, enriching monitoring, governing

Hartmut Schroth 0
Advantages of a standard insurance data model

In my first blog article I explained that many insurance companies have implemented a standard data model as base for their business analytics data warehouse (DWH) solutions. But why should a standard data model be more appropriate than an individual one designed especially for a certain insurance company?

Customer Intelligence | Data Management
Suneel Grover 0
Web analytics vs. digital intelligence - what's the difference?

The business opportunity to intelligently manage customer journeys across their lifecycle with your brand has never been greater, but so is the danger of not meeting their expectations and losing out to savvier competitors. In my opinion, the current state of most digital analytic practices continue to be siloed, tactical, and narrowly fixated on channel-obsessed dashboard

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