Data modeling is the process of designing and validating a database. Logical and physical data models contain terms and symbols to identify and represent all of the data objects needed for a business operation to function.


Information Management NewsEstablishing a data culture and improving data quality is not a one-time project. It is an ongoing discipline. Here's how to get started.
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NewsRising demand for real-time data, distributed sensors, and data mining is fueling growth for energy-related IT services.
NewsIBM's $3 billion bet on the Internet of Things (IoT) includes a heavy focus on weather data -- and its potential implications on the retail, insurance and utility verticals.
AnalyisWhich NoSQL database, if any, is best for your big data projects? Magnitude Software's Thomas Casselberry offers a how-to selection guide.
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BlogWhen it comes to a business decision-making process, there are times when somewhat of a middle ground between data and intuition is called for.
Information Management's DM RadioWhat does Big Data mean for Data Modeling? Good question! The rules have certainly changed when it comes to why data modeling matters, but data flow is just as real an issue as ever. Information systems are ingesting all kinds of new data these days, and in many cases, are then integrating that data with traditional sources. Thus, data modelers should have no fear! Register for this episode of DM Radio to hear Host Eric Kavanagh interview John Choi of IBM, David Dichmann of SAP, Ron Huizenga of Embarcadero and Casey Gwozdz of CA.
Information Management NewsDoes Hadoop mean that data models are no longer required? The answer to this question lies in the purpose of a data model and the needs of this type of environment.
ColumnJust what is the difference between ontologies and data models? If they are both about data, do they not boil down to the same thing?
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The Database as a Service (DaaS) model is growing its presence across the virtual globe. Enterprises are asking whether DaaS is mature enough to meet their low-cost and high-security data management requirements using a cloud paradigm. Companies are deploying virtualized applications and, as a consequence, they are asking for Relational Cloud as well. Dynamic scalability, privacy, performance and heterogeneous environments or interfaces to business intelligence products ask for a class of solutions to satisfy the cloud paradigm as a whole. Data modeling supports DaaS in that it provides a clear mapping of the deployed data structures, storage and data topology as well as the core business concepts. In this way, CA ERwin Data Modeler enables organizations to collect and serve data models from and to any web data source and data management system in the cloud.
Data Discovery and Profiling is a relatively new data management technique that uses tools to identify all data sources throughout the organization and unearth the meaning of the information itself. As with any new paradigm, today’s budget holders and decision makers must first be educated on data discovery and profiling and then shown the value it can bring to the organization through a clear return on investment (ROI) analysis.
Read the usability comparative product review by Craig Boyd as he ranks CA ERwin against PowerDesigner and ER/Studio. All three tests involved modeling for a Microsoft SQL Server 2008 environment.
Data modeling is a time-proven method for understanding data, its interrelationships and its rules. Data management professionals have long understood the value of data modeling. However, business professionals often don’t understand the value of data modeling. So how can you demonstrate to business management the return on investment (ROI) of data modeling? Read this white paper and find out.
In today’s information-driven economy, more and more organizations rely on business intelligence (BI) applications to make strategic business decisions. A BI report is only as good as the database on which it is built, however, and a data model is key to understanding both the business and technical requirements behind the construction of a BI solution. CA ERwin and SAP BusinessObjects BI solutions provide a powerful combination to produce best-of-breed reporting and analytics, along with with robust data modeling and database design capabilities.
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