Data Modeling


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.


FeatureNot all analytics solutions are equivalent or appropriate for specific needs. Making the best solution and vendor choice is paramount to the success of any analytics initiative.
BlogBI is still largely using 17th-century statistical techniques: counts, sums, averages and extrema. At most, we might use techniques that were used by Gauss and Galton in the 19th century.
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BlogHadoop thoroughly disrupts the economics of data, analytics, and data-driven applications. That's cool because the unfortunate truth has been that the potential of most data lies dormant.
FeatureToday, researchers know only a fraction of those variant genes because they lack access to crucial genetic data. Vice President Joseph Biden could help them get the information they need.
BlogMost data-mining algorithms struggle when dealing with rarity—yet rarity is a hallmark of fundamental business and research applications of data science.
FeatureWhile modern tools provide great performance for smaller and simpler datasets, they tend to buckle down under the pressure of dealing with big data, disparate data sources, or many concurrent users.
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BlogThe point of departure for "50 Years of Data Science" is the current squabble in the data industry as to whether data science is really the same as traditional statistics. I've argued many times that the disciplines are quite different, but, alas, others disagree.
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FeatureMany of us have been exposed to aspects of the bitemporal design by using time series data, temporal data, or historical data.
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FeatureOne of the most striking things about attending the annual meeting of the American Economic Association after a long absence is that economics is now really all about the data.
NewsBig data initiatives are delivering generally positive early results for those organizations that have launched projects, according to research from IT industry association CompTIA.
FeatureThe ranks of chief data officers are expected to grow significantly in government this year as a number of federal agencies have put out the ‘Help Wanted’ sign for top data scientists.
BlogThe new version includes features to help end users model their own data without IT assistance while maintaining the centralized governance and security that the platform already has.

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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