Data Modeling creates a model for storing and processing data that works in a predictable, consistent manner. It includes the visual presentation of data structures, while enforcing business rules and government policies. A data model focuses on the needed data and its organization, rather than the operations performed on the data. Data Modeling is done […]
Graph Databases in the Spotlight
Graph databases are distinguished by relationships. Users can query, for example, the connections that relate a customer to an account that he or she owns, or how many degrees of separation exist between Kevin Bacon and Audrey Hepburn. Ontologies are a key underpinning, providing a data model to describe things in a database. Metadata and […]
Data Governance and Data Architecture: There is No Silver Bullet
In terms of a market perspective, Data Governance has increased in visibility partly because of the increase in security breaches, data security issues, and compliance requirements for various industry regulations. To secure and manage data properly, it helps to manage it at a higher level and know which of your data is sensitive in the […]
Data Modeling in the Machine Learning Era
Machine learning (ML) is empowering average business users with superior, automated tools to apply their domain knowledge to predictive analytics or customer profiling. The article What is Automated Machine Learning (AutoML)? discusses a prediction that by 2020, augmented analytics capabilities will play a key role and be a “dominant driver” in the growth (and purchase) […]
Data Modeling Trends in 2019
IT technologies are rapidly changing our lives. Whether it’s your daily grocery purchase, monthly bill payments, booking railway tickets, or receiving online healthcare consultation, data technologies have penetrated every business model, large, medium, or small. Recent cloud platforms, coupled with Big Data and IoT technologies, have ushered in a new era of “smart technologies” powered […]
2018 DATAVERSITY Top 20
As we wrap up 2018 and prepare ourselves for 2019, it’s time to take a moment to review and reflect. And while in review, we take the opportunity to look at the content published, produced, and consumed over the last year. In looking at the top 20 published articles and blogs of the year, Machine […]
Data Modeling vs. Data Architecture
In the second edition of the Data Management Book of Knowledge (DMBOK 2): “Data Architecture defines the blueprint for managing data assets by aligning with organizational strategy to establish strategic data requirements and designs to meet these requirements.” Another way to look at it, according to Donna Burbank, Managing Director at Global Data Strategy: “Data […]
Building the Pillars of Data Modeling and Enterprise Architecture
Ron Huizenga believes it’s possible for an organization to reach an enlightened state where users can “understand the journey of their data through the entire organization.” That entails knowing when the data was created, the processes that use it, being aware of how it’s transformed on its way through the organization, and ultimately, knowing when […]
Data Modeling and NoSQL: Innovation and Flexibility
Hackolade offers an array of Data Modeling tools designed for various NoSQL databases. Their software is user-friendly, while providing powerful graphics. These features, combined with flexible HTML model documentation, provide a visual blueprint for each application. Hackolade’s output is similar to a CAD printout produced by a draftsman or architect. The blueprint promotes discussion. Pascal […]
Data Architects and Data Modelers: The SQL/NoSQL Debate is Dead
Karen Lopez says that when it comes to surviving as a Data Architect, “Hybrid is the future.” It’s no longer enough to speak only one language or stay attached to one set of technologies. According to Lopez, “purely relational (SQL) databases don’t exist any longer,” since most applications developed now use various types of database […]