Category

Data Management

MongoDB: a NoSQL Database 3 Ways it Works for Today’s Data Generation

MongoDB is an open-source document database that provides high performance, high availability and automatic scaling. It’s ideal for running modern applications that rely on structured and unstructured data — and to support rapidly changing data. When compared to relational databases, MongoDB databases are more scalable and provide superior performance. Their data models also address several issues that relational database […]

ETL Data Preprocessing and Normalization: 4 Steps to Cleaner, Better Data

In my last blog entry, I highlighted that the analysis of data in its cleanest, most standardized form is a pinnacle in the performance and growth of a business. In this blog entry, I would like to talk about some of the steps you can take to achieve the cleanest form of data. Real-world data, […]

Getting data architecture right: Making the pieces fall into place

I have evaluated, designed and implemented many different data structures during my career. If there’s one thing I’ve learned with all that I have seen, it is that no data structure is perfect. The most successful data structures maintain a fine balance in accommodating the end user’s many different needs. Some of these needs include […]

NoSQL vs. RDBMS 3 differences in power and performance

When we think of a database, we traditionally envision a relational database management system (RDBMS). This is a repository of structured data organized by schemas, tables, columns, and rows. Data is stored persistently, and is resident on the system if the database application is restarted. RDBMS data is organized through tables and indexes and by […]

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