Big Data analytics requirements have forced a huge shift in data storage paradigms, from traditional block- and file-based storage networks to more scalable models like object storage, scale-out NAS ...

What Is Big Data Analytics? Big data analytics describes the techniques and technologies that are used to analyze very large, diverse data sets. Enterprises can use big data analytics tools to process ...

Google announced a change to several structured data types. This change affects the requirements for the HowTo, QAPage and the SpecialAnnouncement structured data. The guidance didn’t come with ...

A business’s approach to big data cannot be static. They should continually assess warehoused data and practices for managing data.

Here’s why structured data matters, key schema types to use and advanced techniques to boost visibility in rich results.

AI projects stumble not because of flawed algorithms but because the underlying data pipelines are weak or chaotic.

Allowing quality data in can lead to a better understanding of an organization. Read more to improve your data quality for unstructured data.

The Big Data trend represents the evolving need to process large amounts of data with a new crop of technology solutions that aren't necessarily your father's database. So, what does a company ...

Payers must embrace the value of compartmentalized structured data, leveraging the value of its harmonization to create a clearer, longitudinal record of each member.