We look at how to gain structure from unstructured data, via AI/ML analytics to create new records, selecting object data via SQL and storing unstructured files in NoSQL formats.

There are three classifications of data: structured, semi-structured and unstructured. While structured data was the type used most often in organizations historically, AI and machine learning ...

“Tabular data” is a broad term that encompasses structured data that generally fits into a specific row and column. It can be an SQL database, a spreadsheet, a .CSV file, etc.

SQL, the Structured Query Language, remains one of the most widely used programming languages, coming in fourth in Stack Overflow’s research for 2023. Just over half (51.52%) of professional ...

Why SQL Succeeded To some extent, SQL was successful due to timing. As a way to standardize work around data, it provided a list of commands that were easy to understand.

Structured data is designed so it can be passed into another application, such as a business intelligence package, for further analysis. Business systems, such as enterprise resource planning (ERP ...

SQL stands for ‘Structured Query Language’. This is basically a declarative language used for storing and retrieving data in a database. If you’ve heard of SQL, it’s probably in the ...

According to Alluxio, as users and enterprises leverage widely-available analytics engines such as Presto, Apache Spark SQL or Apache Hive, they often run into inefficient data formats and face ...

Getting enterprise data into large language models (LLMs) is a critical task for enabling the success of enterprise AI deployments. That’s where retrieval augmented generation (RAG) fits in ...