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Missing Data

In the real world of business or scientific reporting and analysis, data can prove to be awkward. It can be plain wrong or it can be altogether missing. Sure, we have the NULL to signify unknown, but that doesn't play well with regular business reporting. There are a number of ways of dealing with missing information, and methods of estimating data from existing data has a long and respectable history. Joe Celko gets to grips with a data topic that is often treated with some trepidation.

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Mixing MongoDB and Relational Databases in the Enterprise

Your Agile developers want MongoDB, or a similar document database: your Ops people are concerned about security and backup, and Governance are muttering about transactionality and data transfer between systems. Do you restrict your developers from rapidly-evolving the data design for their domain or do you embrace the joys of NoSQL unconditionally? If you accept a polyglot database environment, where the NoSQL lambs coexist with the relational lions, how do you provide tools and common database concepts that everyone can use and understand?

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SQL Server R Services: Working with Data Frames

Although you can get started with R in SQL Server without understanding data frames, they are a key structure of the R language that are the equivalent of SQL Server table variables. They give you many ways of manipulating and analyzing data and passing it between R and SQL Server. For a database professional, they provide a clear and familiar concept when getting to grips with integrating R into the database.

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SQL Server Vector Support I

What are vectors in SQL Server 2025, as related to the new AI features?

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