SQX for SQL Server

• Matrix Computation

  Matrix computation forms the backbone of this project. We leverage the robustness of C# and the versatility of SQL Server to perform intricate matrix operations. This opens up new possibilities for data manipulation and analysis directly within the SQL Server environment.

• Correlation & Covariance Matrices

  In the realm of statistics and data analysis, aggregate functions play a crucial role, particularly when dealing with correlation and covariance matrices. SQX provides high preformance aggregate functions and procedures to compute correlation and covariance matrices.

• Mutual Information Matrix

  The mutual information matrix is a valuable concept in information theory and statistical analysis. It quantifies the degree of dependence or shared information between pairs of random variables in a dataset. Specifically, it measures how much knowing the value of one variable reduces the uncertainty about another variable. In other words, it captures the information gain when considering both variables together. Researchers commonly use it in feature selection, clustering, and dimensionality reduction tasks. By examining the mutual information between variables, we gain insights into their interdependencies and can make informed decisions in various data-driven applications.

• Principal Component Analysis

  Our project also incorporates Principal Component Analysis (PCA), a linear dimensionality reduction technique with applications in exploratory data analysis, visualization and data preprocessing. This technique is widely used in data analysis and simplifies the dataset by keeping only the most significant variables that capture the maximum data variance.

• Confusion Matrix

  A table layout that visualizes the performance of an algorithm, typically a (binary true/false) supervised learning one.

• Five Numbers Summary

  A comprehensive summary of numerical data, providing insights into data distribution, central tendency, and dispersion.

• Data Transformation

  Techniques to convert raw data into a more suitable format for various data analysis tasks.

SQX is a evidence of the power of integrating advanced mathematical computation with database management systems. It paves the way for more sophisticated data analysis and decision-making processes, all within the familiar and powerful environment of SQL Server. We hope you find it as exciting and useful as we do in developing it. Enjoy exploring!

Download SQX

• Requires .NET Framework 4.7.2. (SQX build language C#)

• SQX have Assembly Permission Level SAFE.

  See the SQL Server CLR Integration Code Access Security.

• SQX will be added to the trusted assembly list of SQL Server.

  A note on clr strict security: When clr strict security change from 0 to 1 all clr dac's will be force to reinitialize and this can cause running queries to abort. Care should be taken on production environment.

• Recomendation: Configure MAXDOP

  MAXDOP (max degree of parallelism) allways depends on scenario. Example: For a standard server with N = 4 x CPU use N - 1, if it is a heavy load server use N - 2.

• SqlPackage Instalation. (Not required)

  dotnet add package Microsoft.SqlServer.DACFx

• About COLLATION:

  SQX uses unicode internally; the default collation is from SQX database.

  You can change the collation of SQX database accordingly to your needs.

Reference