{"id":5938,"date":"2015-12-29T07:00:20","date_gmt":"2015-12-29T15:00:20","guid":{"rendered":"http:\/\/formtek.com\/blog\/?p=5938"},"modified":"2015-11-13T09:06:57","modified_gmt":"2015-11-13T17:06:57","slug":"data-algebra-a-more-rigorous-and-mathematical-approach-to-data-analysis","status":"publish","type":"post","link":"https:\/\/formtek.com\/blog\/data-algebra-a-more-rigorous-and-mathematical-approach-to-data-analysis\/","title":{"rendered":"Data Algebra: A More Rigorous and Mathematical Approach to Data Analysis"},"content":{"rendered":"

Data Algebra is a technique that some are saying can abstract\u00a0away much of the grunge and headaches caused by many of the current tools and make managing data, especially Big Data, much easier to do. \u00a0Data algebra is a mathematical approach for analyzing data sets by apply classical set theory<\/a>.<\/p>\n

\u00a0Bill Rogers<\/a>, a senior engineer at IBM, said that<\/a> “you can do far more sophisticated optimization when you’re using algebraic techniques than you can when you’re just using high-level procedural techniques.”<\/p>\n

Charles Silver<\/a>, CEO of Algebraix Data, a company promoting the use of data algebra,\u00a0said that<\/a> “surprisingly, mathematics has played almost no role in software and programming until now \u2013 even though it has enabled huge advances in virtually every other form of science and engineering. Data algebra provides a universal language for data and can be the technology that allows the thousands of different data models in the world to be integrated.”<\/p>\n

Algebraix Data is promoting data algebra and has open-sourced a Python library<\/a> that implements the concepts that are\u00a0explained in a freely downloadable book<\/a>. \u00a0The abstract notation of the approach is certainly elegant and it also frames the process of data analysis in a mathematically rigorous way.<\/p>\n

But SQL is already a\u00a0widely-used programming language\u00a0based on ideas of set theory? \u00a0What’s different?<\/p>\n

The Algebraix Data\u00a0book calls out\u00a0SQL as\u00a0“a mathematical disaster of the first order”, and points out troublesome aspects of the language, like the use\u00a0of a null value, a concept described as a “wholly unmathematical idea”. \u00a0Also, because SQL only can handle data in tabular format other types of databases have needed step in where an RDBMS database fails, like for hierarchical data, text and graphs. \u00a0Programmers have also\u00a0have long had issues with being able to map data created in\u00a0object models of programming languages into tables of a database, a frequently-discussed problem called\u00a0“impedence mismatch”<\/a>.<\/p>\n

The concept certainly has merit, but it’s likely\u00a0to gain traction only after a serious uphill battle against existing databases and analysis tools.<\/p>\n

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Data Algebra is a technique that some are saying can abstract\u00a0away much of the grunge and headaches caused by many of the current tools and make managing data, especially Big Data, much easier to do. \u00a0Data algebra is a mathematical…<\/span><\/p>\n

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