Microsoft SQL Server Boosting The Analytics Intelligence.
Database has been changing over the years and predictions made was that it will increase from 2025 upto 165 zettabytes an enormous amount of data one would have never imagined. It’s increase was mainly due to increase in complexity types and formats of data available also multiply. The use of Artificial Intelligence and Machine Learning will assist organizations to control these high amount of data. The introduction of Artificial Intelligence has changed the way our various industries operate,, recently the popular mobile operating system Android applied the use of Machine Learning on its recent update codenamed the Android 9 Pie. We’ve also seen applications in the medical field and beyond thereby increasing competition among several players in the industry in a rapid manner.
The Microsoft SQL Server is an Analytics Ready Database
Database management is the strong point of every company or organization, companies are working towards achieving the data driven system. The Microsoft SQL server has been chosen by many due to its versatile and relieble nature. The database helps to improve performance and mission critical analytics operation by offering in-memory online transaction processing (OLTP) and real time operational analytics combining advanced compression level, flexibility and availability benefits.
The Microsoft SQL server has in-Database Advanced Analytics capabilities to enable business, organizations carryout real time operational analytics or predictive analytics with operational data without in any way make a compromise in performance. The in-Memory technology enables the SQL server to perform at this level. The in-Memory technology deliver fast reads and writes.
The Microsoft SQL Machine Learning features has made it possible to build, deploy machine learning solutions using either R* or Python Programming Languages. The functionality eliminated the process of moving data for modeling.
Intel has worked so hard alongside Microsoft to developed two sets of verified software and hardware stacks each optimized for specific software workloads across storage, compute and network.
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