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Showing posts with the label Big Data

Columnar Database-MonetDB

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Hey readers, recently I was exploring one of the databases offering  MonetDB which is a columnar database available open source. As per the documentation, the database has very high read performance and works very well with the data rollups. Apart from this it also supports transactions and other features of transactional databases. In this blog, I will be covering a few things that I learned while exploring the Database. Traditional Transactional DB NO SQL Databases Columnar Databases MonetDB Querying MonetDB using Python Transactional Databases: A decade ago the main purpose of databases was to store info and provide the information as and when required. The operations were mainly write heavy and information was stored in normalized form to avoid redundancy and maintain the integrity of information. The most popular OLTP databases that we have in the market and widely used are : Oracle SQL Server My SQL There are many other open...

Text Analysis -Part 1

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Hi Readers, Recently I was going through some text analytics activities at work and learned some techniques for text analytics and mining. In this series of posts, I will be sharing my experiences and learnings. Introduction Firstly the jargon Text Analysis and Text Mining are sub domains of the term Data Mining and are used interchangeably in most scenarios. Broadly  Text Analysis  refers to, Extracting information from textual data keeping the problem for which we want to get data in mind. and  Text Mining  refers to, the process of getting textual data. Nowadays, a large quantity of data is produced by humans.Data is growing faster than ever before and by the year 2020, about  1.7 megabytes of new information will be created every second for every human being on the planet and one of the main components of this data will be textual data. Some of the main sources of textual data are Blogs Articles Websites Facebook Comments Discussion...