Report on Different means of Storing and Exchanging Structured Information

In the computer operations, the role of mass categorization is very crucial, and data comes in two forms in this regard; structured as well as unstructured data. In this project, the focus is on structured data that how it is stored and exchanged. The structured data is structured through different fields like quantity, date, price, subject, title etc. The beauty of structured information is that if someone wants to search it, it can easily be searched. The other major element of structured information is that it can be analyzed for various reasons. After understanding its definition, it is important to know that how structured information is stored as well as exchanged (Warnier, 2005)

Relational Databases and NoSQL Databases

NoSQL Database is one of the most popular databases in recent times due to various benefits they offer as compared to relational databases. It has been observed that when NoSQL Database is compared with relational database, the primary useful properties associated with NoSQL Database are its flexibility in terms of storing and exchanging data. This is not the only benefit of NoSQL Database. NoSQL Database is also less expensive and more scalable as compared to relational database. It has proved to be a disruptive technology, as database market has been disrupted by this technology. The major difference between relational database and NoSQL database is based on four elements such as development model, scaling, data structure as well as data models (MongoDB, 2019)

 It is important to mention here that relational database is one of the oldest ones in handling structured information and data, as it roots go back to 1970, when it was first invented by an IBM programmer named E. F. Codd. They define relational database as a database model, which is based on description of formal tables which can be used to reassemble or access data in so many ways. The best part of relational database is that database tables are needed to be reorganized. One of the standards application and user programming of relational database is called Structured Query Language (SQL). In SQL, the reports data can be gathered as well as it is useful in handling information with interactive queries of a relational database. However, the relational database can also come up with few disadvantages as well. For instance, the redundancy of data is increased by it, and it also takes a lot of time to set up and program (Rouse, 2018)

XML and JSON Formats

 It is important to know that JSON stands for JavaScript Object Notation. It is one of the lightweight formats, which allow interchange of data and it is independent of language. The basis of this structured data is JavaScript programming language. The good thing about this programming language is that it is easy to be generated as well as understood. On the other hand, the role of XML is different as compared to JSON. In XML, data is not shown rather it is carried by the program. It is said to be a markup language, which helps in encoding of documents with a format, that is not only readable by machines, but by humans as well. The major benefits of XML are its usability, generality as well as simplicity, which mean that it is one of the easiest formats to store data.

Example for XML could be seen below

<weatherML>

 <weatherstation>

<wslocation>

  <wsname>Gormanstown</name>

 <wslatitude>53.637107</latitude>

  <wslongitude>-6.234351</longitude>

 </wslocation>

 <wsmeasuredparams>temperature, humidity, windspeed</wsmeasuredparams>

</weatherstation>

 <measurementset timestamp=”29/1/2017 08:55:30”>

<temperature units=”Deg C”>8.5</temperature>

<humidity units=%>85</humidity>

<windspeed units=”ms-1”>2.5</windspeed>

 </measurementset>

 <measurementset timestamp=”29/1/2017 08:56:00”>

<temperature units=”Deg C”>9.0</temperature>

<humidity units=%>85</humidity>

<windspeed units=”ms-1”>2.0</windspeed>

 </measurementset>

</weatherML>

 The limitation of JSON is that namespaces do not get any support from JSON. Moreover, end tags are also not used in this format and as far as security is concerned, it is considered less secured. On the other hand, the limitation of XML is that array is not supported by this format. In addition to that it is hard to interpret and read its documents. But various encoding formats are supported by it (GeeksforGeeks, 2019).

 CSV and EDIFACT

In the field of electronic data interchange, the role of EDIFACT is becoming more crucial with the passage of time. The role of EDIFACT has become critical because of its use in trade keeping the global context in view. EDIFACT contains various aspects such as covering syntax rules & transaction, and managing data element directories (EDI Plus Ltd, 2019).

Example for EDIFACT file are shown below.

On the other hand, CSV is one of the simplest file formats. This file format is used for the storage of tabular data of different types such as databases and spreadsheets. The programs allow exporting and importing files with CSV format (Computer Hope, 2018)

Example for CSV format could be seen below.

 References of Different means of Storing and Exchanging Structured Information

Computer Hope. (2018). How to create a CSV file. Retrieved April 14, 2019, from https://www.computerhope.com/issues/ch001356.htm

EDI Plus Ltd. (2019). What is EDIFACT? Retrieved April 14, 2019, from https://www.edi-plus.com/resources/message-formats/edifact/

GeeksforGeeks. (2019). Difference between JSON and XML. Retrieved April 14, 2019, from https://www.geeksforgeeks.org/difference-between-json-and-xml/

MongoDB. (2019). NoSQL Vs Relational Databases. Retrieved April 14, 2019, from https://www.mongodb.com/scale/nosql-vs-relational-databases

Rouse, M. (2018). relational database. Retrieved April 14, 2019, from https://searchdatamanagement.techtarget.com/definition/relational-database

Warnier, Y. (2005). Structured vs unstructured information. Retrieved April 14, 2019, from https://beeznest.com/blog/2005/09/13/structured-vs-unstructured-information/