Microsoft Vs. Multi File Database

Relational Database Management Systems are probably the ones that we are most familiar with in 21st century computer science. Relational databases store

UNIX systems use to use flat files for storing data. Word processors and spreadsheet software can create flat files. Health Care facilities might use this type of data file for posting employee phone lists.

This must be in your own words and not copied and pasted from the original source. Include the purpose of the database and the subject matter it covers. This may be four or five sentences; and

Databases have been around long before the computer first utilized them, but they became a necessity as the industry has been using them now for over 40 years. Everything is a database now, your inventory, your class schedule, your closet, it is all a possible database. Arora and Gupta state, “Stand alone applications have been replaced with web-based applications, dedicated servers with multiple servers dedicated storage with network storage” (Arora and Gupta 2012). There have been several movements to try and change the database environment, however attempts to replace the relational database with the object-oriented database never came to popularity and relational databases popularity remains high today. However, a new movement called

In a distributed database system, all the databases or the storage devices are not connected to a single common processing unit like CPU. The various data may be stored at different physical locations in multiple computers that are located in the same physical location; or they may be inter-connected over a network. In other words, distributed database system consists of various data locations but they do not share any physical components.

Relational data is when you can put data in a computer one time and it grows

Q1: How is a file processing system or spreadsheet different to a database system? What disadvantages does the database approach address.

Databases are everywhere now and impact our lives in a multitude of ways. It can accurately be said that “your life is in a database” or, more accurately, in multiple databases, and information about you (a retrieval of facts about

One advantage to using relational databases include ease of use due to query languages, and the ease of altering the structure due to data independence. In addition, there are no predefined set of relationships between data records in the relational

Data is information that is stored and organized by fields and records. A field which can also be known as an attribute is a single unit of information, like a surname of an IBM employee. A record or tuple is a collection of related fields. For example, an employee record contains all information fields that are relevant to a specific IBM employee. Additionally, a file (also known as a table) has multiple records that are pertaining to a specific topic. “To signify, an employee file of a hotel contains all employee records (Rob, 2010). Lastly, a database comprises all related files. A hotel database, among others, consists of employee files, room files, customer files, and payment files.”

Metadata present a more complete picture of the data in the database than the data itself.

Databases allow us to easily store and retrieve data in a purely digital format. The strength of this is that large amounts of data can be stored and retrieved with minimal effort on the part of the user. Opposed to manually flipping through files, one can quickly pull up the requested data through a computer program. Many systems that were conventionally paper and file based have been converted to a digital format which are now stored in one or more databases.

Management of very large datasets requires specialist expertise – each different area briefly described in this section is a technical specialisation and whilst there are a limited number of people with expertise in more than one of these areas, there are not deep technical specialists with capabilities in all areas discussed. This means expert management of very large data stores requires a team of specialists and in large organisations teams of specialists in each area. Such expertise is expensive to acquire, retain, develop and manage on an ongoing basis, so there is sense in sharing that expertise across as many datasets and users as possible. Alternatively, compromises are made and lesser levels of expertise are utilised with smaller datasets or compromises made with regards to the robustness and rigour of the data storage. There is an analogy with libraries – very large national libraries have more specialists than a local library with a smaller collection of books.

It is a distributed database where all sites have different databases and no identical software .

Data has always been analyzed within companies and used to help benefit the future of businesses. However, the evolution of how the data stored, combined, analyzed and used to predict the pattern and tendencies of consumers has evolved as technology has seen numerous advancements throughout the past century. In the 1900s databases began as “computer hard disks” and in 1965, after many other discoveries including voice recognition, “the US Government plans the world’s first data center to store 742 million tax returns and 175 million sets of fingerprints on magnetic tape.” The evolution of data and how it evolved into forming large databases continues in 1991 when the internet began to pop up and “digital storage became more cost effective than paper. And with the constant increase of the data supplied digitally, Hadoop was created in 2005 and from that point forward there was “14.7 Exabytes of new information are produced this year" and this number is rapidly increasing with a lot of mobile devices the people in our society have today (Marr). The evolution of the internet and then the expansion of the number of mobile devices society has access to today led data to evolve and companies now need large central Database management systems in order to run an efficient and a successful business.