An Introduction to Process Documentation
Multinational companies are facing the problem of knowledge management. Industries like software and ITES hire extremely skilled employees to work for them. However, they face several problems. This is because the skill lies in the “employee’s minds” and not in the system. As a result, if the employee goes on long leave or quits the […]
Value Chain and E-Strategy – Components of Commercial Value Chain
Introduction All companies undertake series of activities in order to deliver a product to the customers. These series of activities like procurement of raw material, storage, production, distribution, etc. are referred as value chain activities. The function of value chain activities is to add value to product at every stage before it is delivered to […]
P-Value in Hypothesis Test – Interpreting the Statistical Conclusion
What is the P-Value ? The P-Value is a statistical representation of the likelihood that the null hypothesis is true. Therefore the P-Value is the probability that the output (Y) will not change as a result of the variation that we are deliberately introducing in the input (X). Example: If we have a null hypothesis […]
Factors affecting Inventory Operations
Inventory management operations are increasingly being outsourced to third party service providers, thereby ensuring that the investments and costs in managing the inventories are reduced. This is a welcome trend provided the companies focus on overseeing and reviewing both inventory management as well as inventory operations periodically to ensure proper controls are maintained and processes […]
Value Analysis: An Applied Concept for Manufacturing and Service Industry
Introduction All organizations strive to create value for their customers. This value creates mind space for product and services. Value analysis, therefore, is a scientific method to increase this value. Value is a perception hence every customer will have their own perceptions on how they define value. However, overall at the highest level, value is […]
One of the most important purposes of development of computer systems was the database application which could have been used on them. Data processing drove growth of computer processor speed.
In fact, data processing predates the computers; punched cards were used in the US for collecting data for census during beginning of 20th century. Earliest data processing was done by punched cards on mechanical devices. The real development in data processing speed, storage of data and development of DB applications started much later i.e. from 1950s.
Magnetic tapes were used to store data and being read from it. These database applications had hierarchical structure and used network systems. They were extremely efficient when used with the original query, exactly developed for them, but the DB was not designed to handle new queries or transactions. Also the magnetic tapes must be in same sorted order so as to retrieve the authentic data.
Later in 60s hard disks came about and data retrieval was faster and did not need be stored sequentially. This period was also remarkable in terms of advancement in DB Systems.
Later in 1970 Edgar Codd, father or Relational Database Model, conceptualized a new structure for Database construction and wrote a groundbreaking paper ‘A Relational Model of Data for Large Shared Data Banks’. He freed database from procedural ways of querying and marked the beginning of Data Abstraction i.e. hiding details of how Database is implemented to application programmers and end users.
System R, based on Codd’s concept was developed by IBM and it was first to have a language for querying called SQL or Structured Query Language. Later, System R was further developed to a mainstream commercial DBMS product known as DB2.
Object oriented programming was rapidly developing in the 80s and it also helped break into what we know as Object Oriented Databases. The idea was to treat data as objects and it became easier to conceptualize and program using this idea.
Another great development which happened was processing speed of processors and also conceptualization of indexing which greatly increased data access times, and performances of DB.
90s was a time of a World Wide Web, so unprecedented like world had never seen before. The data was here on the internet.
Databases to which links were forwarded were varied and different and it needed a technique to interchange data efficiently. Also the database had to be of very high availability working 24x7.
XML or eXtended Markup Language is a standard for providing data exchange among different databases and WebPages.
More recently, there has been a growing trend of NoSQL database. These are different from so called classical databases and do not rely on Relational Model for their structure. They do not query data using Structured Query Language but UnQL or Unstructured Query Language which is still in development stage (it is similar to XQuery). These databases are generally used when working with huge quantities of data. Some examples are Mongo DB, CouchBase, HBase used by facebook, Big Table used by Google and Dynamo DB used by Amazon.
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