The introduction of Technology has really transformed the way business is done and also the way data is collected. As many companies or business are now using technology to run their day to day transactions, there is an increasing amount of database that needs to be properly stored. The challenge that most companies face as their database grows is limited storage capacity. Understanding the differences between all of the databases will help you select the database system that will work best for your organization. A database is a crucial part of any organization system, whether it is a large scale manufacturing plant, telecommunications company or other commercial organizations. Their database is at the heart of what they do and must be properly handled and optimized especially as it grows. This is necessary because it will help with improved productivity, help make better and faster decisions, reduced cost and have an edge over their competitors.
Which is the Best Database Applications for your Company?
The most important factors that Organizations need to consider in order to properly manage, control, measure production progress and cost can be gotten from the analysis of the company’s database. This analysis is very important for improvement and at critical times, it will be used for solving complex industrial problems. So with this in mind, it implies that storing the database of your company is very vital. Here is a perfect case–study to describe the value of keeping your company’s database. As information technology was developing, it was recorded that security trading systems usually store ONLY current information. They dispose-off the old information by over –writing the previously stored database with the new. This happened for a long time because of the limited storage space available then.This led to a serious study-problem because they could not get the history and track records of all their previously stored data and achievements. However, most companies today try to save everything that can be saved. The fields saved ranges from contacts, details, calls, to transactions and much more.
And as they do this, they use up a very large chunk of the computer storage. Even when their storage capacity becomes almost fully occupied, they call IT professionals to upgrade their storage systems in order to increase their capacity.This method is preferred to the former whereby new data is written over the old. There are several types of database processing or applications which serve different purposes because they are designed to suit different needs.
Commercial and Industrial (relational) database
There are some commercial applications like Customer’s relationship-systems that make use of relational type of database for organizing their database. For instance, the commercial applications are designed in such a way that they gather data from many fields, these data are subsequently stored. The details of the stored data are most likely going to be customer name, address, company name, email address, phone numbers etc.But if it an industrial applications the required fields are usually simple and they are designed to gather information such as tag name, measurement value and a time stamp which is to be stored.
Production application or data processing is even more concise. The most important fields here is basically quantity, counting, grades, batch, production date etc.
Real-time and Historical Database
Another type is the Real – Time and Historical data processing application. This type of application has a greater ability to process data than the relational database. One major advantage of this application is that it can process and generate historical data massively.
A Case study to compare the advantages of a relational and a historical database
Wellintech incorporated conducted a database comparison-study on the information system of an environmental protection agency. The information system of this agency is a Relational database designed Oracle.This system has been functional for about 3 years, and the relational database of the agency had already occupied 90% of system’s hard disk. Majority of the data stored on the hard disk were from a GIS system. Although, Information on environmental monitoring systems was also stored on the hard disk, the GIS data took most of the space.The GIS system stored maps, locations, GPS information, time stamps, and spatial map information of different work they have done.
But Wellintech Inc. converted the database from relational to process – historian database. The 90% space occupied on the hard disk was reduced to about 25% after the relational database had been compressed and substituted with a process – historian database. This new process – historian database made the system to work faster than before and the efficiency of the system increased as well.It was observed that process – historian database compresses data through a multiple compression algorithm. System Algorithms are precise rule (or set of rules) that specify how to process a data.
Data compression in real – time or process – historian databases is a technology that is very important because of its ability to save space and also help to speed up the rate of query. Query is a form of processing to extract data from a database and present it for use.
Change Compression Algorithm
CHANGE (0) is a type of compression algorithm that is usable for any kind of variable compression. What it does is to detect the compression time – out and also verify the value detection of the same compression process.Next, it stores the value of any variables that has changed. But for those that have not changed, it does not store them. By implication, the first thing that is done for any kind of variable compression is to check the quality and the time of the stamp.
IF Current value < > Previous
THEN Save current value.
ELSE Discard current value
Dead Banding Compression
There is another type of compression algorithm that works by the principle of dead banding. This form is very simple. All it does is to store the data when the changes in variable attain a particular starting point. But there are other forms of variables that change gradually in the real production process; these can drastically reduce the volume of data stored.
IF Abs (Current value – Previous saved value) > Dead compression bias
THEN Save current value. (Through compression)
ELSE Discard current value. (Without compression)
Swinging Door compression
This compression type was first initiated by Open Systems Interconnection (OSI) Soft PI (and patented). However, the algorithm was very simple, so PI opened the whole algorithm up to the public. Since it has been made public, almost all Process – historian database have better modified the technology to their advantage and they use it for algorithm compression.The beautiful thing about swinging door algorithm which makes it unique is the fact that it can judge if a data point needs to be saved or not. All that is needed is just to mark out a distinct straight line between the previous data saved and the next. After which it checks for the absolute bias between both data points.
If there is a bias that exceeds the compression bias, the absolute point will be saved. All the above listed compression technologies actually helps to manage storage space and subsequently improve the data querying by using the various querying algorithms.