Big data and business analytics Every time in the past, whenever data issues posed a problem, experts in Business Intelligence came up with an idea to rescue. The varied BI tools underwent a series of transformation to introduce newer technologies which could handle the data in a better and subtle way. However, the magnanimity of this data grew over and over, and it continues to do so.
At the moment, Big Data is an immediate problem to deal with. The analytics show that generation of data through our sources which are off the paper has grown so rapidly where it is already difficult to manage that. Through the past years of 2012 and 2013, over 2.4 quintillions (2.4*(10^8)) bytes of data has been generated every day. This is supposed to grow bigger, wider. Are we well prepared for this?
Concept Of Big Data:
The term came to existence in 2008 for the first time. Then, the volume of the data suddenly seemed too huge for the conventional systems to handle. It was an imminent threat for the IT experts to delve into the matter, owing to the value of incoming data. Moreover, it was not feasible to get rid of the old information which was present in the systems. Almost every BI tool made use of the historic data to decipher the future plans. This data, however, could be singled out as having three individual characteristics:
How Will Business Intelligence Tools Play A Role?
Many Organizations have already initiated with the high level framework, which can deal with the volume and variation of data. This framework divides the information to various forms, which are different from each other. The next need for the Organizations is to have a system in place that can process the various forms of information and integrate it as one, in the end.
Understanding this in a technological aspect, the Organizations now need to understand which BI tools can be used individually to process which part of the information. This understanding will lead to a faster implementation in dealing with Big Data. The parts of input that still cannot be processed with the available tools may be handled by applying a few transformation logics. Thus, the only logical way to deal with Big Data at the moment seems to distribute it over the various systems, with minimal loss of valuable input rendered.
Read next blog on challenges in online transaction processing OLTP.
At the moment, Big Data is an immediate problem to deal with. The analytics show that generation of data through our sources which are off the paper has grown so rapidly where it is already difficult to manage that. Through the past years of 2012 and 2013, over 2.4 quintillions (2.4*(10^8)) bytes of data has been generated every day. This is supposed to grow bigger, wider. Are we well prepared for this?
Concept Of Big Data:
The term came to existence in 2008 for the first time. Then, the volume of the data suddenly seemed too huge for the conventional systems to handle. It was an imminent threat for the IT experts to delve into the matter, owing to the value of incoming data. Moreover, it was not feasible to get rid of the old information which was present in the systems. Almost every BI tool made use of the historic data to decipher the future plans. This data, however, could be singled out as having three individual characteristics:
- Volume: The volume of Big Data was huge. Unlike past, there are modern systems today which can manage terabytes of data generation with ease. These are the complex systems though, which have been running successfully in the big Organizations and are supposed to tackle the heaviness of data generation with no apparent performance issue. The analysis is around developing these systems further, since the Big Data is going to grow in volume over the coming years as well.
- Variety: The sources for Big Data are many. And this contributes to the heterogeneous data. Conventionally, the BI tools excel in handling either the structured or the unstructured data. There have been ways in which the combination of structured and unstructured data could be fed into multiple systems and could be processed to have usable output in the end. However, the many sources added on in the past have been unimaginably varied. The inputs from Social Media as considered a useful input from the subject exerts, pose a problem in terms of the data which will be completely unanticipated. Likewise, the sensors on vehicles and animals supposed to gain a deeper understanding of the unknown world, leads to a form of data which may be anything.
- Velocity: The traditional systems tend to process the input data, before it can be considered useful. However, the Big Data has a volume which is enormous. Storing in the systems to have it processed adds a complexity to the storage mechanisms. Thus, the need of the time is to have systems which can handle the data in the real time. Extracting the Big Data and making use of it when it is still fresh, also demands to have smart systems which can deal with this fast flow of varied information.
How Will Business Intelligence Tools Play A Role?
Many Organizations have already initiated with the high level framework, which can deal with the volume and variation of data. This framework divides the information to various forms, which are different from each other. The next need for the Organizations is to have a system in place that can process the various forms of information and integrate it as one, in the end.
Understanding this in a technological aspect, the Organizations now need to understand which BI tools can be used individually to process which part of the information. This understanding will lead to a faster implementation in dealing with Big Data. The parts of input that still cannot be processed with the available tools may be handled by applying a few transformation logics. Thus, the only logical way to deal with Big Data at the moment seems to distribute it over the various systems, with minimal loss of valuable input rendered.
Read next blog on challenges in online transaction processing OLTP.
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