IT assignment essay on: Terminologies of Information Technology Big Data

What Big Data is about?

As per the terminologies of Information Technology Big Data is defined as the set of data which is huge and very complex in nature. These data is highly difficult to be processed by using the on-hand based management tools. There are several challenges which include capturing, storage, searching, analysing, and visualizing. This trend of getting a larger data set is due to the additional information which is derived from the analysis of the single large set of data in comparison to the smaller set of data. Here the total amount of data allows a correlation for: (itbusinessedge 2012)

• Spotting business trends,
• Determining the quality of research,
• Preventing diseases,
• Combating crime,
• Determining the real time roadway traffic conditions

It is very difficult to work on big data by the use of relational databases as well as the desktop statistics along with the visualization packages. They require massively parallel software which runs on as much as thousands of different servers. The concept of big data may vary from one organization to the other which is directly proportional to the capabilities of an organization. For example: a big data could be hundreds of gigabytes of data for some organizations, whereas for many others it could be thousands of terabytes.

By Definition Big Data includes data sets which are of huge size and beyond the ability of the commonly used software to capture, manage, and process within a specific tolerable time. By this year the data sizes seem to have moved from a few dozen terabytes to many petabytes of data in the single data set. Sensing this as a difficult task several new platform for the big data tools has come up to make the process easier.

What is the potential of Big Data?

After understanding what exactly the Big Data is the question comes to the potential this data could have for different businesses. The recent buzz of the big data has been that it will affect the marketing and advertising innovation as well as productivity of the organizations in future.

Especially those companies who have a big customer database which surely includes the Singapore Airlines would be largely benefitted from them. Besides this there are large volumes of the data that need to be processed and made available in fraction of a time. In the past leveraging these big data sets were pretty difficult only due to the lack of technology. But in the last 5 to 6 years there has been a revolution in terms of technology, processing as well as marketing innovation. This has helped organizations with big data to capture and process data at exceptional speed. It’s not that any single industry has been benefited but almost every business unit from any sector relying on Information technology has benefitted in a great deal (itbusinessedge 2012).

How Businesses are using the Big Data?

There are numerous ways in which the businesses are utilizing the big data. Some of them have been discussed below:

• For delivering exceptional quality of services to their customers:

The fact that it has become easier to capture and process a big transactional as well as behavioural data set from both the online as well as the offline sources it has made it possible for the organizations to create narrower segments. This in turn helps the marketers for understanding the behavioural profiles of the customers along with the prospects besides facilitating in accurately anticipating the needs of the customers. Thus businesses are utilizing the processed results to deliver highly tailored as well as dynamic services. These could be at any place depending on the domain of the business. Therefore the businesses that are able to use these data in the right manner would highly benefit by an increase in the customer engagement and satisfaction.

·         Improving the overall advertising efficiency:

In the recent times it has been seen that businesses are getting involved in the real time bidding models. As per this model the advertisers try to leverage audience as well as placement of data for maximizing the value they derive from the media. Using the Big data is actually extending the RTB models beyond the display or the digital technology for encompassing the entire media ecosystem. In the future it is expected for the RTB platforms will enable in linking the inventory to all the addressable channels and further enabling the brands for optimizing the price which is paid as per the exposure in the real time. Therefore with the media inventory demand and the supply getting matched in real time, the media bidding and buying platform is slated to create a better market efficiency which means offering lower prices. What this would mean is that by offering lower prices the possibility of the advertisers as well as the publishers for allocating the investments and hence benefiting the consumers.

• Increasing the profitability:

Big Data along with the analytics has become the epicentre of driving profitability for most of the businesses. With the emphasis being laid largely on the bottom line every business is getting concerned about the quality of customers they are able to attract and retain. The innovation which has been evident in the location based services along with mobile profiling will actually make the marketers for personalizing the messages and offer a real time based on profile of the consumers. Moreover it also provides their location, the inventory available, etc. The marketers of different business units are not able to evaluate the impact of their programs on short term sales as well as the long term customer perception and brand loyalty.

What are the Business opportunities and benefits from Big Data?

With the Big data already popular and vastly used around the organizations around the globe the opportunities that it holds and the benefits it is expected to provide is evident. The Big data is already transforming the way businesses are thinking about their marketing strategies. With innovative offerings and the big data that is being processed from the media channels, media buying or the feedback loops would certainly help the businesses for delivering meaningful as well as personalized experiences. Further it would facilitate in understanding consumer behaviour, improving the offerings and building a much stronger prospects for the customers to become brand loyal (getsatisfaction 2011).

What are the Problems and drawbacks of Big Data?

Although big data is highly efficient when used in the right manner there comes a few problems or drawbacks with it as well. Many experts such as Danah Boyd have raised concerns of the big data being used while neglecting the principles of science. A common example cited by her was the method to choose representative sample while being much concerned about the amount of data that is available. As she mentions the approach of selective sampling may yield biased results in a way or the other.

Many others have also argued that although the integration across several heterogeneous data sources which often is considered to be as big data presents formidable logistical and analytical challenges, it may actually represent the most promising new frontiers of science. As per the assertion of Chris Anderson big data could be an end of theory, where it the data would always be contextualized in the social, political as well as economical contexts. Another drawback which had been cited is the lack of knowledge among the employees to properly process the data that are made available to them. It is estimated that where businesses are spending millions for deriving an insight information from the information they get from their suppliers and customers only a small proportion of their workforce actually do it right to process the data in the manner it deserves.

Also some have even raised the concerns over the consumer privacy with the threat due to the increase in storage as well as integration of the personally identifiable information. In the recent times numerous expert panels have been releasing various policy recommendations for protecting the possibility of intrusion in privacy of the consumers in an attempt to gather big data.

What are the future of big data and the next steps of taking advantage from it?

Businesses around the globe are indulging in finding out the best ways for storing the big data which is actually a big challenge for all. The most difficult of the sources for the big data to be stored is the internet. This has been regarded as the most challenging aspect where machine to machine data sharing as well as analytics would be one of them. Currently with the amount of big data flowing in for each organization the businesses are focussing on finding out the right ways for to collect and store them. The future of Big Data will have the companies stressing on the storage than concentrating on the advanced analytics.

Another big challenge that seems to be in store for the future is the explosion of the machine to machine data. The common sight in consumer and industrial devices are the wireless sensors. In Japan high speed trains come with sensors to check the seismic activities, anomalies, environmental changes as well as unexpected rail traffic. In the future with machines talking to other machines and sharing information, correlating the things which goes in a place with another and finally coming out with the conclusions so that its presented to the humans to take the right steps and measures. This further brings in tactical as well as financial challenges for the business globally (getsatisfaction 2012).

With the future of big data bringing challenges the best way of taking advantages need not involve throwing of data in a storage system. But it should be stored in such a way that the big data could be accessed from any corner of the world when required.

One of the means through which even the smaller businesses can take advantage of the big data is the In-memory analytics. This advanced analytics system offers sub second response times along with hundreds of thousands of transactions every second. With the costs coming down it surely comes within the reach of the smaller organization and take advantage of the big data. Researches are being conducted for aligning businesses and IT in a much closer manner through the master’s program which focuses on the analytics. (businessonmain 2011)

Reasons why Singapore Airlines should consider using big data?

With all the advantages discussed above it must be clear that Big Data could do wonders to any sector where it is used in. For Singapore Airlines to take the use of Big Data the reasons would be as follows:

• It will allow the management to take critical decisions. These decisions would include the time to decide when the inventories need to be opened or closed on the existing flights in order to avoid overbooking issues.
• It would facilitate in leveraging the Integrated Passenger Name Record(iPNR) data warehouse by the use of sophisticated analytics for providing the details on overbooking as well as passenger no-shows.
• Would help in highlighting the impact of the customer behaviour on the basis of on demand and show rate trends hidden in the PNR details.
• Would provide detailed description for every metric as well as report layout that would include the value along with the audience for that particular report.
• Moreover with the big data being captured and deliver the desired results it would be easier for the company for understanding the real causes for current trends and possible shifts in the customer behaviour.

Risks that Singapore Airlines should consider and the ways it could mitigate them

The possible risks which may arise while the company trying to consider big data for processing could be as follows:

• May not depict the real picture: As for analysis a section of the larger data is taken it may not reflect the right picture. In order to mitigate this effect it would be required to take the data for processing from almost all corners and all sections which reflects the average consensus.
• May not have the right tools: Big data is obviously much more complex and difficult to handle. It would take the company to adopt the right tools to collect and process the huge collection of data so that the results are reliable and depict the real picture.
• Lack of skilled Technicians: Well it is not easy for every engineer to use and process the Big Data. It needs highly skilled understanding and knowledge to process the data in the manner which it has to be. In order to mitigate this, the thing which most companies have adopted and SIA would be required to adopt will be training the technical staff by the experts who understand big data in the best possible manner.
• Getting customer confidence and maintaining privacy of the customer data: The primary concern is to provide the right security to ensure customer data is protected. Moreover as big data includes all personal information of thousands of customers it is very important to protect them from any unauthorized access. Using the most advanced tools and software which have been serving the companies in handling security of big data for years could be the only solution to this.

How the SIA can measure the success of its Big Data initiative? 

While discussing everything above the point where all comes and stop is how one can track or measure the success of Big Data initiative. Well yes the only thing which matters for a successful business is the ROI which is the first thing companies tend to find out before implementing a project. The success is evaluated in two phases where the 1^st involves discovery. Initial calculations of ROI may not actually be the result which you might be getting. As it is very difficult to predict what is in store for the future one could surely expect additional ROI benefits which might not have been thought of. SO while using the Big Data it is recommended to perform the cost benefits analysis for the project although many benefits are not visible while you calculate. It is important to carry out the cost benefit analysis in three stages namely:

• Before implementation
• During implementation
• After successful implementation

Conclusion

Singapore Airlines as mentioned is the youngest fleet carrier today. With its innovative approach and attractive branding strategies is destined to grow and reach heights. The company is currently using the Information Technology, Cloud computing and Big Data in some or the other way. However the implementation of each with a strategy to work in phases would do wonders for the company. SIA could utilize the data and the information collected to provide better customer services and also increase operational efficiency. Therefore, with the focus to provide enhanced customer satisfaction and cater to the needs to compete while providing efficient services each of the aspects discussed above needs to be discussed and implemented in phases. Further a proper follow up and regular monitoring by the right authorities would be one of the important aspects as well as the challenges that the company needs to address.

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