Explain the professional practices in IT?
The analysis of Big Data involves numerous distinct phases, each of which originates many challenges. Many people distinctly focus just on the modeling phase: while that aspect is important, it is of a very brief use without another phase’s analysis of data pipeline. Even in the stage of analysis, which had received much attention, there are worst understood difficulties in the context of multi-tenanted collections where different users’ programs run simultaneously (Prajapati et al. 2013). Many rich challenges extend beyond the phase of analysis. For instance, a Big Data has to be maintained in context, which might result very noisy, homogenous and not include and direct model (Davis et al. 2013). The need to track the origin and to manage error and uncertainty topics that are vital to success, yet frequently mentioned in the same breath as Big Data. Similarly, the investigations to the analysis of data pipeline will not all is laid out in advance. This study emphasized on data analytics with considering Oracle as the case organization. Oracle is an object oriented database management system marketed and produced by Oracle Corporation. It is the world largest database management system software provider.
Data Analytics is the branch of scrutinizing organic data with the aim of representing completion about the orientation (Chardonnens et al. 2013). It is used in many industries to make business decisions and to authenticate absolute theories. In other words, it is the process of examining, inspecting, testing, analyzing organization useful information, thereby helps in suggesting decision-making. It is very sophisticated software used by almost all the industry.
In many multi-national industries, the theory of data analytics is at height. Many industries use big data analytics. It refers to skills; practice, technology, and investigation of past activities of business that include past business performance, to gain organizational interest and turn to business planning. The figure shown below is the analytics of Oracle:
It is used in business management since the 19th century to face each challenge that frequently arises in commercial activities (Davis et al. 2013). After the invention of data analytics, it had succeeded to bring changes to a completely new level and made endless possibilities.
Errors of the organization are known shortly: It helps companies to react fastly to migrate the operational problems. This will assist the organizational operations to save quickly falling from the stop of the database products (Chardonnens et al. 2013).
New and latest strategy of the industry are known immediately: With the system like Real-Time Big Data, the industry can move one step ahead to get notified of the direct competitor and to lower of the process immediately (Zheng et al.2015).
Detection of fraud: In the world of the multi-national financial area is very attractive to the criminals. Hacking of any type of database system will be informed instantly (Prajapati et al. 2013).
Special computer power: In a company like an oracle the technology like Hadoop is not suitable for Oracle. New tools and latest technology increases costs of Oracle (Prajapati et al. 2013).
Different insights of using real-time data: To gain an accurate information result from greater insights that will harm the entire industry by overlooking some of the processes.
Maintain ace of the system: The management of the system in Oracle requires highly qualified and trained candidates to take and maintain several types of system (Chardonnens et al. 2013).
Risk Assessment: In an industry like Oracle (Corporate Performance Management) helps to make the evolution of the real world technology. It is becoming very tough for the industry to maintain financial forecasting in the market (Prajapati et al. 2013). Because the whole database market is vastly complicated and interconnected.
Analytics business real time: There is a mismatch between different businesses that where should they apply the allocated resources. In some places, business and data work faster than employees. However, in maximum places, it becomes a bottleneck as it is very useful (Chardonnens et al. 2013). In a real time system, the allocation of several resources is quite vital.
Measuring proper Rate of Interest: Oracle develops several types of database software in the market. There is an enough competition for the same product thereby as a brand name of Oracle; it releases a product at a very low price (Zheng et al. 2015). Hence, it results in a low gain rate of interest
Big Data Potential: The actual potential of Big Data application will be unlocked when we get a customized view. In an exact way, that we each have a personal profile on any sites, we will positively have a personally customized view of each data that we interact with. To unlock application vendors provide differentiated value.
By collaborating with a digital solutions technology, a personalized technology system can be developed for Oracle, solving every organizational challenge listed above (Davis et al. 2013). To start an intelligent, analytical scheme and to implement with different digital campaigns allows Oracle to work efficiently and collect useful data (Börner et al. 2015). By maintaining integrated database system helps Oracle to get accessible to information quickly. It is very beneficial to make the environment more user-friendly from several source channels. It is very crucial for the industry to remove the unnecessary noise by making the interaction of consumer trends (Chardonnens et al. 2013). Dashboard analytics is the massive and vast amount of data that determines and gives the ability to organize and make the actual sense of data that had been collected. It takes the data and information to look visually and intuitive and make easily accessible presentable.
In this context, an example is taken into account. According to this, when any customer enters in a bank, Big Data allows the clerk to check their profile and helps them to learn different products they might advise (Chardonnens et al. 2013). It will also have a significant role to play in initializing the physical and digital spheres of shopping; retailers could suggest an offer a mobile, by customer indicating a need in a social media (Börner et al. 2015).
There are few responses from customers in view of data analytics: reporting and insights, holistic approach to different customer services, integration of external and internal data feed in public place, timely response, use of proper and dedicated software of data analytics
Oracle is world number one database management software provider who integrates and manages different system and in that context the trend of Oracle till 2020 is shown below:
Relational Data Cloud Data Analyze, big and enhanced data on Hadoop Aggregate and Transform data using interactive analysis, trends of data with Machine Learning, utilization of Internet things in Real Time Transforming business with a complete data analytics
Conclusion
This study concluded that the existence of Big Data, low-cost products hardware, and latest information management and analytical software has composed an exclusive moment in the history of analysis of data. The solitary of these trends means that we have the efficiency to analyze data sets cost-effectively and quickly for the first time in history. This potential is neither trivial nor theoretical. They perform a genuine surge forward and a fair opportunity to comprehend the enormous gains regarding productivity, efficiency, profitability and revenue. The youth of Big Data is here, and these are truly radical times if both technology and business professionals promote to work stable and convey on the promise.
References
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Börner, M., Rhode, W., Ruhe, T., Morik, K., & IceCube Collaboration. (2015). Discovering Neutrinos Through Data Analytics. In Machine Learning and Knowledge Discovery in Databases (pp. 208-212). Springer International Publishing.
Chardonnens, T., Cudre-Mauroux, P., Grund, M., & Perroud, B. (2013, October). Big data analytics on high Velocity streams: A case study. In Big Data, 2013 IEEE International Conference on (pp. 784-787). IEEE.
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