Descriptive and Predictive Analysis Essay

Big data analytics can be used by company to make informed business decision by examining large amount of varied data to get customer preferences, market trends and other useful information. Company can use it to explore new revenue opportunities, improved operational efficiency, better customer service and competitive advantages over rivals.

GPS, drones, spying, and nuclear war are all capabilities of the everyday items around us. These “normal” devices such as an iPhone or computer are all part of an enormous web infrastructure called the internet of things (IOT). The internet of things is a link between the online world and the physical world through connected devices which can achieve physical accomplishments such as taking a pulse. The Internet of things was said to have been discovered in 1999 during a presentation at Procter and Gamble. When Business moguls were trying to find a way to make the internet profitable, they manufactured the term internet of things. Ironically, IOT tracked its usage of term online through “Google Trends”. According to Google, since 2004 IOT was

Since the 1970’s databases and report generators have been used to aid business decisions. In the 1990’s technology in this area improved. Now technology such as Hadoop has gone another step with the ability to store and process the data within the same system which sparked new buzz about “big data”. Big Data is roughly the collection of large amounts of data – sourced internally or externally - applied as a tool – stored, managed, and analyzed - for an organization to set or meet certain goals.

This is one of the greatest challenge that is acting as a key barrier in widespread adoption and pervasive use of the tools fostering for development and progress in this field of study. The real time of the big data analytics would require some of the unique features and special computing powers and potentials (Gantz, 2012). Tools have to made specially advanced so as to incorporate process terms in real time (Chen, 2012). Every business oriented organization should be transformed into information centric (Kaisler, 2013) to focus upon the real time data analysis in terms of both input and output.

The author points out that although there are existing algorithms and tools available to handle Big Data, they are not sufficient as the volume of data is exponentially increasing every day. To show the usefulness of Big Data mining, the author highlighted the work done by United Nations. In order to further enhance the reader’s perspective, the author provided research work of various professionals to educate its readers about the most recent updates in Big Data mining field. The author further describes the controversies surrounding Big Data. The author has first provided the context and exigence by elaborating on why we need new algorithm and tools to explore the Big Data. The author used the strategy of highlighting the logos by mentioning the research work of different industry professionals, workshops conducted on Big Data and was able to appeal to connect to the reader’s ethos. The author also used pathos by urging the budding Big Data researchers to further dig deep into the topic and explore this area

The emergence of big data has provided different avenues for organizations to use data to improve different aspects of their respective operations. Be it customer service, research and development, or market position, Big Data has the potential to be a significant driving force in all these areas. However, there’s still a significant gap between the ability of Big Data to produce insightful analytical information based on real-time data and the ability of organizations to capture and utilize this readily available tool. This is, in part, due to the fact that the systems and processes necessary to fully maximize the usefulness of Big Data is currently lacking in most organizations. This lack of a conducive habitat for Big Data is further magnified in new organizations without any knowledge of Big Data. For organizations that have that have little to no knowledge of Big Data, there must be a thorough assessment of the benefits of big data and how they could improve the organizations overall place in the market. There also needs to be steps taken towards the design of frameworks that will enable the organization to better capture and utilize Big Data.

The Internet of Things (IoT) is the network of physical objects or "things" embedded with electronics, software, sensors, and connectivity to enable objects to exchange data with the manufacturer, operator

In a fast paced, business ordinated technological world the overall welfare of a company is tied to the success or failure to make the tough decisions. On one instance a company’s CEO might be able to make the choices based on experience, advice, or simple gut instinct. However, this is not the only skill one needs. There is a great deal of information to be found in being able to see investments in data and analytics. These decisions are based off of big data. Big data is a catch-phrase, used to describe a massive volume of both structured and unstructured data that is too large to process using traditional database and software techniques. The volume of data is in most cases is too big, moves too fast or it exceed the processing capacity the company has. Despite these potential drawbacks, big data contains the potential to help companies by improving operations and making faster, more intelligent decisions. This can be broken into three key parts, knowledge, data, and information.

Big data is buzzword in every field of business as well as research. Organizations have found its application across various sectors from Sports to Security, from Healthcare to e-Commerce.

Internet of Things (IoT) are devices that can collect and share data with no human interactions. IoT are machines that connect to other machines. Examples of IoT’s are fitness trackers that report to a smart phone, smart vacuum cleaners that are self- propelled, and Apps for your smart phone that can adjust lighting, temperature or security features at your house when you are away.

The amount of data in our world has been rapidly increasing and analyzing these large data sets, or big data, has become crucial for businesses in increasing their success. Many businesses use big data to model their business structures, control processes, and run the business. The availability of this data leads to a more accurate analysis of the target market. More accurate analyses lead to more confident decision making and better decisions means greater operational efficiencies, cost reductions and reduced risk. There are many ways in which big data can be successfully implemented in an organization. Big data allows businesses to segment their target market, creating more precisely tailored products and services. Big data is also used to conduct controlled experiments to make better management decisions. Finally, big data can unlock value by making the captured information transparent and usable at much higher frequency (Manyika, “Big data: The next frontier for innovation, competition, and productivity”).

Today, data is a growing asset that various businesses are having difficulty converting into a powerful strategic tool. Companies need help turning this data into valuable insight, which can diminish risk and enhance returns on investments. Companies are struggling to make sense and obtain value from their big data. Superior and reliable

One area in which the application of decision analysis appeared to be successful is in the oil industry. The decision environment within which an oil company has to operate is characterized by limited information and complexity. Also, these decisions require intensive capital expenditures thus they are related to substantial risk (Hosseini, 1986). The case of Tomco Oil Corporation is a good example for this type of decisions made under uncertainty.

As the time progresses, amount of data in various enterprises will keep on increasing and therefore, companies will need to continuously evaluate the latest tools and technologies to manage their data in best possible way such that they could respond to market demands quickly. This leads to continuous improvement of current technologies and also paves the way for the development of new technologies in the future.

The concept of the internet of things abbreviated as IoT was introduced as early as the late 90’s by Kevin Ashton, the Executive Director of Auto-ID Labs and a professor at Massachusetts Institute of Technology. Now, “the Internet of things is already a disruptive technology capable of determining fundamental changes that are happening in everyday life, and it is considered the fourth industrial revolution.” (Hucanu) The Internet of Things (IoT)