Objectives Of A Job Report In The Summer Training

Every day, we produce 2.5 quintillion bytes of data. 90% of all data in the world was produced in the past two years. Data has been around forever; we have always gathered information. Paleolithic cavemen recorded their activities by carving them in stone or notching them in sticks. Egyptians used hieroglyphics to record significant events in history. The Library of Alexandria was home to half-a-million scrolls of the ancient world. Less than hundred years ago, we used punch cards to record and store information. As technology continues to evolve, the amount of data we store continues to grow. We’ve come a long way since stone tablets, scrolls, and punch cards. It’s important to understand the concept of big data and the impact is has created. This paper will define the classifications of data, explain the challenges of big data, and describe how big data analytics is being used in today’s data driven world.

Abstract- Big data is a hot research topic in today’s world. Data has become an indispensable part of every economy, industry, organization, business function and individual. With the fast growth now-a-days organizations has filled with the collection of millions of data with large number of combinations. This big data challenges over business problems. Big Data is a new term used to identify the datasets that due to their large size and complexity. Big Data mining is the capability of extracting useful information from these large datasets or streams of data, that due to its volume, variability, and velocity. We address broad issues related to big data and/or big data mining, and point out opportunities which help to reshape the subject area of today’s data mining technology toward solving tomorrow’s bigger challenges emerging in accordance with big data.

Karp (2003) claimed that individuals can actualize their special talent by the way of skill development such as training, education and experience which signify that leadership can be secure by inspiring and encouraging through various channels. This concept has been adopted by public to set forth training programs. Such as Microsoft Cooperation, their summer intern program is the combination of recruiting and training by which they can identify individuals who are qualified and worth being cultivated.

Brown, B., Chiu, M., Manyika, J. (2011), Are you ready for the era of big data? Retrieved

Utilising a participative, supportive and results-orientated training style with a high emphasis on quality, performance management and the overall improvement of professional relations on an on-going basis.

They used facts and arguments from various sources, such as studies and authors. As they are introducing the topic, they use the ideas of Lev Manovich to justify their argument that the name “Big Data” can be misleading. Manovich observed that Big Data has been used to refer to data sets large enough to require supercomputers, yet large amounts of data can now be analyzed on much simpler computers. Boyd and Crawford contend that the value of the industry does not simply come from the large data sets, but the “patterns that can be derived by making connections between pieces of data…” By relating Manovich’s idea, their argument made more sense. As computers become more advanced, bigger data sets look much simpler. But the connections Big Data makes are still valuable, no matter how advanced computers

In the following sections I will be discussing various aspects of the process and analyse my own performance of the task and any skills I have gained.

We all got jobs and we need them to survive. I believe the best job is to be a business manager. When you're in business management you always have to be working hard. It takes a lot to be a business management from knowledge, and technology, education.the best way to describe this job is hard work.

The authors of [1] aim to dispel some of the current hype surrounding big data, mainly the misnomer that it is all about technology and the process is automated. In fact there are three critical elements requiring human expertise 1) the data must be the right kind, of sufficient quantity, and clean 2) a specific process must be followed for success starting with the identification of the objective 3) expert humans who know how to use the technology, execute the big data process, and perform the mining tasks which require significant mathematical calculations.

I am writing to seek the Directorate of Operations internship in Washington, D.C. that the Central Intelligence Agency (CIA) offers. I am currently a freshman student at Harvard College in Cambridge, MA, and have served in a variety of political, governmental and legal roles throughout my work career. I trust that, upon review, you will recognize that the skills and experience I have garnered are exactly what the CIA looks for in a Directorate of Operations intern.

Foster Provost and Tom Fawcett. Big Data, Data Science and its Relationship to Big Data and Data-Driven Decision making,” http://online.liebertpub.com/doi/full/10.1089/big.2013.1508

Big Data is an expansive phrase for data sets so called big, large or complex that they are very difficult to process using traditional data processing applications. Challenges include analysis, capture, curation, search, sharing, storage, transfer, visualization, and information privacy. In common usage, the term big data has largely come to refer simply to the use of predictive analytics. Big data is a set of techniques and technologies that need or require new forms of integration to expose large invisible values from large datasets that are diverse, complex, and of a massive scale. When big data is effectively and efficiently captured, processed, and analyzed, companies

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 promise of data-driven decision-making is now being recognized broadly, and there is growing enthusiasm for the notion of ``Big Data.’’ While the promise of Big Data is real -- for example, it is estimated that Google alone contributed 54 billion dollars to the US economy in 2009 -- there is currently a wide gap between its potential and its realization.

For analysis, advanced statistical tools are used and the experimenter can draw necessary conclusions and inferences. In business sectors, they have a huge amount of scattered data in terms of profits, loss, demand, supply, sales and production. The industrial, insurance, agricultural, banking, information technology, food industry, telecommunication, retail, utilities, travel, pharmacy and many more have challenges to manage their data. As the coin always has two sides, there are both advantages and a few disadvantages of data analysis. The key advantages of data analysis are- The organizations can immediately come across errors, the service provided after optimizing the system using data analysis reduces the chances of failure, saves time and leads to advancement. It is also used to compare strategies between two companies so as to reduce the prices and gaining attention of target customers, ultimately leading to maximization of profit and minimization of cost(as done in Game Theory). However, big data analysis sometimes becomes more tedious and disadvantageous because it uses software Hadoop which requires special provisions in the computers. For now use of Hadoop for real-time analysis is not available. The manner in which the data is collected and the decision making view can vary from one person to another. Here, the quality of data gets affected and leaves the data insufficient or inefficient. In order to tackle this problem, the researcher must be professional, well experienced and should have deep knowledge about the characteristic under study. Also, we need to update data from time to time so as to avoid the changes in trend caused by the past data especially, for the rapidly growing