A glimpse of Big Data Essay Example for Free

A glimpse of hulky info Essay Brobdingnagian information is not a meticulous term rather its a characterization of the never ending accumulation of all kinds of information, most(prenominal) of it un organise. It describes information sets that are growing exp angiotensin converting enzymentially and that are too large, too raw or too unintegrated for analysis using relational selective informationbase techniques. Whether terabits or petabytes, the precise amount is less the issue than where the data ends up and how it is pulmonary tuberculosisd.Cite from EMCs publish speculative data elephantine opportunity to create business foster. When explosion happened in alert ne 2rk, cloud computing and internet technology, more and more contrasting information appeared. In the past, the numerous terabyte data could be a disaster for any play along, beca office it centre broad(prenominal) cost of storage and high performance CPU. However, in nowadays, companies discover ed many facts they havent thought or so these data before. Companies started to use data analytics technology to image business values from these terabyte or petabyte data. It seems to be a galactic opportunity instead of disaster for companies now. entropy is not only defined as organize data. When we talking about enceinte data, it could be categorized into three types of data structured data, unstructured data, and semistructured data (Please see map I).Especially when internet and mobile internet developed rapidly, the unstructured data and semistructured data exploded. For specimen, a bank could gain a conclusion by analyze unstructured data to find out why number of churn increased. Most definitions of bear-sized data all talk about the size of data. However, size, or volume, is not the only characteristic of large-scale data. There are other two characteristics, variety and velocity. Variety means loose data generates from several of sources. Data type was no end less connected to structured data. According to the EMCs report, most of big data related to unstructured data. amphetamine means the speed of data wareion. Data was no long structured data which was stored in the structured database. Data could come from anywhere and anytime mobile, censors, devices, manufacturing machine etcetera The stream of data generates in real time. This means keep companys action should be taken with this speed.Structured data Structured data is organize in structure. These data can be read and stored by computer. The form of structured data is structured data base that store specific data by methodology of columns and rows. uncrystallised data Unstructured data refers to the data without identified structure. For example, video, audio, picture, text and so on. These data also called loosely structured data. Semistructured data Semistructured data organized in semantic entities. The datas size and type in one group could be different. For example, X ML and RSS feeds. This data subdue to reconcile the real world with computer based database. Chart I. Three types of data.Big data analyticsBig data analytics is not a technique. It is a terms that contains a lot of technologies (See EXHIBITION I). Based on enterprises different requirement, each program bequeath use different technology to analyze data. However, with the big datas development, some of these techniques become universal and useful. On the basis of the exhibition II, advanced analytics, visualization, real time, in-memory databases and unstructured data have loyal-to-moderate commitment and strong potential growth.The traditional techniques, for example, OLAP tools and hand-coded SQL, have gradually lost their place. When a bank want to find the rationalness why the number of customer churn increased, or marketing section decide to push precise advertisement to their customer, they need to analyze customer behavior. These data from customer service emails, phone call records, gross revenue interview reports, login data from mobile devices, and so on. Almost all of these data cannot be analyzed by traditional data analytic techniques. Thats why these new techniques development so rapid and fierce. How a company adopt big data analytics?According to the article Big Data, Analytics and the Path from Insights to Value promulgated on MIT Sloan Management Review, the author categorized the company who used big data analytics into three stages (See order II). For most companies, it is easy to establish an enterprise data warehouses (EDWs). However, how to interpret these data and finding the business value from these data become the most crucial factor for companies. Besides, so many techniques and tools behind the term big data. For any company who decide to adopt big data analytics, the leading obstacle is lacking of apprehensiveness of how to use analytics to improve their business. From the article, the author gave 5 recommendation to any c ompany who wanted to adopt big data analytics.1. Think Big. Focus on the biggest and highest value opportunities. Narrow down the options. 2. Start in the Middle. inside each opportunity, start with questions, not data. Company prefer to collect data and information at frontmost place. In fact, start with questions could help company continue to narrow down the scope and define the most valuable direction. 3. Make analytics come alive. When Problem was defined, company need to apply analytics. Choosing the propriety tools to analyze the data. 4. Add, dingdong detract. Use centralized analytics. Every analysis is connected. 5. Build the parts, plan the whole. Big data from everywhere. The data entrust become more and more big and complex. Building the data infrastructure is crucial for big data analytics. Big Data, Big OpportunityWhen company decide to concern big data, it means every department are involved. Big data is not IT departments or analysts responsibility. In fact, big d ata analytics need information and help from sales, marketing, RD, IT and even external sources. Today, number of companies have entered into big data market. The sideline chart lists some big organizations who have adopted big data analytics. Besides, some of them provide big data services to other companiesThese organizations are just the tip of the iceberg. When big data converted from blue devil Ocean to Red Ocean, some of these organizations have turned into services provider. This become a future sheer in big data area. Big data needs expensive hardware and labor cost. non every company can afford that. Besides, big data involved so many different computer technologies, not everyone understood all these techniques. For that matter, there will be more and more companies try to seek big data service from external environment. Using the external big data syllabus or tools could reduce the cost for building a totally new technique teams. What the companies need to do is findi ng the problem, narrow down the scope and sending the needs to services provider. When they get the analysis result, they could use the valued result to take the next action.Furthermore, these services provider will not only focus on on big companies. The new fashion is to provide friendly interface and easy to use product to individual customer. What behind big data will be still mystery for people, however, the face or terminal of big data will become more and more friendly and simple. There is an example Twithink. Twithink is a program invented by a MIT group. They provide customized twitter behavior analysis for customer. This program could draw some conclusion by analysis the unstructured information on Twitter. They collected the gender, location, time, key words, images, etc. from tweets. Then they analysis these data under certain arithmetic to draw conclusions. The last research was the preference in 2012. The latest research is Gun Control discussion which still in progr ess.Problem and threats.Although big data has many opportunity and advantage for enterprises, it still has some disadvantages. The first crucial problem is screen invasion. After you searched one product on Amazon, the next time when you login to Amazon, you will find the products you may enkindle which was Amazon pushed to you. This is called precise advertisement. However, you even didnt know when amazon collected your information. Another example was Google Analyst, company embedded code into their website to collect peoples internet behavior.These things happened every day and everywhere. It is hard to urge this action is right or wrong. Maybe some are good. However, if personal data is sold or published by someone, it will affect individuals daily life. It will become a crucial problem. The Second problem is informations validity. According to the article With big data comes big responsibilities points out that big data sets are never complete. If data is insufficient, the a nalysis result would be invalid or distorted. The invalid information would guide company to wrong direction and cause a big loss. Thus, big data also has two side. How to use it to create more value for company is the first consideration for all managers.Reference1. Office 2013 Brings BI, Big Data to Windows 8 Tablets. ZDNet. N.p., n.d. entanglement. 25 Jan. 2013. 2. Big Recognition for IBM Big Data. 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