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69-520: "Internet Plus" refers to the application of the internet and other information technology in conventional industries. It is an incomplete equation where various internets (mobile Internet, cloud networking, big data or Internet of Things) can be added to other fields, fostering new industries and business development in China. It was a five-year plan to integrate traditional manufacturing and service industries with big data, cloud computing, and Internet of things technology. China's economy's growing speed

138-576: A C++ -based distributed platform for data processing and querying known as the HPCC Systems platform. This system automatically partitions, distributes, stores and delivers structured, semi-structured, and unstructured data across multiple commodity servers. Users can write data processing pipelines and queries in a declarative dataflow programming language called ECL. Data analysts working in ECL are not required to define data schemas upfront and can rather focus on

207-413: A statistical population , and each row corresponds to the observations on one element of that population. Data sets may further be generated by algorithms for the purpose of testing certain kinds of software . Some modern statistical analysis software such as SPSS still present their data in the classical data set fashion. If data is missing or suspicious an imputation method may be used to complete

276-513: A fourth concept, veracity, refers to the quality or insightfulness of the data. Without sufficient investment in expertise for big data veracity, the volume and variety of data can produce costs and risks that exceed an organization's capacity to create and capture value from big data . Current usage of the term big data tends to refer to the use of predictive analytics , user behavior analytics , or certain other advanced data analytics methods that extract value from big data, and seldom to

345-459: A higher false discovery rate . Big data analysis challenges include capturing data , data storage , data analysis , search, sharing , transfer , visualization , querying , updating, information privacy , and data source. Big data was originally associated with three key concepts: volume , variety , and velocity . The analysis of big data presents challenges in sampling, and thus previously allowing for only observations and sampling. Thus

414-447: A moving target. "For some organizations, facing hundreds of gigabytes of data for the first time may trigger a need to reconsider data management options. For others, it may take tens or hundreds of terabytes before data size becomes a significant consideration." The term big data has been in use since the 1990s, with some giving credit to John Mashey for popularizing the term. Big data usually includes data sets with sizes beyond

483-416: A multiple-layer architecture was one option to address the issues that big data presents. A distributed parallel architecture distributes data across multiple servers; these parallel execution environments can dramatically improve data processing speeds. This type of architecture inserts data into a parallel DBMS, which implements the use of MapReduce and Hadoop frameworks. This type of framework looks to make

552-851: A particular size of data set. "There is little doubt that the quantities of data now available are indeed large, but that's not the most relevant characteristic of this new data ecosystem." Analysis of data sets can find new correlations to "spot business trends, prevent diseases, combat crime and so on". Scientists, business executives, medical practitioners, advertising and governments alike regularly meet difficulties with large data-sets in areas including Internet searches , fintech , healthcare analytics, geographic information systems, urban informatics , and business informatics . Scientists encounter limitations in e-Science work, including meteorology , genomics , connectomics , complex physics simulations, biology, and environmental research. The size and number of available data sets have grown rapidly as data

621-461: A person's height in centimeters, but may also be nominal data (i.e., not consisting of numerical values), for example representing a person's ethnicity. More generally, values may be of any of the kinds described as a level of measurement . For each variable, the values are normally all of the same kind. Missing values may exist, which must be indicated somehow. In statistics , data sets usually come from actual observations obtained by sampling

690-419: A set of techniques and technologies with new forms of integration to reveal insights from data-sets that are diverse, complex, and of a massive scale. "Volume", "variety", "velocity", and various other "Vs" are added by some organizations to describe it, a revision challenged by some industry authorities. The Vs of big data were often referred to as the "three Vs", "four Vs", and "five Vs". They represented

759-403: A special need. Commercial vendors historically offered parallel database management systems for big data beginning in the 1990s. For many years, WinterCorp published the largest database report. Teradata Corporation in 1984 marketed the parallel processing DBC 1012 system. Teradata systems were the first to store and analyze 1 terabyte of data in 1992. Hard disk drives were 2.5 GB in 1991 so

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828-532: A tool to help employees work more efficiently and streamline the collection and distribution of information technology (IT). The use of big data to resolve IT and data collection issues within an enterprise is called IT operations analytics (ITOA). By applying big data principles into the concepts of machine intelligence and deep computing, IT departments can predict potential issues and prevent them. ITOA businesses offer platforms for systems management that bring data silos together and generate insights from

897-416: Is a highly lucrative tool that can be used for large corporations, its value being as a result of the possibility of predicting significant trends, interests, or statistical outcomes in a consumer-based manner. There are three significant factors in the use of big data in marketing: Examples of uses of big data in public services: Data set A data set (or dataset ) is a collection of data . In

966-402: Is an open approach to information management that acknowledges the need for revisions due to big data implications identified in an article titled "Big Data Solution Offering". The methodology addresses handling big data in terms of useful permutations of data sources, complexity in interrelationships, and difficulty in deleting (or modifying) individual records. Studies in 2012 showed that

1035-512: Is collected by devices such as mobile devices , cheap and numerous information-sensing Internet of things devices, aerial ( remote sensing ) equipment, software logs, cameras , microphones, radio-frequency identification (RFID) readers and wireless sensor networks . The world's technological per-capita capacity to store information has roughly doubled every 40 months since the 1980s; as of 2012 , every day 2.5 exabytes (2.17×2 bytes) of data are generated. Based on an IDC report prediction,

1104-451: Is declining due to the growing debt, declining factory activity and foreign exchange reserves devaluation, which has led the government to figure out a plan to create a new driver to stimulate its development. In the field of industrial development, the U.S. government has put forward the term "Industrial Internet", while Germany has proposed the idea of Industry 4.0 . The emerging new industrial revolution and ecological revolution as well as

1173-501: Is good—data on memory or disk at the other end of an FC SAN connection is not. The cost of an SAN at the scale needed for analytics applications is much higher than other storage techniques. Big data has increased the demand of information management specialists so much so that Software AG , Oracle Corporation , IBM , Microsoft , SAP , EMC , HP , and Dell have spent more than $ 15 billion on software firms specializing in data management and analytics. In 2010, this industry

1242-436: Is not trivial. With the added adoption of mHealth, eHealth and wearable technologies the volume of data will continue to increase. This includes electronic health record data, imaging data, patient generated data, sensor data, and other forms of difficult to process data. There is now an even greater need for such environments to pay greater attention to data and information quality. "Big data very often means ' dirty data ' and

1311-400: Is particularly promising in terms of exploratory biomedical research, as data-driven analysis can move forward more quickly than hypothesis-driven research. Then, trends seen in data analysis can be tested in traditional, hypothesis-driven follow up biological research and eventually clinical research. A related application sub-area, that heavily relies on big data, within the healthcare field

1380-482: Is that of computer-aided diagnosis in medicine. For instance, for epilepsy monitoring it is customary to create 5 to 10 GB of data daily. Similarly, a single uncompressed image of breast tomosynthesis averages 450 MB of data. These are just a few of the many examples where computer-aided diagnosis uses big data. For this reason, big data has been recognized as one of the seven key challenges that computer-aided diagnosis systems need to overcome in order to reach

1449-407: Is that they are relatively slow, complex, and expensive. These qualities are not consistent with big data analytics systems that thrive on system performance, commodity infrastructure, and low cost. Real or near-real-time information delivery is one of the defining characteristics of big data analytics. Latency is therefore avoided whenever and wherever possible. Data in direct-attached memory or disk

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1518-521: The IT industry such as Ma Huateng , the founder of Tencent and Yu Yang, CEO of Analysys International, first put forward the idea in 2013 in a bid to extend their businesses into some service sectors. China's Premier Li Keqiang brought up the concept of Internet Plus and made it the national strategy in his Government Work Report presented to the National People’s Congress. Internet Plus aims to use

1587-532: The open data discipline, data set is the unit to measure the information released in a public open data repository. The European data.europa.eu portal aggregates more than a million data sets. Several characteristics define a data set's structure and properties. These include the number and types of the attributes or variables, and various statistical measures applicable to them, such as standard deviation and kurtosis . The values may be numbers, such as real numbers or integers , for example representing

1656-622: The American Statistical Association . In 2021, the founding members of BigSurv received the Warren J. Mitofsky Innovators Award from the American Association for Public Opinion Research . Big data is notable in marketing due to the constant "datafication" of everyday consumers of the internet, in which all forms of data are tracked. The datafication of consumers can be defined as quantifying many of or all human behaviors for

1725-535: The British public-service television broadcaster, is a leader in the field of big data and data analysis . Health insurance providers are collecting data on social "determinants of health" such as food and TV consumption , marital status, clothing size, and purchasing habits, from which they make predictions on health costs, in order to spot health issues in their clients. It is controversial whether these predictions are currently being used for pricing. Big data and

1794-508: The Internet. Although, many approaches and technologies have been developed, it still remains difficult to carry out machine learning with big data. Some MPP relational databases have the ability to store and manage petabytes of data. Implicit is the ability to load, monitor, back up, and optimize the use of the large data tables in the RDBMS . DARPA 's Topological Data Analysis program seeks

1863-542: The IoT work in conjunction. Data extracted from IoT devices provides a mapping of device inter-connectivity. Such mappings have been used by the media industry, companies, and governments to more accurately target their audience and increase media efficiency. The IoT is also increasingly adopted as a means of gathering sensory data, and this sensory data has been used in medical, manufacturing and transportation contexts. Kevin Ashton ,

1932-405: The ability of commonly used software tools to capture , curate , manage, and process data within a tolerable elapsed time. Big data philosophy encompasses unstructured, semi-structured and structured data; however, the main focus is on unstructured data. Big data "size" is a constantly moving target; as of 2012 ranging from a few dozen terabytes to many zettabytes of data. Big data requires

2001-413: The amount of e-commerce has been more than 13 trillion yuan (Chinese monetary unit). China's import and export transactions of cross-border e-commerce has exceeded 3 billion yuan. The potential risks of this new technology in a financial industry also exists in terms of personal information security since the related information could be under higher exposure than before. Internet plus is expected to ease

2070-437: The case of tabular data, a data set corresponds to one or more database tables , where every column of a table represents a particular variable , and each row corresponds to a given record of the data set in question. The data set lists values for each of the variables, such as for example height and weight of an object, for each member of the data set. Data sets can also consist of a collection of documents or files. In

2139-526: The country’s long-awaited economic transformation." On top of that, while Chinese government filter a lot of access to information, the relationship between Internet Plus and freedom of speech online is doubted by some people. Big data Big data primarily refers to data sets that are too large or complex to be dealt with by traditional data-processing software . Data with many entries (rows) offer greater statistical power , while data with higher complexity (more attributes or columns) may lead to

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2208-470: The definition of big data continuously evolves. Teradata installed the first petabyte class RDBMS based system in 2007. As of 2017 , there are a few dozen petabyte class Teradata relational databases installed, the largest of which exceeds 50 PB. Systems up until 2008 were 100% structured relational data. Since then, Teradata has added semi structured data types including XML , JSON , and Avro . In 2000, Seisint Inc. (now LexisNexis Risk Solutions ) developed

2277-521: The desired outcome. A common government organization that makes use of big data is the National Security Administration ( NSA ), which monitors the activities of the Internet constantly in search for potential patterns of suspicious or illegal activities their system may pick up. Civil registration and vital statistics (CRVS) collects all certificates status from birth to death. CRVS is a source of big data for governments. Research on

2346-535: The digital innovation expert who is credited with coining the term, defines the Internet of things in this quote: "If we had computers that knew everything there was to know about things—using data they gathered without any help from us—we would be able to track and count everything, and greatly reduce waste, loss, and cost. We would know when things needed replacing, repairing, or recalling, and whether they were fresh or past their best." Especially since 2015, big data has come to prominence within business operations as

2415-572: The digital interactions between the government and citizens, government and government agencies, government and employees, and government and the commerce.(Jeong, 2007) With the help of this new strategy, governments can enable anyone visiting a city website to communicate and interact with city employees via the Internet. As for ordinary people, they can access to government affairs, learn about concerned information and express their attitudes toward government. Moreover, government work such as permanent residence registration, careers guidance can be done via

2484-561: The effective usage of information and communication technologies for development (also known as "ICT4D") suggests that big data technology can make important contributions but also present unique challenges to international development . Advancements in big data analysis offer cost-effective opportunities to improve decision-making in critical development areas such as health care, employment, economic productivity , crime, security, and natural disaster and resource management. Additionally, user-generated data offers new opportunities to give

2553-485: The entire organization. Relational database management systems and desktop statistical software packages used to visualize data often have difficulty processing and analyzing big data. The processing and analysis of big data may require "massively parallel software running on tens, hundreds, or even thousands of servers". What qualifies as "big data" varies depending on the capabilities of those analyzing it and their tools. Furthermore, expanding capabilities make big data

2622-650: The existing mode of production. With the help of mobile Internet technology, traditional manufacturers can install hardware and software on cars, household appliances, accessories, and other industrial products to achieve functions of remote control, automatic data acquisition and analysis, etc. "Internet + Finance" means that financial industries can apply internet technology to their service provision and product sale. For instance, clients can pay bills or transfer money from one account to another through internet. The number of Internet users has reached about 649 million in China, while

2691-612: The fraction of data inaccuracies increases with data volume growth." Human inspection at the big data scale is impossible and there is a desperate need in health service for intelligent tools for accuracy and believability control and handling of information missed. While extensive information in healthcare is now electronic, it fits under the big data umbrella as most is unstructured and difficult to use. The use of big data in healthcare has raised significant ethical challenges ranging from risks for individual rights, privacy and autonomy , to transparency and trust. Big data in health research

2760-513: The fundamental structure of massive data sets and in 2008 the technology went public with the launch of a company called "Ayasdi". The practitioners of big data analytics processes are generally hostile to slower shared storage, preferring direct-attached storage ( DAS ) in its various forms from solid state drive ( SSD ) to high capacity SATA disk buried inside parallel processing nodes. The perception of shared storage architectures— storage area network (SAN) and network-attached storage (NAS)—

2829-484: The general public to make innovations or start their own business. Moreover, according to the official statement, the plan exerts a profound influence on adapting to information economy, rebuilding innovation system, intriguing creativity, cultivating emerging industry and public service pattern. A first challenge to the Internet Plus plan is that, precisely, if it’s government-powered in China, it means going through all

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2898-555: The global data volume was predicted to grow exponentially from 4.4 zettabytes to 44 zettabytes between 2013 and 2020. By 2025, IDC predicts there will be 163 zettabytes of data. According to IDC, global spending on big data and business analytics (BDA) solutions is estimated to reach $ 215.7 billion in 2021. While Statista report, the global big data market is forecasted to grow to $ 103 billion by 2027. In 2011 McKinsey & Company reported, if US healthcare were to use big data creatively and effectively to drive efficiency and quality,

2967-747: The globally stored information is in the form of alphanumeric text and still image data, which is the format most useful for most big data applications. This also shows the potential of yet unused data (i.e. in the form of video and audio content). While many vendors offer off-the-shelf products for big data, experts promote the development of in-house custom-tailored systems if the company has sufficient technical capabilities. The use and adoption of big data within governmental processes allows efficiencies in terms of cost, productivity, and innovation, but comes with flaws. Data analysis often requires multiple parts of government (central and local) to work in collaboration and create new and innovative processes to deliver

3036-405: The guarantees and capabilities made by Codd's relational model ." In a comparative study of big datasets, Kitchin and McArdle found that none of the commonly considered characteristics of big data appear consistently across all of the analyzed cases. For this reason, other studies identified the redefinition of power dynamics in knowledge discovery as the defining trait. Instead of focusing on

3105-411: The internet to upgrade China's economy . The State Council provided support for Internet Plus through policy support in area including cross-border e-commerce and rural e-commerce. Various regulatory bodies promoted Internet Plus within their sectors. "Internet + Manufacturing industry" means that the traditional manufacturing enterprises can adopt information and communication technologies to reform

3174-505: The internet. "Internet + Agriculture" makes it possible to precisely know the climate, the land and all the other large data analysis for agricultural purposes. In addition, the farmers can use the Internet to acquire updated information about the price and the demand for their production. Apart from Chinese government’s goal of upgrading China into a "powerful industrial country", the "Internet Plus" strategy will, most importantly, produce new economic forms and create suitable environment for

3243-556: The intrinsic characteristics of big data, this alternative perspective pushes forward a relational understanding of the object claiming that what matters is the way in which data is collected, stored, made available and analyzed. The growing maturity of the concept more starkly delineates the difference between "big data" and " business intelligence ": Big data can be described by the following characteristics: Other possible characteristics of big data are: Big data repositories have existed in many forms, often built by corporations with

3312-462: The labor market and the digital economy in Latin America, Hilbert and colleagues argue that digital trace data has several benefits such as: At the same time, working with digital trace data instead of traditional survey data does not eliminate the traditional challenges involved when working in the field of international quantitative analysis. Priorities change, but the basic discussions remain

3381-644: The ladder of central, provincial and local barons. Another argument from the South China Morning Post edited in Hong Kong writes that "Beijing needs to address censorship before any new strategy can be expected to have an impact", adding that "we all know the key thing about the internet is freedom. If Beijing misses the point and continues to censor access to information, Premier Li’s new Internet Plus strategy will probably just get more Chinese to shop online rather than have any significant and long-term impact on

3450-702: The main components and ecosystem of big data as follows: Multidimensional big data can also be represented as OLAP data cubes or, mathematically, tensors . Array database systems have set out to provide storage and high-level query support on this data type. Additional technologies being applied to big data include efficient tensor-based computation, such as multilinear subspace learning , massively parallel-processing ( MPP ) databases, search-based applications , data mining , distributed file systems , distributed cache (e.g., burst buffer and Memcached ), distributed databases , cloud and HPC-based infrastructure (applications, storage and computing resources), and

3519-516: The map-reduce architectures usually meant by the current "big data" movement. In 2004, Google published a paper on a process called MapReduce that uses a similar architecture. The MapReduce concept provides a parallel processing model, and an associated implementation was released to process huge amounts of data. With MapReduce, queries are split and distributed across parallel nodes and processed in parallel (the "map" step). The results are then gathered and delivered (the "reduce" step). The framework

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3588-461: The medical current problems of the general public in China. Specifically, Internet plus will optimize the traditional mode of treatment for patients with one-stop health management services. Through the Internet, the patient’s medical data can be obtained from the mobile terminal to monitor their own health data. "Internet + Government" (also known as Internet government , digital government , online government and connected government ) consists of

3657-419: The middle class, which means more people became more literate, which in turn led to information growth. The world's effective capacity to exchange information through telecommunication networks was 281 petabytes in 1986, 471 petabytes in 1993, 2.2 exabytes in 2000, 65 exabytes in 2007 and predictions put the amount of internet traffic at 667 exabytes annually by 2014. According to one estimate, one-third of

3726-432: The next level of performance. A McKinsey Global Institute study found a shortage of 1.5 million highly trained data professionals and managers and a number of universities including University of Tennessee and UC Berkeley , have created masters programs to meet this demand. Private boot camps have also developed programs to meet that demand, including paid programs like The Data Incubator or General Assembly . In

3795-651: The particular problem at hand, reshaping data in the best possible manner as they develop the solution. In 2004, LexisNexis acquired Seisint Inc. and their high-speed parallel processing platform and successfully used this platform to integrate the data systems of Choicepoint Inc. when they acquired that company in 2008. In 2011, the HPCC systems platform was open-sourced under the Apache v2.0 License. CERN and other physics experiments have collected big data sets for many decades, usually analyzed via high-throughput computing rather than

3864-411: The processing power transparent to the end-user by using a front-end application server. The data lake allows an organization to shift its focus from centralized control to a shared model to respond to the changing dynamics of information management. This enables quick segregation of data into the data lake, thereby reducing the overhead time. A 2011 McKinsey Global Institute report characterizes

3933-708: The production of statistics and its quality. There have been three Big Data Meets Survey Science (BigSurv) conferences in 2018, 2020 (virtual), 2023, and as of 2023 one conference forthcoming in 2025, a special issue in the Social Science Computer Review , a special issue in Journal of the Royal Statistical Society , and a special issue in EP J Data Science , and a book called Big Data Meets Social Sciences edited by Craig Hill and five other Fellows of

4002-505: The purpose of marketing. The increasingly digital world of rapid datafication makes this idea relevant to marketing because the amount of data constantly grows exponentially. It is predicted to increase from 44 to 163 zettabytes within the span of five years. The size of big data can often be difficult to navigate for marketers. As a result, adopters of big data may find themselves at a disadvantage. Algorithmic findings can be difficult to achieve with such large datasets. Big data in marketing

4071-399: The qualities of big data in volume, variety, velocity, veracity, and value. Variability is often included as an additional quality of big data. A 2018 definition states "Big data is where parallel computing tools are needed to handle data", and notes, "This represents a distinct and clearly defined change in the computer science used, via parallel programming theories, and losses of some of

4140-404: The rising of business startups indicate that the internet is not only a tool but a platform that can be combined with traditional industries. In the 2011 Two Sessions Work Report, Premier Wen Jiabao announced support for e-commerce in China , describing it as a mechanism to expand domestic consumption. Emphasis on e-commerce was later incorporated into Internet Plus. Chinese entrepreneurs in

4209-908: The same time), portfolio management (optimizing over an increasingly large array of financial instruments, potentially selected from different asset classes), risk management (credit rating based on extended information), and any other aspect where the data inputs are large. Big Data has also been a typical concept within the field of alternative financial service . Some of the major areas involve crowd-funding platforms and crypto currency exchanges. Big data analytics has been used in healthcare in providing personalized medicine and prescriptive analytics , clinical risk intervention and predictive analytics, waste and care variability reduction, automated external and internal reporting of patient data, standardized medical terms and patient registries. Some areas of improvement are more aspirational than actually implemented. The level of data generated within healthcare systems

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4278-456: The same. Among the main challenges are: Big Data is being rapidly adopted in Finance to 1) speed up processing and 2) deliver better, more informed inferences, both internally and to the clients of the financial institutions. The financial applications of Big Data range from investing decisions and trading (processing volumes of available price data, limit order books, economic data and more, all at

4347-449: The sector could create more than $ 300 billion in value every year. In the developed economies of Europe, government administrators could save more than €100 billion ($ 149 billion) in operational efficiency improvements alone by using big data. And users of services enabled by personal-location data could capture $ 600 billion in consumer surplus. One question for large enterprises is determining who should own big-data initiatives that affect

4416-592: The specific field of marketing, one of the problems stressed by Wedel and Kannan is that marketing has several sub domains (e.g., advertising, promotions, product development, branding) that all use different types of data. To understand how the media uses big data, it is first necessary to provide some context into the mechanism used for media process. It has been suggested by Nick Couldry and Joseph Turow that practitioners in media and advertising approach big data as many actionable points of information about millions of individuals. The industry appears to be moving away from

4485-588: The traditional approach of using specific media environments such as newspapers, magazines, or television shows and instead taps into consumers with technologies that reach targeted people at optimal times in optimal locations. The ultimate aim is to serve or convey, a message or content that is (statistically speaking) in line with the consumer's mindset. For example, publishing environments are increasingly tailoring messages (advertisements) and content (articles) to appeal to consumers that have been exclusively gleaned through various data-mining activities. Channel 4 ,

4554-808: The unheard a voice. However, longstanding challenges for developing regions such as inadequate technological infrastructure and economic and human resource scarcity exacerbate existing concerns with big data such as privacy, imperfect methodology, and interoperability issues. The challenge of "big data for development" is currently evolving toward the application of this data through machine learning, known as "artificial intelligence for development (AI4D). A major practical application of big data for development has been "fighting poverty with data". In 2015, Blumenstock and colleagues estimated predicted poverty and wealth from mobile phone metadata and in 2016 Jean and colleagues combined satellite imagery and machine learning to predict poverty. Using digital trace data to study

4623-492: The whole of the system rather than from isolated pockets of data. Compared to survey -based data collection, big data has low cost per data point, applies analysis techniques via machine learning and data mining , and includes diverse and new data sources, e.g., registers, social media, apps, and other forms digital data. Since 2018, survey scientists have started to examine how big data and survey science can complement each other to allow researchers and practitioners to improve

4692-455: Was very successful, so others wanted to replicate the algorithm. Therefore, an implementation of the MapReduce framework was adopted by an Apache open-source project named " Hadoop ". Apache Spark was developed in 2012 in response to limitations in the MapReduce paradigm, as it adds in-memory processing and the ability to set up many operations (not just map followed by reducing). MIKE2.0

4761-429: Was worth more than $ 100 billion and was growing at almost 10 percent a year, about twice as fast as the software business as a whole. Developed economies increasingly use data-intensive technologies. There are 4.6 billion mobile-phone subscriptions worldwide, and between 1 billion and 2 billion people accessing the internet. Between 1990 and 2005, more than 1 billion people worldwide entered

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