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Безопасная магистраль на пути к Большим Данным

11 апреля 2013 Быстро развивающиеся технологии в совокупности с непрерывным потоком объемов данных несут угрозу для компаний, так как они должны быть настороже остаться позади конкурентов, инвестирующих первыми в новые технологии. Существует ли безопасный путь, следуя которому компании могут оптимизировать затраты, уменьшить риски и в то же время оставаться лидером среди инноваторов? Конечно, существует! Читайте брошюру компании Informatica на английском языке и узнайте, с какого угла подходить к работе с Большими Данными. (Материал опубликован на английском языке)
Risk: It’s the enemy of IT projects. Big data can make risk seem even bigger.

Emerging big data technologies coupled with huge spikes in data volumes, velocity, and variety put risk squarely in the spotlight, raising difficult questions of risk and reward. IT and business managers wary of spiraling costs and busted deadlines with conventional IT projects can be even more apprehensive about putting organizational resources and their own career track on the line without a proven path to big data value.

And indeed the risk in big data projects can be substantial, both in terms of project missteps if not the dreaded “epic fail,” as well as lost opportunities to deliver business value and competitive advantage.

Big data risk and cost can be minimized with the right approach and proven technology to address the bulk of big data work—integrating disparate and complex information from a growing array of sources. This white paper examines the risk and reward of big data and highlights how leading organizations are utilizing Informatica technology as a safe on-ramp to big data that reduces risk and cost while speeding insights and innovation.

Perceptions of Risk and Reward in Big Data

Big data has generated big interest for organizations in virtually every industry. Most enterprises recognize the need to cost-effectively manage growing volumes of big transaction data—the conventional information in onpremise and cloud enterprise applications, data warehouses, and storage environments.

The other flavor of big data—big interaction data—opens a new frontier for business opportunity. Innovative enterprises are already leveraging vast quantities of big interaction data from social media, machines and sensors, call detail records (CDRs), geospatial systems, the web, and other sources. By combining these new data types with conventional data, leaders are increasing customer retention and acquisition, increasing operational efficiencies, improving product and service delivery, and generating breakthrough results with new insights.

Yet a sizable number of organizations are taking a conservative wait-and-see approach to big data. An Informatica survey of 589 IT and business professionals found that 31 percent had no plans to pursue big data initiatives, at least in the near term.1 More than half (52 percent) of survey respondents identified a lack of maturity in big data tools as the top challenge in big data projects.

For instance, the open-source Hadoop framework lacks support for reusability and metadata, making it difficult to extend projects and ensure consistency. Emerging technologies such as Hadoop are still maturing with capabilities for data management and analytics in a heterogeneous environment, prompting some organizations to resort to manual scripting and introducing the risk that big data projects will end up as another data silo.

As shown in Figure 1, other key challenges cited by respondents including lack of support for real-time data and concerns over poor data quality, security, and privacy. The survey also reveals perceptions of risk in the limited availability of skilled developers to manage big data, and in potentially difficult and time-consuming development in Hadoop, NoSQL, and other new technologies.

Source:  informatica.com
The Safe On-Ramp to Big DataБрошюра компании Informatica на английском языке
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