译：2015年将变成大数据的黄金日期： Oracle’s的五大预测

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在互联网和“大数据”之前，Oracle’s是通过并行处理大数据类型从而加载数据库。与不断增长的的个人和业务数据相比，全球许多企业把他们的目光转向可以为企业带来价值和收益的数据。

Oracle的副总裁Neil Mendelson在负责大数据和先进的分析方法，仔细研究了他的办公室。当我们进一步发现Neil Mendelson先生提供了一些关于进化持有权威的数据从而进行数据趋势预测。

新的数据贸易语言

您只需要检查像谷歌这样的公司要理解数据带来的真正价值，Neil Mendelson先生断言。“当前市场关注品牌价值，未来趋势预计将转向数据。在最后的分析中，大型企业和小型企业它们所持有的数据将被分化给有信息的地方，事情和人。

所以根据这一点，以下是从Oracle中来进行的五大相关数据预测。

# 1：公司董事会将从大数据转移到数据资本：

数据金融资本有助于创新和创造新的产品、服务和流程。对于CEO（首席执行官）来说，这意味着更大的关注意味着数据资本的领先以及对访问数据提供流动性会感兴趣。

# 2：大数据管理的发展：

对关系数据库系统来说，NoSQL和Hadoop将从目前的实验进展到实践中的应用从而进行对业务数据管理,。年内，公司在早期多数会决定最好的角色分配给各种基本的组件和利用所有资源组成一个成熟的大数据管理系统架构。

# 3：对SQL的更大的需求：

企业将需求一个SQL从而适用于各种大数据，而不仅仅是在rdbms数据，NoSQL或Hadoop。SQL从上面的需求也将有类似的功能，SQL已经被应用到现代商业的开发人员和应用程序中了，对于SQL来说要求需要有成熟的技术。

# 4：IT的ETL转换：

提取、转换和加载(ETL)过程将被重新审查内存的能力。数据专家将喜欢实时数据复制方法在批量处理的标准。利用这种内存处理技术，将数据转换快速足以维持互动探索。

# 5：大数据将成为可视化和自助服务的工具：

数据可视化和和展示工具对于的企业内的专家是会有用的。新工具将合并消费者层面用户交互表面上支持复杂算法组织、调查和增强。这将使企业利用外部来源的数据从而审查和管理数据。因此，大数据将变得更容易探索。

英语原文：Why 2015 Will Be Year of Big Data: Oracle’s Five Predictions

Long before the Internet and the inception of “big data,” Oracle has been dealing with big datatype loads through parallel databases. With the growing supremacy of personal and business data globally, many of the world businesses have turned their eyes towards the possible gains to their bottom-line that said data could contribute.

This is what Neil Mendelson, a VP at Oracle in charge of Big Data and Advanced Analytics, has been poring over at his office. As we move further into the year, Mr. Mendelson offers some predictions held by the data authority regarding evolution of the data trends.

The new Trade Language of Data

“You need only examine companies like Google to understand the true worth that data brings,” Mr. Mendelson asserted. “Where the current market is focused on brand value, future trends are expected to shift towards data value. In the final analysis, businesses large and small will be differentiated by the data they hold – information about places, things and people.”

Bearing this in mind, below are the five top predictions relating to data from Oracle.

#1: Talk in corporate boardrooms will shift from big data to data capital

Data contributes just as much as financial capital to innovation and creation of new products, services and processes. For the CEO, this implies greater focus on means to access data capital ahead of the curve while the CIO would be interested in providing data liquidity.

#2: Growth of big data management

NoSQL and Hadoop will progress from their current experimental aviator positions to typical components within business data management, right along relational database systems. During the year, firms within the early majority will decide on the best roles to assign to various rudimentary components and utilize all three architectures to comprise a mature big data management system.

#3: Greater demand for an all-seasonal SQL

Enterprises will demand an SQL that works with every kind of big data, rather than just data within RDBMSs, NoSQL or Hadoop. There will also be demand for the SQL from above to have similar capabilities as the modern SQL which are already being used by the business’s developers and applications, requiring an overnight maturity on the technology behind the SQL.

#4: Transformation of ETL by JIT transformation Extract, transform and load processes (ETL) will be re-examined following the explosion of in-memory streaming capabilities. Data specialists will prefer real-time data replication methods over the batch-oriented ones that were the standard. Taking advantage of this in-memory processing technology, data transformation will be made quick enough to sustain interactive exploration.

#5: Big data will be characterized by visualization and self-service discovery tools

Technology resulting in the inception of data visualization and discovery tools will be useful to experts within the enterprise. The new tools will merge consumer level user interaction on the surface supported complex algorithm organization, investigation and enhancement behind the scenes. This will enable businesses utilize data from external sources according to internal scrutiny and governing data policies. As a result, big data will become much easier to explore.