译文 : 2017年的6个大数据趋势

1. 将会推出更多的分析工具

随着数据量的不断增长，数据分析方法也将进一步提高。虽然SQL依然会是数据分析的标准方法，但是新兴分析工具也不可小觑。Spark是其中之一，它是大数据时代下的一个快速处理数据分析工作的框架，多家世界顶级的数据企业例如Google，Facebook等现已纷纷转向Spark框架。

这些新兴分析工具操作简单，对用户没有任何编码知识要求。Microsoft和Salesforce都已经推出了新型分析工具，Microsoft R Server和Lightning CRM平台，非编码人员也可以创建应用程序来查看数据。

2.实时数据分析将获得更多关注

技术专家预测，2017年企业将需要实时数据分析工具，来帮助他们利用数据进行实时决策。实时计算一般都是针对海量数据进行的，一般要求为秒级。目前有几款数据分析工具可以提供实时访问数据，如Google Analytics和Clicky。

3.隐私问题将成最大挑战

高德纳资讯公司预测，到2018年，近50%的企业都将面临隐私泄露问题。事实上，欧盟实施新的隐私法规时，早已经预见到了这一点。大数据时代，解决用户隐私泄露问题，就是解决大数据发展与使用的问题。

4.人工智能将广泛应用

过去一年，我们亲眼见证了人工智能的爆发：无人驾驶汽车试驾成功、AlphaGo围棋获胜。随着人工智能技术日益成熟，未来公司企业将很大程度上依赖于这项技术。虚拟助手、机器人、智能顾问和自动驾驶汽车等多种技术都将得到广泛的应用。

5.认知技术将加速发展

认知技术是人工智能领域的产物，能完成以往只有人能够完成的任务。认知技术如下图所示，包括计算机视觉、机器学习、自然语言处理、机器人技术和语言识别技术等。

随着人工智能的发展，认知技术的重要性越来越受到人们的认可。只要人们认识到大数据和分析学之间的紧密联系，就会发现认知计算和分析学一样，都是企业发展不可或缺的技术。

6.“大”数据将不复存在

大数据的发展面临共享难度大、垄断程度高、融合能力差、应用价值低以及安全风险大等一系列制约因素。因此一些专家认为，数据的“量”已经不再是数据的重点了。与其一味地追求数据量，还不如好好研究如何提高手头数据的利用效率。

大数据将被分割成数据块，这将打破行业领域对信息流动的限制，通过对不同类型、不同领域数据的跨界集聚，极大地改变信息的生产、传播、加工和组织方式，进而给各个行业的创新发展带来新的驱动力，推动各个领域的彻底变革和再造。

英文原文

6 Big Data Predictions You Should Not Miss

Big data is getting bigger and bigger and more businesses are adopting it. Why not when it makes business faster and more efficient. Through big data, they can easily access information to help them create well-informed decisions. It surely has done a lot of benefits to companies but how about next year? How will big data affect businesses and industries in the coming years?

More analytic tools will emerge

As data volume grows, analytical methods will improve. SQL will still be the standard; however, there are emerging ways how big data is analyzed. One of them is Spark which is a good complementary tool for analysis. These tools will also be easier to use where users will be able to use them without any coding knowledge. Microsoft and Salesforce have already introduced these tools recently allowing non-coders to create apps to view data.

Real-time streaming insights will be the big winners

Tech experts predict that in 2017, business and organizations will want to use data to make real-time decisions using advanced analytic tools.

Privacy will be the greatest challenge

Gartner predicted that by 2018, almost 50 percent of businesses will face violations in business ethics in relation to big data. In fact, that is already anticipated when the European Union put into effect the new privacy regulation.

Autonomous agents will continue to thrive

As artificial intelligence becomes more sophisticated, companies will rely more on these things, which include virtual assistants, robots, smart advisers, and autonomous vehicles.

Cognitive technology will emerge

With the emergence of AI, cognitive computing will become a necessity. It will even become synonymous with analytics as businesses perceive the relationship and similarity between big data and analytics.

Big data will be gone

What it means here is that big data will be divided into chunks to make it more efficient and actionable. As some experts say, volume is not necessarily better where data is concerned. More so, a lot of companies don't really use up all those data they have access to. Therefore, instead of accumulating volume, companies should know how to efficiently use the data they have in their hands no matter what the size is by asking the right questions.

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