003 大数据十大趋势/预测-2019 年为何选大数据

003 Top 10 Big Data Trends/Predictions – Why to Choose Big Data for 2019

Everyone is running behind big data these days. Professionals from varied spheres are adoring 21st-century data science. Big Data has been an ambivalent word in the IT industry for some time, but this will change in 2019. Let’s see Big Data Trends of 2019 to understand the big picture of big data.

这些天大家都在大数据后面跑.来自不同领域的专业人士都热爱 21 世纪的数据科学.大数据一段时间以来，在 IT 行业一直是一个矛盾的词，但这将在 2019年发生变化.让我们看看 2019年的大数据趋势，了解大数据的全貌.

Gartner found in a survey that about** 48% of companies invested in big data** in 2016. Nearly three-quarters of those surveyed have already invested or planned to invest in 2019.

Gartner 在一项调查中发现,大数据投资企业占比 48%2016年.在接受调查的人中，有近三个季度已经或计划在 2019年投资.

So, let’s explore top Big Data Trends.

所以，让我们来探索大数据的趋势.

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Big Picture of Big Data – Top 10 Big Data Trends

Today, different sectors like marketing and pharmaceutical companies use data-driven decisions. Algorithms influence by information about shopping habits, which we use for engineering in both formula 1 vehicles & asthma drugs.

如今，像营销和制药公司这样的不同行业使用数据驱动的决策.算法受购物习惯信息的影响，我们在 f1 车辆和哮喘药物中使用这些信息进行工程.

But has Big Data reached its peak or is there more potential to explore? Here are the** top 10 Big Data predictions** for 2019 by different Big Data experts. It will help you in knowing Big Data Trends in 2019. It will also help you in understanding top Big Data technologies and salary along with other Big Data 2019 trends. Looking to compare different Big Data technologies follow this comparison guide.

但是有大数据达到顶峰，还是有更多的潜力去探索？以下是十大大数据预测不同的大数据专家为 2019.它将帮助您了解 2019年的大数据趋势.它还将帮助您了解顶级大数据技术和薪酬以及其他大数据 2019 趋势.对比不同的大数据技术遵循这个比较指南.

1. Latest Big Data Trends for 2019

1. 最新大数据趋势 2019

• A proliferation of data

• Increasing Streaming Analytics via Apache Flink and Spark Streaming

• Increasing Data Analytics

• Hadoop at its Best

• Increasing Focus on Cloud-Based Data Analytics

• More Demand for Big data and Analytical Skills

• Hike in Salaries for Big Data Specialists and Data Scientists

• Improving Customer Experience

• Increasing Monetization

• Achieving Maximum Business Intelligence with Data Virtualization

• 数据的激增

• 通过 Apache Flink 和 Spark Streaming 增加流分析

• 增加数据分析

• 最好的 Hadoop

• 更加关注基于云的数据分析

• 对大数据和分析技能的需求增加

• 大数据专家和数据科学家的工资上涨

• 改善客户体验

• 增加货币化

• 通过数据虚拟化实现最大的商业智能

i. Proliferation of data

I. 的数据

The most obvious big data prediction for 2019 is that there will be more of data that will be analyzed to gain valuable insight. Forrester declares that ‘all companies are in the data business now’.

最明显的大数据2019 的预测是，为了获得有价值的洞察力，将会有更多的数据被分析.弗雷斯特宣称现在所有的公司都在做数据业务”.

The increasing number of individuals mostly using internet shows that there is more opportunity than ever before to create and collect data. By 2020, this data that is worth analyzing is predicted to double. By empowering the organization to make data-driven decisions at a high speed, IT will soon become the data hero who helps in shaping the future of the business. – “Francois Ajenstat, Chief Product Officer at Tableau”

越来越多的人主要使用互联网，这表明创建和收集数据的机会比以往任何时候都多.通过 2020，这个值得分析的数据被预测会翻倍.通过授权组织高速做出数据驱动的决策，它将很快成为帮助塑造业务未来的数据英雄.-“Tableau 首席产品官 Francois Ajenstat”

ii. Increasing Streaming Analytics via Apache Flink and Spark Streaming

Ii.通过 Apache Flink 和 Spark Streaming 增加流分析

Analytics will experience a revolution in 2019. In 2019, streaming analytics is predicted to become a default enterprise capability, and there will be widespread enterprise adoption and implementation of this technology to help companies gain a competitive advantage from their data.

分析将在 2019年经历一场革命.在 2019 中，流分析预计将成为默认的企业能力，企业将广泛采用和实施这种技术，以帮助公司从数据中获得竞争优势.

In terms of the technologies to achieve this, there will be an acceleration in the usage of open sources streaming engines, such as Spark Streaming and Apache Flink, in tight integration with Hadoop Data Lake which will provide easier approaches in leveraging open source in the enterprise. – “Anand Venugopal, Head of Product, StreamAnalytix, Impetus Technologies”

就实现这一目标的技术而言，开源流媒体引擎的使用将会加速，例如火花流和Apache Flink的紧密集成,Hadoop数据湖，它将为企业利用开源提供更简单的方法.-“阿南 Venugopal，头，StreamAnalytix，推动技术”

iii. Increasing Data Analytics

Iii.增加数据分析

Interconnected devices are projected to hit 34 billion in 2020. More businesses will start exploring and exploiting their benefits to fulfill various business objectives. Big data is invaluable to marketers and the IoT add further value to it. Along with better targeting & personalizing the marketing messages, business will be able to create more useful products for their customers. That will help unleash the real potential of some of those new technologies like IoT, machine learning and AI – “Chuck Pieper, CEO, Cambridge Semantics”

预计 2020年互联设备将达到 340亿台.更多的企业将开始探索和利用他们的利益来实现各种业务目标.大数据对于营销人员和物联网为它增加更多的价值.随着营销信息的更好定位和个性化，企业将能够为客户创造更有用的产品.这将有助于释放物联网等新技术的真正潜力,机器学习与人工智能-“剑桥语义公司 CEO Chuck Pieper”

iv. Hadoop at its Best

四、最好的 Hadoop

2016 was not a good year for Hadoop and specifically for Hadoop distribution vendors. But in 2019, there is going to be an increased adoption of Hadoop. Hadoop will not replace other databases but it will be an essential part of data ingestion in the IoT / digital world. – “George Corugedo, CTO, RedPoint Global”

2016 不是一个好的一年Hadoop专门针对 Hadoop 分发供应商.但是在 2019年，Hadoop 的应用将会越来越多.Hadoop不会取代其他数据库，但它将是物联网/数字世界中数据接收的重要组成部分.-“RedPoint Global 首席技术官 George Corugedo”

v. Increasing Focus on Cloud-Based Data Analytics

五、对基于云的数据分析日益关注

As per Ashish Thusoo, CEO, Qubole, in 2018, enterprises are expected to move their big data projects to the cloud in droves. Moving data to the cloud intensifies adoption of the latest capabilities to turn data into action. It also enables cost cutting in on-going maintenance and operations. We expect that there will be more data on the cloud. This enables enterprises to select the analytics tools like Spark or Flink – “SnapLogic”.

根据阿希什 Thusoo 首席执行官 Qubole2018年，预计企业将把大数据项目云成群结队.将数据迁移到云，将会加速采用将数据转化为行动的最新功能.它还能够在持续的维护和运营中降低成本.我们预计云上会有更多的数据.这使得企业能够选择像火花或 Flink-“SnapLogic ”.

vi. More Demand for Big Data and Analytical Skills

六、对大数据和分析技能的需求增加

More and more organizations will be adopting Hadoop and other big data stores which will rapidly introduce new, innovative Hadoop solutions. For this, Businesses will hire more big data analytics to provide a better service to their customers and keep their competitive edge. This will open up capabilities for coders and data scientists that will be mind-blowing. – “Jeff Catlin, CEO, Lexalytics”.

越来越多的组织将采用 Hadoop 和其他大数据将迅速推出创新 Hadoop 解决方案的商店.为此，企业将雇佣更多的员工.大数据分析为客户提供更好的服务，保持竞争优势.这将为程序员和数据科学家这将是令人兴奋的.-“Lexalytics CEO 杰夫 · 凯特林”.

vii. Hike in Salaries for Big Data Specialists and Data Scientists

七、大数据专家和数据科学家的工资上涨

According to the McKinsey Global Institute, data scientists demand is growing by as much as 12 percent a year and there could be a shortage of as many as 250,000 data scientists by 2024 in US economy.

据麦肯锡全球研究院, 数据科学家需求每年增长高达 12%，到 2024年，美国经济可能会短缺多达 250,000 名数据科学家.

As per prediction by Robert half, Data Scientist salaries are predicted to range from 163,500 in 2018. This is an increase of about 6.4% over 2016 salary levels. Similarly, Big Data Engineer salaries are predicted to range from 196,000, increasing 5.8% over 2016 salary levels.

根据预测半罗伯特据预测，数据科学家的薪水在 2018年将从 116,000 美元到 163,500 美元不等.这比 6.4% 的工资水平增加了大约 2016.同样,大数据工程师的工资预计从 135,000 美元到 196,000 美元不等，比 5.8% 的工资水平增加了 2016.

viii. Improving Customer Experience

八、改善客户体验

Everything from social media, health monitors and taxi apps collect data from the user, to better understand customers. In order to improve top line revenue through cross-sell/upsell or reduce churn to remove the risk of lost revenue.

从社交媒体、健康监视器和出租车应用程序收集用户的数据，以更好地了解客户.为了通过交叉销售/追加销售或减少流失来提高顶级收入，以消除收入损失的风险.

This will have a transformative impact on the ability of a data-centric business in identifying new revenue streams, saving costs and improving their customer intimacy. – “Scott Gnau, Chief Technology Officer, Hortonworks”.

这将对以数据为中心的业务在识别新的收入流、节省成本和改善客户关系方面的能力产生变革性影响.-“Hortonworks 首席技术官 Scott Gnau”.

ix. Increasing Monetization

九、增加货币化

Many experts have predicted that the creation of the huge volume of data & its use will result in its monetization. *Michael Dell *predicted that big data analytics is the next trillion-dollar market. IDC predicts that data monetization efforts will result in enterprises increasing the marketplace’s consumption of their own data by 100-fold – or even more.

许多专家预测，大量数据的产生和使用将导致其货币化.戴尔迈克尔大数据分析是下一个万亿美元的市场.IDC据预测，数据货币化的努力将导致企业将自己的数据消费增加 100 倍甚至更多.

x. Achieving Maximum Business Intelligence With Data Virtualization

X.通过数据虚拟化实现最大的商业智能

Thus, Forrester expects that the number of firms will look to drive value and revenue from their ‘exhaust fumes’. IDC predicts that by 2020, organizations can analyze all available data to deliver actionable information. This information will gain an extra $430 billion in productivity benefits over their less analytically oriented peers.

因此，Forrester预计公司的数量将从他们的 “废气” 中推动价值和收入.IDC预测到 2020年，组织可以分析所有可用的数据，以提供可操作的信息.与那些不太注重分析的同行相比，这些信息将获得额外的 4300亿美元的生产力收益.

Regardless, business intelligence will no longer be considered a department but an attitude. At least for those who plan to be in business by 2019. – “Anthony Dina, Director Data Analytics, Dell EMC”.

不管怎样商业智能不再被认为是一个部门，而是一种态度.至少对于那些计划在 2019年前开业的人来说是这样.-“戴尔 EMC 数据分析总监 Anthony Dina ”.

2. Summary for Big Data Trends

2. 摘要大数据的趋势

Ultimately, it looks like big data will be bigger and bigger in 2019 as compared to 2016. So, patents for innovative products, huge growth in the generated data, & increasing customer demand shows that data will be the driving force behind many business decisions in 2019.

最终，与 2019年相比，2016年的大数据看起来会越来越大.因此，创新产品的专利、产生的数据的巨大增长以及不断增长的客户需求表明，数据将是 2019年许多商业决策的驱动力.

Big Data, Big Opportunities, Big Impact, Big Decision, Big Scope, Big Career, Big Salary….!!!

大数据、大机会、大影响、大决策、大范围、大事业、大薪酬……!!

Hence, this was all in top Big Data Trends. Still, if you have any query, ask through the comments tab.

因此，这都是大数据的主要趋势.尽管如此，如果你有任何查询，请通过 “评论” 选项卡询问.

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