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This article comes from: Zhihu column " FanRuan Data Application Research Institute " - data dry goods & information center!
Article introduction
1. Status Quo and Challenges of Big Data Industry
2. Development Goals for 2020
3. Key measures to achieve the goal
4. The Enlightenment of "Planning" to Enterprises
V. The Enlightenment of the "Plan" to Individuals
Since the Fifth Plenary Session of the 18th Central Committee of the Communist Party of China in 2015 put forward the "implementation of the national big data strategy", relevant state departments have intensively issued a number of opinions and plans for the development of big data. With the extension of various subdivisions, the development of big data has gradually moved from theoretical research to practical application. Among the many policy plans, the recently released "Big Data Industry Development Plan (2016-2020)" has the most extensive influence, and the attention is as high as 92.11. FanRuan Data Application Research Institute has the responsibility and obligation to make a contribution to the "Plan". Interpretation will help you understand the policy more deeply, seize the opportunity, and ride the ride of the policy dividend.
1. Status Quo and Challenges of Big Data Industry
At present, my country's informatization level is improving day by day, and China has accumulated rich data resources. my country has become one of the countries that generate and accumulate the largest amount of data and the most abundant data types. It has a good foundation and faces good development opportunities, but there are still some difficulties, problems and challenges, mainly in:
The degree of openness and sharing of data resources is low. The quality of data is not high, the circulation of data resources is not smooth, the management ability is weak, and the value of data is difficult to be effectively exploited and utilized.
Technological innovation and support capabilities are not strong. There is still a big gap between China and foreign countries in terms of new computing platforms, distributed computing architecture, big data processing, analysis and presentation, and its influence on open source technologies and related ecosystems is weak.
The application level of big data is not high. The development of big data in my country has a strong application market advantage, but there are still problems such as not wide application fields, not deep application levels, and insufficient understanding.
The support system of the big data industry is not yet perfect. Relevant laws and regulations such as data ownership and privacy rights, as well as information security, open sharing and other standards and norms are not sound, and a data openness, management and information security guarantee system that takes into account both security and development has not been established.
The construction of talent team urgently needs to be strengthened. There is a shortage of talents in basic research on big data, product development and business applications, making it difficult to meet development needs.
2. Development Goals for 2020
(1) Overall goal
By 2020, a big data industry system with advanced technology, prosperous applications and strong guarantees will be basically formed. The revenue of big data-related products and services has exceeded 1 trillion yuan, with an average annual compound growth rate of about 30%. It will accelerate the construction of a data-powerful country and provide strong industrial support for the realization of a manufacturing powerhouse and a network powerhouse.
(2) Sub-targets
1. Advanced and controllable technological products.
It has formed safe and controllable technology products in the aspects of big data basic software and hardware, has reached the international advanced level in the field of big data acquisition, storage management and processing platform technology, and is in a leading position in algorithms and tools such as data mining, analysis and application, and has formed a group of Independent innovation, advanced technology, products, solutions and services that meet major application needs.
2. The application ability is significantly enhanced.
The application of industrial big data fully supports intelligent manufacturing and industrial transformation and upgrading. Big data is widely and deeply applied in innovation and entrepreneurship, government management and people's livelihood services. The capabilities of technology integration, business integration and data integration have been significantly improved, enabling cross-level, cross-regional, and cross-border applications. System, cross-department and cross-business collaborative management and services form a new model of data-driven innovation and development.
3. Ecosystem flourishes and develops.
Form a number of big data backbone enterprises with outstanding innovation capabilities, cultivate a group of professional data service innovative small and medium-sized enterprises, cultivate 10 international leading big data core leading enterprises and 500 big data application and service enterprises. A relatively complete big data industry chain has been formed, and a big data industry system has been initially formed. Build 10-15 big data comprehensive pilot areas, create a group of big data industry clusters, and form several demonstration bases for new big data industrialization industries.
4. The support ability is continuously enhanced. Establish and improve a big data standard system covering technology, products and management.
Establish a group of regional and industry big data industry and application alliances and industry organizations. Cultivate a group of professional service institutions such as big data consulting and research, testing and evaluation, technology and intellectual property, investment and financing. Build 1-2 open source communities with standardized operation and certain international influence.
5. Strong data security guarantee.
The data security technology has reached the international advanced level. The national data security protection system has been basically established. The data security technical guarantee capability and guarantee system basically meet the needs of national strategies and market applications. The laws and regulations for data security and personal privacy protection are relatively complete.
3. Key measures to achieve the goal
On the basis of analyzing and summarizing the current situation and form of industrial development, the "Planning" specifically sets 7 key tasks and 8 key projects for the realization of the 2020 goals, focusing on the keywords of "innovation, openness, sharing, application, collaboration, and system". As well as 5 aspects of safeguard measures, in order to facilitate reading and understanding, the author has made a decomposition process, see the following figure for details.
8个重点工程：围绕重点任务，设置了大数据关键技术及产品研发与产业化、大数据服务能力提升、工业大数据创新发展、跨行业大数据应用推进、大数据产业集聚区创建、大数据重点标准研制及应用示范、大数据公共服务体系建设、大数据安全保障八个工程，作为工作抓手重点推进。
5个方面保障措施：大数据涉及面广，对跨层级、跨部门的协调要求高，同时需要法律法规、政策、人才以及国际合作等多层面支持，提出推进体制机制创新、健全相关政策法规制度、加大政策扶持力度、建设多层次人才队伍、推动大数据国际化发展五个方面的保障措施。
四、《规划》对企业的启示
好风凭借力，送我上青天。大数据企业需要充分利用政策红利，积极响应国家的号召和导向，既要不断通过技术创新，提升产品竞争力，也需要从业务切入，以国家战略、市场需求为牵引，提供行业应用解决方案，更需要响应开放共享，利用互联网共创思维实现企业快速发展，从而打造一流品牌，实现企业价值和利益。
1、把握先入优势
无数案例验证了行业先入者优势，英特尔首席执行官Andrew Grove曾说，当企业有了技术突破或其他根本性改变时，机会就来了，抓住机会。在这一行业，先入者而且只有先入者，也就是在别人犹豫不决时就果断采取行动的企业，才真正有机会赢得时间，超过其他竞争对手。在这个市场里，时间优势是获得市场份额的最可靠的办法。虽然国外产品比国产更好，但是鉴于中国特殊情况和本次战略时间窗口，国外厂商想形成垄断几无可能，这正是中国厂商的机会，凭借本土优势还是很容易成长为各个细分领域的领导者。
2、持续技术创新
创新是动态发展的，如果进行一次技术创新之后不再进一步开拓进取，而是坐享原来的结果，必然会陷入困境，原有的先入优势和客户忠诚度将消耗殆尽。综合来看，企业创新的驱动力主要有以下四个方面：
企业领导自身的内驱力；
企业外界的外界压力，如行业内部各企业之间的竞争方式、市场竞争的激烈程度、市场策略等；
技术和社会文化的影响力，如本地区社会发展状况、企业文化、企业员工素质等；
目标市场和预期利润的吸引力，即企业有没有梦想有没有拼劲；
3、创建生态优势
进入互联网和大数据时代，产业环境、消费者需求发生了巨大的变化，一是整合性需求的提高，用户不再满足于单一产品功能，而是希望企业交付一览的的个性化解决方案；二是行业跨界增加了竞争的不确定性，黑天鹅乱飞的年代，谁也想不到将来竞争对手会是谁。所以企业必须学会构建生态，创建生态优势。
这里的生态是指企业、个人在相互依赖和互惠的基础上形成共生、互生和再生的价值系统，实质上是规模经济的逻辑延伸，在产品获服务的创造层面让更多的人参与，让事业目标链接更多的人。个人消费者领域，苹果公司与开发者、app与ios系统就是一个共赢共生的生态；大数据BI领域，帆软公司与开发者联盟、问题互助团队、文档团队等也是共创共赢的生态。生态优势的背后假定不再是零和博弈，它强调共赢，追求“为我所用”，做到你中有我，互惠互利。
五、《规划》对个人的启示
《规划》已明确指出，大数据基础研究、产品研发和业务应用等各类人才短缺，难以满足发展需要。《2017年中国大数据发展报告》调查中显示，高端综合型人才短缺问题日益突出，问题主要有：
我国大数据从出现到广泛应用历时较短，从业者经验不足，对大数据的认知和分析思维相对滞后
岗位供需不平衡，数据分析、系统研发等技术类岗位大多供不应求，项目管理类求职人数占比远远高于招聘需求
学历层次错位明显，低学历的招聘需求高于求助数量占比，高学历则供不应求
二三线大数据行业发展较好的城市，如南京、大连、贵阳等人才供给相对不足；
机会留给有准备的人，我们要顺时顺势。网络和付费知识的发展，让我们可以不受时间、金钱、地域的限制学到最新知识，但要成为好的数据科学家，还需要做到以下3点。
1、训练多模式思维
现实生活中一件事往往有多种解决方案，最佳解决方案会是不同的想法和解决思路碰撞的结晶，而这些想法和解决思路的来源往往也不尽相同。一个企业会从各种渠道收集信息，我们需要学习在每个渠道中提取有用的数据信息进行分析，再把这些分析结合到一起去，从而找出最佳解决方案。
2、把工作当成职责
兴趣是最好的老师，如果你愿意并喜欢大数据行业，那么就不仅要把工作当成谋生的手段，还是你的一个习惯和职责。你要习惯于用探索数据的方式来看待周围的世界，比如有人想听你对于数据如何改变生活的看法，那么你就应该用具体的数据和例子来支持你的观点，甚至用创造性的可视化信息展示。
3、扩展交际圈
在商业上，扩展人脉一直很重要，所以下班后多多出去看看吧。如果你想成为大数据领域内的专家，你应该多接触这个领域内的人。多去参加那些关于大数据的论坛、讲座等活动，多关注一些关于大数据的社交媒体账号。如果你的熟人在一家优秀的大数据公司工作，当他们有职位空缺时，他们会想到你。这便是扩展交际圈带来的好处之一。