Hello, everyone!
This post mainly describes the big data opportunities and challenges we face in the age of big data.
Traditional Data Processing Are Facing Great Challenges
Challenge 1: Few Business Departments Have Clear Big Data Requirements
Many enterprise business departments have no idea about the values and application scenarios of big data, and therefore have no accurate requirements for big data. In addition, the enterprise decision-makers are worried that establishing a big data department may yield little profits and therefore even delete a large amount of historical data with potential values.
Challenge 2: Data Silos Within Enterprises
The greatest challenge for enterprises to implement the big data strategy is that different types of data are scattered in different departments. As a result, data in the same enterprise cannot be efficiently shared, and the value of big data cannot be brought into full play.
Challenge 3: Poor Data Availability and Quality
Many large- and medium-sized enterprises generate large volumes of data every day.
However, many of them fails to pay enough attention to data preprocessing. As a result, data is not processed in a standard way. In the big data preprocessing phase, data needs to be extracted and converted into data types that can be easily processed, and cleaned by removing noisy data. According to Sybase, with the availability of high-quality data improved by 10%, the profits of enterprises would be improved by 20% consequently...
Challenge 4: Unsatisfactory Data Management Technologies and Architecture
Traditional databases are not suitable for processing PB-scale data.
It is difficult for traditional database systems to process semi-structured and unstructured data.
The O&M of massive volumes of data requires data stability, high concurrency, and server load reduction.
Challenge 5: Data Security Risks
A rapid spread of the Internet increases the chance of breaching the privacy of individuals and also leads to more crime methods that are difficult to be tracked and prevented.
It is a key issue to ensure user information security in this big data era. In addition, the increasing amount of big data poses higher requirements on the physical security of data storage, and therefore higher requirements on multi-copy and DR mechanisms.
Challenge 6: Lack of Big Data Talent
Each step of big data construction must be completed by professionals. Therefore, it is necessary to develop a professional team that understands big data, knows much about administration, and has experience in big data applications. Hundreds of thousands of big data–related jobs are added each year around the world. In the future, there will be a big data talent gap of more than 1 million. Therefore, universities and enterprises make join efforts to explore and develop big data talent.
Challenge 7: Trade-off Between Data Openness and Privacy
As big data applications become increasingly important, data resource openness and sharing have become the key to maintaining advantages against competitors. However, opening up data inevitably risks exposing some users' private information. Hence, it is a major challenge in this big data era to effectively protect citizens' and enterprises' privacy while promoting data openness, application, and sharing, and gradually strengthening privacy legislation.
Standing Out in the Competition Using Big Data
Big data can bring a huge commercial value, and it is believed to raise a revolution that is well-matched with the computer revolution in 20th century. Big data is affecting commercial and economic fields and so on. It boosts a new blue ocean and hastens generation of new economic growth points, becoming a focus during the competition among enterprises.
Opportunity 1: Big Data Mining Becomes the Core of Business Analysis
The focus of big data has gradually shifted from storage and transmission to data mining and application, which will have a profound impact on enterprises' business models. Big data can directly bring enterprises profits and incomparable competitive advantages through positive feedback.
On the one hand, big data technologies can effectively help enterprises integrate, mine, and analyze the large volumes of data they have, build a systematic data system, and improve the enterprise structure and management mechanism.
On the other hand, with the increase of personalized requirements of consumers, big data is gradually applied in a wide range of fields and is shifting the development paths and business models of most enterprises.
Opportunity 2: Big Data Bolsters the Application of Information Technologies
Big data processing and analysis is a support point of application of next-generation information technologies.
Mobile Internet, IoT, social networking, digital home, and e-commerce are the application forms of next-generation information technologies. These technologies continuously aggregate generated information and process, analyze, and optimize data from different sources in a unified and comprehensive manner, feedback or cross-feedback of results to various applications further improves user experience and creates huge business, economic, and social values.
Big data has the power to drive social transformation. However, to unleash this power, stricter data governance, insightful data analysis, and an environment that stimulates management innovation are required.
Opportunity 3: Big Data Is a New Engine for Continuous Growth of the Information Industry
Big data, with its tremendous business value and market demands, becomes a new engine that drives the continuous growth of the information industry.
With the increasing recognition of big data’s value by industry users, market requirements will burst, and new technologies, products, services, and business models will emerge continuously in the big data market.
Big data drives the development of a new market with high growth for the information industry: In the field of hardware and integrated devices, big data faces challenges such as effective storage, fast read/write, and real-time analysis. This will have an important impact on the chip and storage industry and also give rise to the market of integrated data storage and processing servers and in-memory computing. In the software and service field, the value of big data brings urgent requirements for quick data processing and analysis, which will lead to unprecedented prosperity of the data mining and business intelligence markets.
That's all, thanks!
