The development of big data poses a challenge that cannot be ignored

Big data research is hot, but leveraging the value of data remains challenging. Today, we will take a detailed analysis of these challenges.

The speed at which big data is generated is alarming, and the fact that 90% of the available data has only just emerged in the last two years. Today we need to work hard to analyze big data to uncover insights that can be used to guide decision-making and strategic business transformation.

Big data applications have begun to work in areas such as improving products, improving service levels and customer service. Here's a set of numbers: Only 17% of companies have no plans to build big data projects, and more than 70% have already started using big data-including integrating it into their business, or as a test-water project. Data technology is maturing and more and more organizations are preparing to integrate it into the information management and analysis infrastructure.

However, the "big challenges" of the following big data also cannot be ignored.

Find the language for communicating big data

All kinds of science, including chemistry and even mathematics, have been greatly promoted by the advent of a particular language. Obviously, we have to find a specific language that is equally worthy of being relied upon in big data, so that it can be better analyzed as well as using algebraic notation and the appropriate programming language.

Improve data reliability

As the amount of available data continues to grow, we must effectively differentiate between "signals" and "valuable information" in the "data". Unfortunately, there are still many companies that are struggling to find the ideal data and how to use it. This distinction between "junk data" and the quality of data is a key challenge.

Data access

Data access and connectivity are also a big hurdle. The McKinsey survey shows that there are still a large number of data points that fail to access the network, so companies often do not have the data platforms necessary to manage their overall business.

Bring more complex data into the door

If the initial stage of big data is struggling with "simple" data, such as digital tables and graphs, the data that needs to be processed today is becoming more complex: pictures, videos, and descriptions of physical and even living environments. Therefore, it is necessary to re-examine and build big data tools and architectures to capture, store and analyze diversity data.

Better integration of time variables

The time dimension is also an important challenge in the development of big data, that is, how to analyze long-term causal relationships, not just real-time data streams. Finally, this issue poses a challenge to the storage sector. We need to carefully choose to actually carry such a large amount of data storage.

IT architecture

The technological environment of the data world is rapidly evolving, so the ability to have valuable data is premised on partnering with technology partners with strong innovation capabilities to build the right IT infrastructure to efficiently adapt to changing factors.

Security

Last but not least, security is a problem. We need to use the corresponding identities of each member of the team for data access management, along with appropriate data encryption mechanisms to avoid potential risks.

The large-scale trend brought by big data technology also brings profound influence on science, economy and politics, and even deeply marks the development of mankind. Big data is challenging our analytical capabilities and the way we perceive the world. Therefore, in the face of change and continuous growth, we should also adhere to the principle of people-oriented, based on lean, with the times, uphold integrity and serve the whole world.

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The development of big data poses a challenge that cannot be ignored