With the continuous development of the Internet, big data technology has been widely used in various channels. Today, Changping Beida Jade Bird will understand the practical operation of big data analysis and big data application through case analysis. A trend of big data analysis in the past few months is that more and more attention is paid to using artificial intelligence (in different forms and styles) to help analyze large-scale data and gain predictive insight.

In fact, the recently revived AI is largely a product of big data. The algorithm behind deep learning (the AI field that has attracted much attention recently) was basically born decades ago, but it didn't show great potential until it could be applied to large-scale data cheaply and quickly. AI is so closely related to big data that experts in the industry now think that AI has "wearily fallen in love with big data".

But in turn, artificial intelligence is now helping big data realize the promise of the latter. Analyzing the increasing attention to AI/ machine learning is also in line with the next evolution trend of big data: now I have all the data, but what insights can I get from it? Of course, this matter can be solved by data scientists. From the beginning, their role is to realize machine learning, otherwise they have to come up with models to discover the meaning of data. However, machine intelligence is gradually playing an auxiliary role for data scientists-only by dumping data can emerging products extract mathematical formulas (such as ContextRelevant) or automatically establish and recommend data science models (such as DataRobot) that may return good results. A new batch of products provided by AI companies can automatically identify complex entities like images (such as Clarifai and Dextro) or provide powerful predictive analysis (such as HyperScience).

At the same time, with the spread and improvement of products based on unsupervised learning, it will be very interesting to see how the relationship between them and data scientists evolves-will they be enemies or friends in the future? Of course, AI will not replace the position of data scientist soon, but it is expected to see that the simpler tasks that data scientists usually perform become more and more automated, which can greatly improve productivity.

But in any case, AI/ machine learning is by no means a trend worthy of attention in big data analysis. The universal maturity of big data BI platform and its increasing real-time capability are also an exciting trend (such as SiSense, ArcadiaData, etc.). ).