Five trends in the processing and development of large data in the future

In recent years, large numbers have become the driving force behind the growth of our digital life from popular words and concepts that are unique to big companies. Here are five trends in the processing and development of large data in the future.

1. Increasing popularity of data science

With the popularity of these web-based educational platforms, such as Coursera, Udacity, and edx, more and more people can learn all the knowledge, from basic statistical knowledge to natural language processing and machine learning, without spending a penny. In addition to this, oxdata and integration of the R language after the introduction of the analysis products, quid is doing with the machine learning and artificial intelligence concept of the tool also designed a fool-type use of interface and image specific user display methods. More companies like Kaggle have launched a crowdsourcing platform for forecasting models. So one of the trends in the processing of large data is that, like Datahero,infogram and statwing, the analysis of data becomes easy to use, the public.

2.Hadoop's reliance on MapReduce is getting smaller.

The era of the Hadoop platform for MapReduce Services officially ended with the 2.0 version of Hadoop. The products and services supported by the new version will be the same as the Cloudera Impala using an SQL query engine, or some other way to replace MapReduce. HBase NoSQL Database is a good example of Hadoop leaving MapReduce constraints. Large web companies, such as Facebook and ebay, have used hbase to deal with transactional applications.

3. More and more large data are being used in applications around us

The first is that large data applications are becoming less demanding for our developers, and sometimes developing large data applications is like adding a few lines to your application's code, or writing a script. Second, the scope of application of large data has been expanded, user habits analysis, network security, artificial intelligence, after-sales service, etc. can be made by large data processing products or applications to achieve. Now the big data technology has been brought into many networks and mobile applications, from shopping recommendations to finding people with their own connections and so on.

4. Machine learning is everywhere

It's easy to see the growing popularity of machine learning, from small applications around us prismatic, Summly, Trifacta, CloudFlare, Twitter, Google, Facebook, bidgely, Healthrageous, Predilytics, BloomReach, Datapop, Gravity ... It's hard to imagine a technology company with no machine learning technology can survive. Heck, even Microsoft, has a big stake in machine learning. It will become an important source of revenue.

5. Mobile phone will become an artificial intelligence data source

The application of our mobile phones and mobile phones may now be the largest source of private information. Through machine learning, speech recognition and other techniques, these applications can know where we go, who our friends are, what reminders are on our calendars, and what we surf the Internet. Through a new generation of personal assistant applications (Siri,saga and Google Now) our phones are more able to understand our comments, know where we often go, what we usually eat, how much time we have at home, work and outing, and so on.