2014 Big data will have 12 trends: Hadoop and R language lead

Now, "Big data" has become one of the hottest words, more and more enterprises began to pay attention to and embrace large data, 2014 Big data will have more substantial progress, in which Hadoop and R language will be the protagonist.

"Big Data" has become one of the most frequently used technical hot words in the 2013. The corresponding market has also seen rapid growth in the year. Hadoop and its ecosystems, which are associated with large data, have become a common tool for data scientists from technologies that were previously used by very talented programmers and engineers. More and more companies are embracing large data technologies and introducing large data applications into production environments.

So how will the big data for 2014 be developed? Here are 12 predictions that big figures could draw next year.

1. People stop talking about big data and start giving it meaning

In the 2014, the attraction of "big data" as a technical hot word will dissipate, and people will pay more attention to the value of the big data itself. For example, Gainsight company is using large data analysis in its IaaS platform to provide the so-called "customer success management" service. Gainsight believes that in 2014, each cloud application provider will support large data at the back-end infrastructure.

2.Hadoop will turn from novelty to key component

Cloud environment is not the only place where large data technology can be used. In the 2014, Hadoop will move from data batching and storage to a general-purpose computing infrastructure, making it the core component of the enterprise Data architecture. This means that data analysis will continue to be the primary application of large data.

3. Enterprise mining customer data to obtain forward-looking

Companies are planning to take seriously the so-called digital "breadcrumbs" that their customers leave behind when interacting with product customer service and online customer service, and find valuable content. To achieve this, the ability to analyze data must be more of a barrier to the BI team and provide business value to the enterprise.

4. Big Data into marketing games

2014, data analysis and large data for marketing will also become a year, affecting advertising, product promotion and consumer behavior. Some of these key innovations are expected to occur during the World Cup and the Winter Olympics. \

5. Modern analysis is no longer just a matter of data scientists

It would be more important for analysts in various business sectors to engage in large data and data analysis than to hire data scientists with high salaries. This will depress the high salaries caused by data science skills.

6. Evolution from interconnection (Internet of Things) to IoT (Web of Things)

IEEE's professional branch believes that in the 2014, everything interconnected--recognizable objects seamlessly integrated into the information network--will give way to the real internet of things. The Internet of things will give full play to the ability of mobile devices and sensors to observe and monitor their surroundings, enhancing the synergy between objects in the real world and their web replicas.

The Internet of things will generate a lot of data related to the real world, which will require intelligent solutions to give connectivity, interconnection, and relevance between the real world and the corresponding digital world resources.

7. From large data to massive data

The size, speed, and type of data (volume, velocity and produced) will continue to grow exponentially in 2014, so a few simple analysis tools are needed to harness these "data floods".

"It is these 3 v that make big data a very difficult tiger to subdue," IEEE said. The technology world has not been able to keep up with the training of data scientists, the huge demand for easy-to-use tools for all walks of life, and the ability to convert data collected from industry to meaningful insights. The vast data age that has already emerged requires the adoption of new paradigms and practices in data management and analysis. Competition will begin in this field in 2014. ”

8.R language will replace traditional SAS solutions as mainstream

The analysis, based on the R programming language, is designed for statistical analysis of data scientists, which will become mainstream in the 2014 and gradually marginalize traditional programming environments such as SAS and SPSS.

More than 2 million users and 3 million of analysts are looking for a better solution. R language coincides with its time.

9.Hadoop enhanced real-time custom applications

Next year we will see a variety of interactive applications Web applications, mobile applications, social applications, such as the explosion, they are based on the Hadoop platform to build, real-time interaction with people, real-time Sql-on-hadoop database manufacturers Splice Machine co-founder and CEO Monte Zweben said.

"There will be a real-time, large data application platform in 2014," Zweben said. "We are no longer using today to analyze yesterday's data. You can analyze the data 5 minutes ago or even 1 minutes ago. An enterprise must have an interactive application for real-time decision-making. ”

10.Hadoop will get enterprise-class hardening

In the 2014, Hadoop will develop better in terms of security, operational management, resource management, and multiple replication to gain more trust in the business, Zweben said.

"All the things that businesses need, Hadoop is going to be there," he said. "And these large data platforms will become more standardized and standardized." I think that will be a big point. ”

11. By the end of 2014, at least one NoSQL company will be listed successfully

One of the most widely recognised signs of a large data platform's business is that at least a Hadoop or NoSQL provider will be successfully listed in 2014, and the President and CEO Larry Wamock of Gazzang, who provides security solutions for large data and cloud environments, has made such predictions.

12. The new analysis stack will appear

In the 2014, a new data and analysis stack will emerge with new solutions such as database, analytics, and virtualization, which can be a severe blow to traditional large database vendors. Traditional manufacturers will also respond to new solutions hastily pieced together.

(Responsible editor: The good of the Legacy)