A detailed explanation of the impact of large data on markets such as it

Large data is changing the way many companies and IT departments observe, store, and read data. But the technology is still in its infancy, and many companies are still looking for the right balance.

As successful companies tap into their data to get information, a range of seemingly random numbers of information becomes profit growth, and the ability to large data and manage large data has become a core competency in almost every industry.

But what does "big data" really mean? Is it some kind of charade or something? Simply put, the big data is the company-wide data that comes and goes into the company. Big data is growing.

IBM is one of the leading manufacturers in this emerging field. It estimates that every day a variety of sources generate a total of 2.5*109 bytes of data, including sensors, social media, and 1 billion of thousands of mobile devices worldwide. This makes it difficult for businesses to master and analyze data to improve competitiveness, efficiency, and profitability.

IDC estimates that the market for large data technology and services will grow by nearly 40% a year, to $16.9 billion trillion by 2015.

In addition, people send 1 billion tweets a month, posting 30 billion messages on Facebook. Meanwhile, more than 1 trillion mobile devices are now in use, and mobile commerce is expected to reach $31 billion trillion by 2016.

Large data and data analysis go hand in hand. Data analysis is a useful model for discovering and communicating data. One of the most common uses of data analysis is to tap business data to describe, predict, and improve performance.

Some specific areas of data analysis include enterprise decision management, retail analysis, marketing and web analytics, predictive science, credit risk analysis, and fraud analysis. Retail, marketing, and customer management have become key business points for leading vendors. IBM and Adobe, for example, have invested heavily in marketing analytics. Another leading manufacturer in the field, SAS, focuses on all types of analysis, including predictive analysis.

But the field is open to newcomers. Initial companies like QUANT5 are entering the market, bringing their own brand analytics solutions and services.

Andrew Brust is a large data expert, analyst and consultant. He founded Blue Badge Insights in New York. "The most advanced sectors in the Big data field include Web/Internet, financial services, retailing, and manufacturing and marketing in a variety of industries," he says. Web/Internet, retail and marketing analytics are weblog and social media data to determine the customer's browsing and buying patterns and perceptions. Financial services analyze market data for trading strategies and financial product design. Manufacturing companies use so-called ' historical ' data to monitor pipeline equipment and develop predictive models to determine when these devices may fail. ”

Mark Pitts, director of Science, solutions and strategy at United Healthcare, told eWEEK that the company uses analytical tools to serve its millions of customers on a variety of uses, including quarterly forecasts, fraud prevention, and customer service opportunities. In addition, his team uses the SAS High-performance Analytics platform to analyze more data in large-scale parallel environments. As a result, Pitts says his team has been able to shorten the past 4-hour process to just 10 seconds.

Large data is changing the way many companies and IT departments observe, store, and read data. But the technology is still in its infancy, and many companies are still looking for the right balance.

"My team has almost exclusively used SAS products," says Pitts. He points out that he has been programming SAS since 1985. "With SAS, we are able to react quickly when any business problem occurs," he said. The world today is very different from when I started this career. I used to do SAS programming on mainframes, when our data sources were very limited. Now, data from a variety of sources is exploding--some sources even we haven't seen, such as telemetry data from personal medical devices. ”

SAS recently announced that its SAS high-performance Analytics server (SAS high-performance Analysis servers) now supports more analytical tools, including text mining and optimization. SAS high-performance Analytics Server Predictive Modeling now also uses the Hadoop Distributed File System (Hdfs:hadoop distributed filesystem), a popular open source large data architecture.

"Macy.com's analysis team chose Hadoop on a large data platform, and SAS is our analysis engine," said Kerem Tomak, vice president of macys.com Marketing analysis. We link these two environments to create an analytical solution that can drive business value. ”

(Responsible editor: The good of the Legacy)