Gartner forecasts: 2020 Big data will become a traditional industry

Big data has become a big business, and it will not only shine in the last decade, but it will also become a regular business for companies like enterprise Resource planning, supply chain and customer management, and other parts of the enterprise computing field.

But there is a premise that we have to get more people involved and develop a large number of data scientists and experts in relevant fields.

Gartner, the IT market research firm, is holding its Symposium/itxpo conference in Orlando, Florida, and, as in previous years, it has also released some predictions at this year's conference.

Gartner first gives its latest forecast of global IT spending this year, and you may not be buying too many of these stocks, and it vendors and your company's IT departments are indirectly affected by this kind of data and forecasts for the entire IT spending. When corporate CEOs and CFOs hear that global IT spending will fall, you may not feel the problem.

The good news is that Gartner predicts global IT spending will grow by 3.8% to $3.7 trillion trillion. In its latest forecasts, Gartner reduced its spending on hardware, software and services (including telecoms equipment and services) this year by 3% to $3.63 trillion.

As in previous practices, Gartner revised its spending data for 2011 and adjusted its forecast for 2012. In fact, most managers remember only the rate of change or percentage, not the data that has been changing.

By the way, the data has been revised and changed this year, one reason is that the dollar has been changing, and Gartner has converted all foreign currencies into dollars when it comes to research and forecasts.

The big data market is expected to grow faster than the entire IT market, with sales in the big data market increasing by 21.4% in 2012 to $34 billion trillion. In a statement, Gartner said that only 4.3 billion dollars or 12.6% of total spending would flow to new software licences this year, and most of the spending would still flow to more traditional solutions to meet customers ' demands for speed, diversity and data capacity. Because of these requirements, large data is different from data warehousing and online transaction processing (OLTP).

You might think that social networks and click-Stream analysis will occupy the bulk of this year's big data spending, which accounts for around 45% of the $34 billion trillion in spending. Risk analysis and other financial services have also begun to increasingly use Hadoop and other data analysis tools, while moving from batch tools to real-time tools, just as transactions were transferred from batch to online over several decades ago.

While the prospects for big data appear to be very clear, Gartner thinks most of us think the business is as virtual as cloud computing. The big data we're talking about is the use of modern tools to do a lot of work quickly, and the conventional relational database doesn't. Just as cloud computing is a new phase of distributed computing, large data is another form of computation.

Large data can cleverly use the log file information you think is not used to pry into your customers and try to provide them with better service. It can associate your operational data with other data and try to build dependencies. If this work is done, it will be a time-consuming and laborious project, and will result in disastrous consequences because we may incorrectly correlate the data or not close the loop. Don't say the internet has been trying to get me to buy clothes for my wife for months in a row, but I've actually bought her clothes. Not only do I pay attention to the super cookies, but I also buy them, but you may not notice it.

Mark Beyer, vice president of Gartner Research, explained: "Although there is a lot of hype about big data, big data is not a clear, independent market, it actually represents a market force in the industry and must be integrated into the delivery of products, practices and solutions." ”

"In 2011, big data almost boosted the growth in spending for each IT classification project," Bayer said. However, from now until 2018, the requirements of large data will gradually evolve into the basic requirements of information management practices and technologies. It is expected that by 2020, the function of large data will become the traditional enterprise manufacturers and some of their products, the common function. ”

So Gartner argues that the big data will be the new standard in the next 10 years, and we should be studying the mega-scale system in ten years, and if everything goes well, then we'll see exaflop-level calculations, EB-level storage, 10 megawatt-level power and huge costs. But Gartner also points out that analysts will draw attention to the fact that we now lack data scientists who are familiar with all the data and how the data is used.

Peter Sondergaard, senior vice president and global research director at Gartner, said in a statement that the IT industry would create 4.4 million jobs in the Sandgad from now until 2015, with 1.9 million jobs in the United States.

Each large data task has a multiplier effect that can create several job opportunities for downstream supply chains. If so, 1.9 million of America's big data jobs will create 5.7 million more jobs outside the IT sector. EL Reg may say that as the current level of automation is already very high, it can be difficult to deliver employment opportunities to the marketing and sales departments.

Sandgad said: "But there is still a problem here, the industry does not have enough talent now." Our public and private education systems do not meet our needs in this regard. Therefore, I estimate that only one-third of the posts will be filled. Data experts will be a rare and valuable commodity. ”

We are in an awkward position again. Many people in the IT industry are still looking for jobs, but they obviously don't have the technical skills required by the jobs that big data creates.

In the present case, if companies are able to buy fewer shares and spend less money on other things, it will be a problem to invest in developing large data professionals they think they will need later. Enterprises are always lamenting the lack of quality talent, I really do not know how they persist.

EL Reg predicts that, just as businesses allow SAP and Oracle to take over their business operations through their own software, there are applications and service providers in large data areas to address the large data problems of the enterprise.

Unless absolutely necessary, businesses will not invest in developing large data professionals. And only the largest companies with the most financial resources can get professional talent. Just as you must pay for a good Java programmer or a database administrator who understands your business, you must use high salaries to retain large data scientists who know your business and the data that is useful to your company.

(Responsible editor: Schpeppen)