Big data to death you can't imagine the last winner

Hunt Cloud Web September 17 report (Compile: Colin)

Are you still scratching to understand hive, Spark, pig these programming languages? Don't worry, a competition is making it easier for non-professional users to use the complex, big data technology like Hadoop, and you can enjoy the extra benefits that make you rich.

Yes, that's you.

A few years ago, Peter Goldmacher, a former analyst at Cowen&co, said in a survey briefing, "After all, the closer you get to the end users of the big data technology, the more you return." "The biggest winners in the big data world are not suppliers of the technology, but companies that use it to create new industries or disrupt traditional businesses," he says.

As time goes on, the forecasts made by Goldmacher in 2012 appear to be getting more and more correct. The builders of the big data base should be praised, but the most profitable are the companies that are most closely related to technology marketing and sales experts who may not know how to do parallel operations from a PivotTable report.

Provide solutions instead of technology

We've seen this practice in companies like John Deere, who have developed very powerful data-oriented applications using Hadoop and NoSQL database technology. While Silicon Valley is also the center of the universe, the wider world outside is using big data in the most useful places.

If not, we would be surprised. As Goldmacher writes, this always applies to science and technology: As previously said, if we review the history of ERP, more than 200 companies have been created to accumulate capital in the process of automating standard business processes. This means that 1990-year investors are less than 0.5% likely to choose SAP or ORCL as the ultimate winner. However, if investors bought shares in the company's 30 Dow companies in 1990, he could reduce the general cost and management costs by 35%, and increase it by five times times through large-scale automated production, which would increase by nearly eight times times the market value.

Of course, large data infrastructure service providers will also be cashing, such as Cloudera. Cloudera's market capitalisation has reached $ billions of trillion, and other companies, such as DataStax and MongoDB, are already worth more than $1 billion trillion.

But it is not themselves that have benefited most from the software of these companies, for the following reasons:

· Most large data technologies are open resources, which means that everyone can use it and it is hard to make a profit from it.

· The main users of these technologies are developing companies like Hadoop, which are important for pushing technology, but they don't want to spend money.

· Companies with more consumer ties and relatively well-funded companies are more likely to profit from big data.

According to the 1th reason, Cloudera's co-founder, Mike Olson, said, "You cannot succeed on a closed resource platform, and you cannot build a successful independent company on the basis of open resources alone." "This allows suppliers to combine ownership with open source licensing to maximise returns, but those at the top of the industry need not worry about that."

The winner is ...

Clearly, they are application (service-specific) suppliers who do not show the complexity of the technology to end users and charge only for the services they provide. Workday's co-founder, Aneel Bhusri, had this idea a few years ago.

McKinsey & Co. Detailed description of the impact of large data on different industries:

These companies include John Deeres, which I mentioned earlier, but who will win when it comes to the more technical mainstream?

The answer is those companies that are most likely to hide the complexity of the product and make it easy for users to operate.

Microsoft, for instance, fits the pattern. Look at what he did with the Azure machine. Azure machine learning is expected to eliminate almost all of the "initiative costs associated with the production, development and expansion of machine learning methods", and "visual workflow and initiative templates can make the General machine learning task simpler".

Although Microsoft has a lot of picky places (I've always been looking for it), it does more than any other company in reducing the difficulty of complex computing. Windows, Visual Studio, and many other technologies make it possible for mainstream system administrators and developers to be creative, as azure machines learn to emulate these technologies.

The Geek is gone!

But we have to think about it further. After all, while big data is good for developers and system administrators, the real problem is to make big data easier for ordinary people like you and me, Wikibon analyst Dave Vellante has the following idea:

Business intelligence has created a class of analysts, but it has not been the mainstream. We want big data to be mainstream.

One of the companies that looks good for this is adobe. Adobe has always been concerned about creative careers, and a few years ago the acquisition of Omniture had made adobe steadily leap into the big data world, but it was more concerned with helping marketing experts get leads.

The key to managing large data is not the huge amount of data, but the increasing data sources and data types. For a company like Adobe, to get marketing experts to make decisions in a very short time based on ads, charts, etc., it collects and analyzes information from social media, cash receipts, and so on to understand customer behavior.

It's time to clear the weeds.

Microsoft and Adobe are just two examples of big data potential winners, and many other companies may stand out and hope for your company.

To achieve this, we need to stop delving into the useless things in big data technology and instead focus on the business value they can create. This value can be passed through the applications we use and will not vanish into thin air.

In an interview with Bosch's Dirk Slama, Olson said he talked to a lot of people who just used large data as data, and he felt "these people are not ideal partners because they are fundamentally not business-oriented". The real winners in the big data age are those who are focused on solving real business problems.