Goldman Sachs: High return on current investment in large data industries

Goldman Sachs co-chairman Scott Stanford said: "In terms of current conditions, investment in large data and its use of the highest rate of return." The remark comes from Scott's video session, which shows Goldman is supportive of big data innovations and gives investors some advice on how to invest.

Goldman Sachs is one of the few investment banks to invest in big data so far, and its main competitor is still the old rival, Morgan Stanley. Two of investment banks are keen to invest in High-tech industries, secretly competing with each other, "Goldman Sachs is http://www.aliyun.com/zixun/aggregation/1560.html" >facebook IPO major investor " The news is from Morgan Stanley.

The following are Scott's main ideas for the development of the big Data industry:

First, in the final analysis, large data is also data.

At present, the amount of data created by Internet media in the world is several times that of the Library of Congress, it is very difficult for enterprises to capture these data. But the ability to use large data depends largely on: doing and not doing.

To capture this data, the enterprise needs to: (1) Obtain the required data, (2) on how to deal with the relevant technology and knowledge of data, (3) How to apply the results of large data processing to the right consumers. There are already a few enterprises in the market have one of the above three, with three capacity of the enterprise is almost zero. (Scott did not mention the problem with the Apple map, but Google Maps are a typical example of using data to make products.)

Second, how to effectively use the function of large data.

How to use-large data can be universal to all walks of life, not only transportation, but also education, labor, retail and other industries. Because the industry is too general, comprehensive treatment efficiency is too low, all the Internet is now experiencing a "fine differentiation" phase, the breakdown of the Internet will be closely combined with large data.

Third, innovation in the technology industry is unprecedented.

It takes 80 months (6-7 years) for a previous site to get 150.02 billion users, and now startups only need 10 months to reach tens of millions of users.

The emergence of the new platform so that enterprises do not need to spend many years to be able to obtain a large number of users, data, capital and global market share, this is the previous technology start-ups do not dare to think about.

Here's what Scott has to offer investors:

"Available Market" size and Profit path. The big data companies that investors want to invest in are probably not profitable so far, but it doesn't matter. Long-term investment gains are much better than short-term gains. To determine profitability according to the economic level of the industry.

Scalability-theoretically influenced by the Internet.

There are few hurdles to entering the big data field, and there is almost no defensive nature.

The data obtained by the enterprise can be large and small, according to the specific development of the enterprise. Specific reference to the above three to determine whether the enterprise qualified.

Large data enterprise teams have the passion and ability to meet challenges.

Article Source: VentureBeat

(Responsible editor: The good of the Legacy)