Mckinsey Data Analytics

Lead: Today, foreign media published an article claiming that with the advent of cloud computing and open source software projects, the cost of storing and processing massive amounts of data has rapidly ebbed and the "big data" era officially kicked off. Not only has this trend reinvigorated India's stalled IT industry, but it has also spawned a large number of companies that rely on this technology for living. Here's the full article: "Big Data Times" shopping in a U.S. department store? A surveillance camera may monitor every move you make, and not because you might be a pickpocket. A few minutes later ...

The time is 1948, the location is Northeast China. Liaohsi into the critical phase. For the commander of the four field army Lin Biao, the most important goal after the Jinzhou is to defeat the Kuomintang new six troops. The method used by Lin Biao is to listen to the "intelligence report" every day, and the officers on duty should read out the situation and seizure of the troops. It's almost uniform data, and it's boring. Until one day, Lin Biao suddenly discovered that in a two-armed encounter in the Hu Shack, the ratio of the spear to the spear was slightly higher than the other battles, and the proportion of the car and the cart was slightly higher than the other battles.

In addition to simple bytes and bits, big data now creates billions of of dollars in business opportunities. 　　Some business organizations, such as retailers and manufacturers, analyze the customer's postal code and purchase records, and discover the limitless power that large data brings to the business development. According to the research department of the McKinsey Global Cato and McKinsey consulting firm, Big data will yield a 60% profit growth rate for the retail industry. And a recent study by the Boston consulting firm shows that customers ...

The time is 1948, the location is Northeast China. Liaohsi into the critical phase. For the commander of the four field army Lin Biao, the most important goal after the Jinzhou is to defeat the Kuomintang new six troops. The method used by Lin Biao is to listen to the "intelligence report" every day, and the officers on duty should read out the situation and seizure of the troops. It's almost uniform data, and it's boring. Until one day, Lin Biao suddenly discovered that in a two-armed encounter in the Hu Shack, the ratio of the spear to the spear was slightly higher than the other battles, and the proportion of the car and the cart was slightly higher than the other battles.

The time is 1948, the location is Northeast China. Liaohsi into the critical phase. For the commander of the four field army Lin Biao, the most important goal after the Jinzhou is to defeat the Kuomintang new six troops. The method used by Lin Biao is to listen to the "intelligence report" every day, and the officers on duty should read out the situation and seizure of the troops. It's almost uniform data, and it's boring. Until one day, Lin Biao suddenly discovered that in a two-armed encounter in the Hu Shack, the ratio of the spear to the spear was slightly higher than the other battles, and the proportion of the car and the cart was slightly higher than the other battles.

The time is 1948, the location is Northeast China. Liaohsi into the critical phase. For the commander of the four field army Lin Biao, the most important goal after the Jinzhou is to defeat the Kuomintang new six troops. The method used by Lin Biao is to listen to the "intelligence report" every day, and the officers on duty should read out the situation and seizure of the troops. It's almost uniform data, and it's boring. Until one day, Lin Biao suddenly discovered that in a two-armed encounter in the Hu Shack, the ratio of the spear to the spear was slightly higher than the other battles, and the proportion of the car and the cart was slightly higher than the other battles.

Over the past few years, with the transactional IT to interactive IT transition, corporate data began to show an explosive growth. Due to the rise of social media, the massive applications of digital sensors and the popularization of mobile devices have directly led to the rapid emergence of various large amounts of big data. This kind of multi-structured data market value is not high, but the huge amount of data contains a hidden huge wealth. Thus, how to effectively manage big data has become a topic of concern to the industry. According to 2011 Unisphe ...

According to a report published last month by IDC (International Data Company), sales of large data technology and services are expected to grow from $3.2 billion trillion in 2010 to $16.9 billion in 2015, with an annual growth rate of 7 times times the average it market. The McKinsey Global Institute points out that data is becoming a factor in products such as physical capital and human capital. Companies that can take advantage of big data will defy the data. Data capital will be as important as brand capital. Business is already adapting to big data, and the data revolution is disrupting already-established industries and business models. No matter ...

Gartner presented the BI concept in 1989. Gartner further upgraded the BI concept to advanced analysis (Advanced Analytics) in 2008. 2011, McKinsey explained the concept of large data. The names are different, but the problems they are trying to solve have never changed. However, now large data analysis technology can deal with more than 20 years ago, a larger, more diverse, real-time (Volume, produced, Velocity) data, that is, large number ...

The large data in the wall are registered as dead data. Large data requires open innovation, from data openness, sharing and trading, to the opening of the value extraction ability, then to the foundation processing and analysis of the open platform, so that the data as the blood in the body of the data society long flow, moisture data economy, so that more long tail enterprises and data thinking innovators have a colorful chemical role, 　　To create a golden age of big data. My large data research trajectory I have been 4-5 years of mobile architecture and Java Virtual Machine, 4-5 years of nuclear architecture and parallel programming system, the last 4-5 years also in pursuit ...