inventory big data project success seven secrets(库

Inventory: Big Data project success Seven

Secrets

Success (free papers Download Center News) big data projects What magic? What are the traps can cause big data projects fail? In this paper, the three experts will conduct a Detailed.

Today, many large companies have to understand the composition of the data, but to be successful big data project is another matter. Gartner analyst, Doug Laney. Forrester analyst Mike Gualtieri. International Institute for Analytics expert, senior research scholar, Robert Morison data fields are big, they are great for businesses on how to use the data has a unique perspective. The following can help big data project success factors, and possible reasons for the failure of big data project what they think.

Who began the project

CIO who have heard this advice before, but from the beginning of the project in the end mean? ‘This means that from the one you think you can improve business performance in the field to proceed from an analysis of

more data you think you can get more information on the field started,’ Institute of Morison said.

He cited the case of a pharmaceutical company, the firm wants its product yield increased by 1% to 2%. The use of traditional business intelligence tools, which can analyze a certain number of production history, which found parts of the production process can be adjusted. Then, companies want to know if more data analysis, can help determine the production performance of the real driving force. Then, using the Hadoop-related open source technologies, the company within a week analyzing the production history of the past three years.

‘Soon, they began to develop a variety of combinations of variables hotspot map - in this case, pressure, temperature, stirring and rate of these parameters can result in higher product yield,’ Morison said. ‘So, in a few months time, they can bring more data from the analysis of what the outcome, the development of the manufacturing plant to carry out experiments to gain increased production.’

Constantly test

It is time the CIO and business executives from the

traditional consumer, goal-oriented IT project

management style came out, Morison said. Instead, encourage pilot projects and creative thinking. In the previously mentioned case of pharmaceutical companies, ‘the goal is to test side, while progress and learning,’ he said. ‘This case really valuable is that once they start doing so, each new batch of products, they become part of the database. They have a continuous feedback loop. This test enables business performance is getting better. ‘

Gartner’s Laney thought experiment should include ‘those that do not seem natural to integrate the relevant data source.’ For example, retailers, analysis of surveillance video data ‘to understand the traffic within the store,’ Let them have the opportunity to determine the shopping habits and shopping patterns, he said.

Using Hadoop technology

Hadoop big data is not just technology, ‘but Hadoop is a big catalyst’, because it cheap and easy to obtain, Forrester’s Gualtieri said. Many get big data project successful companies are more or less in Hadoop technology background. ‘With Hadoop. Use it as your