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capgemini-数据驱动型企业:为什么组织必须加强对数据的掌握(英)-2021

# 数据驱动型企业 # 数据 大小:5.07M | 页数:64 | 上架时间:2021-06-24 | 语言:英文

capgemini-数据驱动型企业:为什么组织必须加强对数据的掌握(英)-2021.pdf

capgemini-数据驱动型企业:为什么组织必须加强对数据的掌握(英)-2021.pdf

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类型: 专题

上传者: ZF报告分享

撰写机构: capgemini

出版日期: 2021-06-15

摘要:

The already-rich seam of global data shows no sign of letting up – volumes of digital data are expected to reach 40 ZB this year, up from 1.8 ZB in 2011.1 To put this into some sort of perspective – this is 40 trillion gigabytes, equivalent not just to every grain of sand on all the world’s beaches, but 57 times that amount. However, the sheer volume of data in our hands today in no way translates into equivalent levels of actionable and credible insights.

This is a problem, as data has never been more important.

The uncertainty unleashed by the ongoing COVID-19 crisis has heightened the need for forward-looking, realtime insights and scenario modelling, such as pandemic modeling. Actionable data is the most critical factor in digital transformation. But aside from a few high-performers – what we call the Data Masters – our research shows that data capability is patchy among many organizations today.

So, what is it that separates those leading firms that do have a sophisticated capability? What are the unique attributes of their business and technical teams and how can others emulate them to become data-powered enterprises? To answer these questions, we surveyed 500 technology executives and 500 business executives from a range of industries, and conducted detailed interviews with more than 15 executives. We also looked at the relationship between data mastery and the financial performance of organizations.

Based on our research, we look at the following key areas in this report: 1. Where are organizations today in their data journey?

2. What gaps exist between data executives’ perceptions and the expectations of business executives on the data mastery of their organizations?

3. Who are the data masters?

4. What are the benefits they achieve?

5. How can we build a data-powered enterprise and what can we learn from the masters in this field?

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