Qlik > 实例探究 > Strong Leaders, Strong Results: Our Path to Data Analysis, Literacy, and Governance

Strong Leaders, Strong Results: Our Path to Data Analysis, Literacy, and Governance

公司规模

1,000+

地区

Africa
Asia

国家

Russia

产品

Qlik

技术栈

SQL
Python

实施规模

Enterprise-wide Deployment

影响指标

Digital Expertise
Productivity Improvements

技术

分析与建模 - 大数据分析
分析与建模 - 数据即服务

适用行业

石油和天然气

适用功能

商业运营
离散制造

用例

自动化制造系统
预测性维护

服务

数据科学服务
系统集成

关于客户

Gazprom Neft Group, celebrating its 25th anniversary in 2020, is one of the top three oil-producing companies in Russia. The company is involved in every stage of oil-based products, from hydrocarbon exploration and the production of high-quality oil and gas to the retail sale of a wide variety of petroleum products. Gazprom Neft has operations in many areas of the world, including South America and Africa. With more than 70 subsidiaries related to production, refining, and direct sales, it is one of the largest energy operations in the world. In 2019, the company's net profit was over $5 billion USD and it currently employs over 50,000 people.

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挑战

Gazprom Neft, one of the top three oil-producing companies in Russia, was facing challenges in making data-based decisions due to the lack of a robust Business Intelligence (BI) unit. The company was already a year into their journey with Qlik, a data analytics platform, when the BI Department Head joined in 2013. The task was to further develop the internal Qlik-based processes. However, the allocation of resources was a major challenge, especially server resources. The company was also not always on schedule in the purchasing of new equipment. Change management was another challenge, particularly overcoming internal resistance without clear signaling from company leadership.

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解决方案

Despite the challenges, the company had full support from top management, especially the CFO, who was interested in the potential benefits of a robust BI unit. This support led to a revolution of sorts, leading to a transformation into a data-driven culture. The company took its time to develop expertise and structures for data analysis, data literacy, and data governance. As the company's data analysis competence grew, so did the team. By the end of 2014, the BI office had one developer and two analysts, all of whom were required to know structured query language (SQL). A year later, mathematical statistics and languages like Python were added to the required skills. As the functionality developed, so too did the various categories of staff expertise. The company also worked closely with a number of universities, offering internships to students from a variety of backgrounds, many of whom eventually joined the organization as full-time employees.

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运营影响

The company was able to establish standards for data quality and developed a single dictionary, which established standard terms for dimensions and expressions for all departments. This made it much easier for data literacy growth and the sharing of dashboards or reports across the organization.
The company was able to allow several areas to develop their own solutions due to the large and diverse nature of the organization. Each functional unit was allowed to develop their own infrastructure and rules according to their resources and needs.
The company developed different organizing principles for data processing and storage. Architectural needs often changed based on the data source and the necessary layers.

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数量效益

By 2015, the number of Qlik users had grown significantly.
Today, the company has more than 100 specialists all using the Qlik platform to power their data intelligence projects.

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