Love Analysis: 2020 Data Intelligence Manufacturer Panorama Report

In the process of enterprises promoting digital transformation, mining the value of data to empower business has become a common consensus. How to realize the scenario-based implementation of data-driven business has become a key problem that enterprises need to solve urgently.

Based on the survey of Party A enterprises in various industries in China, Aianalytics believes that the application of data intelligence presents the following trends:

• The increasing attention to the value mining of unstructured data and the maturity of data applications;
• The real-time requirements of enterprises for data intelligence applications in various business scenarios are constantly increasing;
• Data applications are gradually becoming popular, and front-line business personnel and data analysts have become important end users of data applications;

• Leading companies in data intelligence applications in the industry have begun to empower the upstream and downstream ecosystems of the industry and export their data intelligence application capabilities to the outside world.

For how to promote the implementation of data intelligence in the process of enterprise digital transformation, Aianalytics puts forward the following suggestions:

• The data middle platform has become a new infrastructure supporting the digital transformation of enterprises and the application of data intelligence. The construction of the data middle platform is to promote data intelligence.
• Effective means of application;
• The construction of the data center is a "top-level project", involving various business departments and systems of the enterprise, requiring top-level strategic planning first, and pushing it from top to bottom
• progress and coordinate with organizational and business change;
• The construction of the data center needs to be guided by clear priority application scenarios to achieve rapid implementation and verification of business value;

• Pay attention to data governance, formulate unified specifications from the organizational and operational levels of the enterprise, and improve data quality.