The inclusion of data assets in financial statements can quantitatively reflect the value of data factors on corporate financial reports, consolidate enterprises’ asset base, push enterprises to pay attention to the development, management, and utilization of data resources, and provide more comprehensive accounting information for stakeholders such as investors and regulatory authorities. Nevertheless, differing from traditional tangible assets and intangible assets, data assets bear distinctive particularities. They are intangible with complicated ownership relations; their values fluctuate under the influence of technological iteration, market demand, data quality, and multiple other factors, and their costs can hardly match values precisely. As a result, the conventional accounting confirmation and measurement system cannot fully adapt to the accounting treatment requirements of data assets. Therefore, systematically studying existing problems in the accounting confirmation and measurement of data assets and putting forward scientific and reasonable improvement measures carry important theoretical and practical significance.