Data is increasingly recognized as an essential economic factor of production in digital goods and services. As a result, a robust and management system for data is now critical to an organization’s competitive strategy as well as its future in the digital economy.
Data governance is a complex set of policies and practices that ensures an organization’s data assets are managed according to business needs. It involves a team of people with diverse skillsets who must coordinate tasks, communicate decisions and drive ongoing audits and metrics that measure data governance program success and ROI. A key element of a data governance framework is the development of a vision and a business case. The vision spells out your broad strategic objective for building a governance program and the business case articulates the specific business opportunity you are looking to capture.
In addition, the business case should be actionable and clearly state what actual roles, technologies and processes will make up your governance program. This is important because it helps to avoid creating a governance program that is overly prescriptive and fails to deliver on the benefits that it is meant to address.
It is also worth noting that, as a global company, Tech Data HK must comply with the laws of every country in which it operates. This includes Hong Kong, which has strict privacy laws that require companies to obtain a warrant before sharing personal data with government agencies. The company says it only complied with three Hong Kong requests last year. Its policy states it will only respond to requests that meet local law and international norms. In some cases, such as emergencies involving threats to life, it may notify the account holder of a request by email unless it is legally prohibited from doing so.
Tech Data HK is an industry leader in the technology channel, offering products and solutions that enable customers to maximize their business outcomes. The company’s Network AI, for example, uses software advancements such as artificial intelligence and machine learning to solve problems caused by existing technologies. As a result, it is able to provide customers with higher business value while reducing costs and improving their network performance.