What exactly are the characteristics that define data as an asset? We can judge it by the following three criteria: controllable, quantifiable, and realizable.

For how to efficient data asset management, to help enterprises with high-quality data to provide more accurate products and services, reduce costs and control risk, thereby enhancing the core competitiveness of enterprises, the next by the Shenzhen count on you to understand the data center asset management.

One, data governance: governance but not chaos, so that data into assets

Now the IT department is the most miserable, the IT department is not the owner of the data, but when the data problems are to find the IT department: blame the data is inaccurate, unreliable, unsafe.

In reality, data drives the core business of an organization, so data governance shouldn't just be the responsibility of IT. It also requires extensive business engagement, with interdepartmental communication to provide ongoing support for business decisions, business definitions, data quality processes, and development prioritization for the future state vision of the enterprise. ***This standard may not be optimal, but it is the most effective and appropriate in current working practice.

II. Data Asset Management Architecture: Driving Enterprise Architecture Maturity

"Data drives everything" is no exaggeration for enterprise development in the era of big data. In the enterprise, it is not difficult to see the operation and maintenance of ERP, CRM, financial systems, technical architecture, data centers, and these resources are managed by dedicated personnel. And when data becomes a core asset of the enterprise, who is responsible for it?

IT should only be responsible for HowtoDo. Changing the structure, should first change from the people; enterprise change, should first start from the organizational change. When data becomes a core asset, enterprises should set up a professional responsible for data architecture and management of cross-project professional data asset management materialized, or virtual organization, continuously improve the data architecture, enhance the enterprise in data planning, design, development and delivery of the quality of the IT system construction lifecycle from start to finish management.

Three, data ****sharing: the foundation of big data

***sharing economy opens a new era, data ****sharing is the foundation of big data. All the tools provided by the Internet based on the solution is the problem of trust, there is no trust as the basis, there is no *** enjoy the existence of.

The first step is to solve the problem of *** enjoying data within the enterprise. Before big data, enterprises were using ESBs, but people gradually realized that only the enterprise bus could not solve the problem. Because the solution of services is just to encapsulate the complexity of the problem in a simple way, but the seemingly perfect call does not solve the core problem of data.

Thus, at the beginning of the establishment of a big data center in the enterprise, it is necessary to avoid simply integrating data together without effective management. For SMBs, the way to agility in big data is scenario-driven. It must be centered around the most fundamental business needs of the enterprise, rather than big data for the sake of big data, SMEs need more flexible, faster, more cost-effective solutions.