Digital transformation is a work that enterprises make email list comprehensive arrangements around the core of "data empowerment business" and persist for a long time. It is necessary to pay attention to the following six indispensable elements. In addition, pay special attention to data operation, data management and data usage. If you are also struggling with what to do with digital transformation, take a look at how the content of these 6 elements is doing. Digital transformation is a systematic project, and the six elements of data, applications, talents, tools, experience, and middle-office are the embodiment of systematic projects.
Even the data of the same department may be email list placed in different data warehouses, and there are technical barriers to connecting these data. If the internal data of the enterprise is not connected, the business department cannot associate and integrate different data, and cannot mine deeper data value. In the digital age, if companies want to seize business opportunities in a timely manner, they need not only internal data, but also external data support. In the past, companies were not good at integrating and using external data. Today, in the face of the sweeping wave of digitalization, companies have to pay attention to this external data. Businesses have data problems for many reasons. First, there are certain data problems within the enterprise. 1)
The internal data inventory is not clear enough, and the enterprise does not have a clear data asset management method and system. 2) The value of internal data assets is not clear. 3) Data does not form a closed loop, and enterprises cannot fully use data assets. 4) The data does not reach OneWorld, and the data standards are inconsistent. 5) For data without quality assurance, enterprises dare not use it easily. 6) Some data assets are in the hands of suppliers, and enterprises cannot use them flexibly and autonomously. 7) Data assets lack the protection of risk control systems (technical means, legal means, management means, etc.), resulting in data outflow and no data advantage.