摘要: There is a always a need for data modelers, however, the job description of this career field varies, depending on the needs of the organization. For example, a data modeler working for a startup would coordinate with data scientists and data architects in designing a new system — one that included the goals of the organization, and the steps needed to achieve them, within its architectural design. This “model” represents the organization and promotes understanding through the use of core data, such as attributes, entities, and relationships regarding customers, staff, products, and other factors.

摘要: The journey of advanced analytics has been a long in development, with many hurdles along the way. Some of the most complicated aspects of data analytics that still remain today are data gathering technologies, data cleansing methods, and skill support for advanced analytics. It has taken years to come to the automated age of business analytics, when even mainstream business users without much technical knowledge are able to use AI or machine learning-enabled self-service analytics.容

摘要: Being a data scientist is hard. In addition to the combination of advanced mathematics and coding skills required to do the job, it’s a newer role for many organizations, so data scientists are called upon to navigate corporate landscapes, source the right IT resources, and establish new workflows across departments

摘要: Data integration uses both technical and business processes to merge data from different sources, with the goal of accessing useful and valuable information, efficiently. A well-thought-out data integration solution can deliver trusted data from a variety sources.

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