摘要： Data have been an essential part of business for so many years. Manufacturers, retailers, and marketers depend on data to develop products and design strategies used in daily business operations. Handling simple data could be easy for businesses as they can be stored, analyzed, and presented using spreadsheets or text processors.However, the rise of big data has brought about the need for better data management amongst businesses.
摘要： In order to be an excellent big data architect, it is essential to be a useful data architect; both the things are different. Let's take a look ..!
摘要： If your end goal is to build a high-performance and scalable application, you need to have a good database design. Everything begins with the database and a badly designed one is like having a bad foundation on your house. No matter how many quality elements you add to it, it won’t matter.
摘要： Openly sharing information has been a part of human culture since the beginning of civilization. Information would be shared with the general community and the practice has had a powerful impact on the development of tools and machinery.
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： The models you create have real-world applications that affect how your colleagues do their jobs. That means they need to understand what you’ve created, how it works, and what its limitations are. They can’t do any of these things if it’s all one big mystery they don’t understand.
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
