摘要： Looking to pursue a career as a data scientist? This is a field that many people are interested in because the job prospects are so good, with data playing such a pivotal role in modern-day business. Data scientists can benefit from great job security, lucrative pay, career development opportunities, and rewarding and interesting work. While there are many perks to a career as a data scientist, you should also know that it is not an easy job and will be competitive. With this in mind, keep reading for a few pieces of advice that should come in useful for anyone looking to pursue a career as a data scientist.
摘要： Don't let useless, unnecessary data strangle your storage resources. Save time and money, while eliminating potential mistakes and confusion, by embracing data hygiene.
摘要： Marketers are increasingly coming to realize the importance of artificial intelligence (AI) for analyzing data and constructing more targeted campaigns. As AI becomes more advanced, it will almost certainly come to dominate the marketing industry in the years and decades to come.
摘要： Many enterprises move their data problems to the cloud. Invest the time and money to clean up your data so that it can be more valuable to the business.
摘要： Since its conception in October 2010 by James Dixon, data lake has undergone a myriad of developments and is now used globally by a lot of firms. To understand how a data lake works or what it can be used for, we must first understand what it means.
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 ..!
