No matter what company does, in order to succeed in today's competitive environment, you need a robust infrastructure to both store and access the company's data. And, it needs to be done from the very beginning. And, thus the demand for skilled data engineers is rapidly growing and is projected to grow at a faster rate.
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This post examines the evolution of data processing in data lakes, with a particular focus on the concepts, architecture and technology criteria behind them.
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Data mining is sifting through all of the data collected by a business or organization, searching for relationships so that reasonable predictions can be made with regard to behavior. This kind of activity is most common among businesses that deal with consumer behavior of any kind.
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You need to have done Data Warehousing before doing Data mining.
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The article explains the complete lifecycle of a Data Science Project so that every beginner who is starting to undertake a project gets the guidance and any experienced who is already into the process can cross check whether he is following the right steps or not.
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The 7 most important terms in Data Science that every Data Scientist must know while making a career in Data Science are discussed in the present article.
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A Big Data Analyst is the person in the organization who collects data from various resources, clean it for further processing, converts it into another format which is easy to analyze (also called Data Munging) and finally analyze it for finding hidden patterns and useful information from it (also called insights).
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Data Science Tools, Data Analysis, Data Warehousing, Data Mining, Microsoft Azure, MySQL, DataRobot, Amazon
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