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Big Data Modeling And Management Systems Course

About The Courses

Big data is basically a non-transactional form of data containing some structured and unstructured data. By Big data management we mean administration, organization and governance of large volumes of data. The basic aim of big data management is to ensure good level of accessibility for business intelligence and big data analytics applications. The big data may involve many terabytes or even petabytes of information that are saved in various file formats. Many organizations apply big data management strategies on this fast growing data to locate valuable information from large datasets.

This course is designed to give you knowledge of analyzing and collecting the data, and organizing your data with big data solutions. You will gain knowledge of various data management tools and different data elements in everyday life problems. You will learn about Big Data Infrastructure plan and Information system design. This course will teach you various data models that suit the features of your data and help you to identify frequent data operations. You will learn concepts of Big Data management system and become capable of applying techniques to handle streaming data. The main topics included in the course are:

  • Big Data Modeling
  • Working With Data Models
  • Big Data Management
  • Big data management challenges

This course will be beneficial for data science engineers that are new to the field. You will learn to combine traditional data warehouse with Big Data systems in logical data warehousing architecture.

So, register yourself with ProLearning hub and join the Big Data modeling and management course to enhance your acumen in data science engineering.

Learning Objectives:

  • Understand the Big data management concepts thoroughly.
  • Learn to analyze, collect, and organize data using big data solutions.
  • Acquire knowledge of data management tools and big data infrastructure.
  • Understand various data models that suit the characteristics of your data.
  • Learn to apply techniques to handle streaming data.

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