Big Data Management: Data Repository Strategies and Data Warehouses

Big Data Management: Data Repository Strategies and Data Warehouses

Big Data Management: Data Repository Strategies and Data Warehouses. Managing huge amounts of structured and unstructured data is crucial to the success of every company that needs systematic organization and governance to ensure their data is of high quality and suitable for analytics and business intelligence applications.

Introduction

Managing huge amounts of structured and unstructured data is crucial to the success of every company that needs systematic organization and governance to ensure their data is of high quality and suitable for analytics and business intelligence applications. Although the key aspects of big data can be summarized to the popular 3 Vs of Volume, Velocity, and Variety, there are also other key questions that every company needs to ask when choosing the proper process they need to store and transform their data.

Big Data Aspects

Volume:_ How big is the incoming data stream and how much storage is needed?_

Velocity:_ Refers to speed in which the data is generated and how quickly it needs to be accessed._

_Variety: _What format the data needs to be stored? Structured such as tables or Unstructured such as text, images, etc.

_Value: _What value is derived from storing all the data?

_Veracity: _How trustworthy the data source, type and its processing are?

_Viscosity: _How the data flows through the stream and what is the resistance and the processability?

_Virality: _Ability of the data to be distributed over the networks and its dispersion rate across the users

big-data data-lake data-management data-science data-engineering

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