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What is Big Data?

By   /  November 13, 2017  /  No Comments

big dataBig Data refers to extremely large data sets of varying types of data – structured, unstructured, and semi-structured – that can be collected, stored, and later analyzed to provide insights for organizations.

Big Data’s promise depends on how the data is managed. In the past data was organized in relational models, sometimes within Data Warehouses, and controlled through various ETL (Extract, Transform and Load) processes. This strategy does not work well with Big Data, the size and complexity of the datasets have caused enterprises to adopt new processes and different approaches (such as NoSQL or non-relational databases) that have drastically changed many time-honored Data Management practices.

Big Data is often described by:

  • Volume: The amount of data. Often this consists of thousands of instances or billions of records
  • Velocity: The speed at which data is captured, generated or shared. This can be distributed and analyzed in real-time
  • Variety/ Variability: Forms in which data is captured or delivered. These can take different data structures that are often inconsistent within or across data sets
  • Viscosity: The difficulty to use or integrate the data
  • Volatility: The timeliness of the data. Its changeability
  • Veracity: The credibility of the data (DAMA DMBOK)

Other definitions of Big Data include:

  • “High-volume, high-velocity and/or high-variety information assets that demand cost-effective, innovative forms of information processing that enable enhanced insight, decision making, and process automation.” (Gartner IT Glossary)
  • “Vitality, in addition to Volume, Velocity, Variety, and Variability. Vitality describes a dynamically changing Big Data environments in which analysis and predictive models must continually be updated as changes occur to seize opportunities as they arrive.” (Peter Aiken)
  • “A major disruption in the business intelligence and data management landscape, upending fundamental notions about governance and IT delivery.” (Forrester)
  • “A driving force behind many ongoing waves of digital transformation, including artificial intelligence, data science and the Internet of Things (IOT).” (Forbes)
  • “A holistic information management strategy that includes and integrates many new types of data and data management alongside traditional data.” (Oracle)
  • “The way organizations create jobs by increasing the speed and transparency, creating a lot of data.” (Daisy Ridley)
  • “Data that exceeds the processing capacity of conventional database systems.” (O’Reilly)

A few uses of Big Data are:

  • Decrease expenses (Harvard Business Review)
  • Stimulate innovation (DMBOK)
  • Find and act on business opportunities
  • Define predictive and prescriptive models that anticipate customer needs, improve business interaction, and ultimately affect the ROI of a business
  • Target customers in more efficient ways
  • Optimize decision-making and business processes
  • Enhance enterprise-wide performance
  • Improve data security, compliance, and regulation

 

Photo Credit: Photon photo/Shutterstock.com

About the author

Michelle Knight enjoys putting her information specialist background to use by writing technical articles on enhancing Data Quality, lending to useful information. Michelle has written articles on W3C validator for SiteProNews, SEO competitive analysis for the SLA (Special Libraries Association), Search Engine alternatives to Google, for the Business Information Alert, and Introductions on the Semantic Web, HTML 5, and Agile, Seabourne INC LLC, through AboutUs.com. She has worked as a software tester, a researcher, and a librarian. She has over five years of experience, contracting as a quality assurance engineer at a variety of organizations including Intel, Cigna, and Umpqua Bank. During that time Michelle used HTML, XML, and SQL to verify software behavior through databases Michelle graduated, from Simmons College, with a Masters in Library and Information with an Outstanding Information Science Student Award from the ASIST (The American Society for Information Science and Technology) and has a Bachelor of Arts in Psychology from Smith College. Michelle has a talent for digging into data, a natural eye for detail, and an abounding curiosity about finding and using data effectively.

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