The global market for Data Historian is
projected to reach US$1.1 billion by 2025, driven by the rise of industrial big
data and the growing importance of storing process data for time-series
analysis to extract phenomena like long-term trends, cyclical fluctuations and
anomalies. With modern businesses operating in data-intensive
environments, data is at the core of about every vital business decision. Data
volumes are increasing at an alarming rate with organizations becoming more
scattered and large number of sensors being used. Consolidating and managing
the large amount of industrial big data derived from various devices, systems
and applications has become a major challenge for industries. On the other
hand, rapid expansion of businesses has further increased the need for precise
information to make accurate decisions. Growing in popularity under this scenario
is data historian also called as operational historian or process historian,
and defined as an intelligent software program which captures and retrieves
production as well as process data by time and stores data in a time series
database. Few of the benefits that strengthen the business case for data
historian include high speed data
acquisition; 50x data compression; reduced
storage space; effective in capturing
plant IoT data; complete capture of plant operating data; enables complex event
processing; query interfaces that feed into enterprise BI pipes; quicker and
informed decision making; and ensures business continuing and disaster recovery.
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The Global Market for Big Data Technologies and Services is Projected to Reach $60 Billion by 2022
GIA launches comprehensive analysis of industry segments, trends, growth drivers, market share, size and demand forecasts on the global Big Data market. The global market for Big Data Technologies and Services is projected to reach $60 billion by 2022 , driven by soaring digital data volumes in organizations and the resulting need to turn this data into valuable insights for enhancing operational efficiency, tapping new opportunities and gaining competitive edge. Defined as a natural result of mankind’s obsession with information technology and digitalization, “Big Data” refers to extremely large sets of structured, semi-structured and unstructured data of different types, including text, audio or video, generated from diverse data sources that has the potential to be mined for required information. While data supply associated with big data ecosystem has always been large and voluminous in most organizations, the ability to use these large datasets and convert them into meaningf
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