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Big data Concept and tools (Fundamentals of Big Data Analytics (New…
Big data Concept and tools
Fundamentals of Big Data Analytics
New technologies needed
Challenge of effectively and efficiently capturing, storing, and
analyzing Big Data
Big Data by itself, regardless of the size, type, or speed,
is worthless
No SQL
applications
data to end-users and Big Data
Serves discrete data stored among large volumes of multistructured
Challenges of Big Data Analytics
Data Volume:
The ability to capture, store, and process the huge volume
of data in a timely manner
Solution cost : Return on Investment
Skill availability : shortage of data scientists
Processing capabilities
The ability to process the data quickly, as it is captured
(i.e.,stream analytics)
Coexistence of Hadoop & DW
Use Hadoop for storing and archiving
multistructured data
Use Hadoop for filtering, transforming, and/or
consolidating multi-structured data
Use Hadoop to analyze large volumes of
multistructured data and publish the analytical
results
Limitations of Data Warehouse/Relational Database
Speed:
Unable to handle speed at which big data is arriving
Scalability
Unable to handle huge amounts of
new/contemporary data sources
Others:
Unable to handle sophisticated processing