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CREATING A MODERN ANALY TICS ARCHITECTURE
analytics
What are the barriers to getting to the data you need?
We hear from organizations all the time that they are looking to extract
more value from their data but struggle to capture, store, and analyze all the
data generated by today's modern and digital businesses. Data is growing
exponentially, coming from new sources, increasingly diverse, and needs to be
securely accessed and analyzed by any number of applications and people in
shorter and shorter periods of time. The size, complexity, and varied sources of
the data mean the same technology and approaches that worked in the past
don't work anymore.
As the amount of data accumulates, customers store it in different silos, making
it difficult to perform analytics. To make it easier, customers want all of their data
in a single repository, i.e., a data lake. Organizations need to store data securely at
any scale and at low cost, using the standards-based data formats of their choice.
They want the flexibility to analyze the data in a variety of ways, using a broad
set of analytic engines to ensure their needs will be met for their present and
future analytics use cases. They also need to go beyond insights, from operational
reporting on historical data to being able to perform real-time analytics and
machine learning in order to accurately predict future outcomes.
