Big data analytics is the process of examining large data
sets to uncover hidden patterns, unknown correlations, market trends,
customer preferences and other useful business information.With
today’s technology, it’s possible to analyze your data and get answers
from it almost immediately – an effort that’s slower and less efficient
with more traditional business intelligence solutions.
Why is big data analytics important?
Big data analytics helps organizations harness their data and use it
to identify new opportunities. That, in turn, leads to smarter business
moves, more efficient operations, higher profits and happier customers.
IIA Director of Research
Tom Davenport interviewed more than 50 businesses to understand how
they used big data. He found that they got value in the following ways:
Why is big data analytics important?
Big data analytics helps organizations harness their data and use it
to identify new opportunities. That, in turn, leads to smarter business
moves, more efficient operations, higher profits and happier customers.
IIA Director of Research
Tom Davenport interviewed more than 50 businesses to understand how
they used big data. He found that they got value in the following ways:- Cost reduction. Big data technologies such as Hadoop and cloud-based analytics bring significant cost advantages when it comes to storing large amounts of data – plus they can identify more efficient ways of doing business.
- Faster, better decision making. With the speed of Hadoop and in-memory analytics, combined with the ability to analyze new sources of data, businesses are able to analyze information immediately – and make decisions based on what they’ve learned.
- New products and services. With the ability to gauge customer needs and satisfaction through analytics comes the power to give customers what they want. Davenport points out that with big data analytics, more companies are creating new products to meet customers’ needs.
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