three things to consider when making investments in your big data infrastructure
TRANSCRIPT
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Three Things to
Consider When Making
Investments in your Big
Data Infrastructure
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Three things to consider...
Copyright © 2014 FlyData Inc. All rights reserved.
● Is your company data-driven?
● However, before looking into making an investment
into big data architecture, here are three important
points to consider:
1. Performance and Scalability
1. Accessibility and Availability
1. Cost
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Necessity
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● Before we even get to point #1, let’s first take a step
back and consider this question: do we really need
that much data?
○ Big data is often referred to as “dumb data”
when it’s collected without knowing what to do
with it!
○ Big data is helpful and sometimes it isn’t. It
depends on your situation.
○ Sometimes all you need is smarter data!
Necessity
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● For companies in certain stages or industries, the
cost of data collection or data management may
outweigh the expected returns from big data
analysis.
● If you happen to be a leading tech company with
millions of users, you do want to take full advantage
of your data.
○ Any small optimization made as a result of data
analysis could mean millions of dollars!
Necessity
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● However, if you’re in a situation where
○ Data collection is easy and cheap
○ Service improvements are scalable across your
entire service
○ You have a good budget for data analysis
● …then you’re probably in a good position to benefit
from big data!
#1 Performance
and Scalability
Copyright © 2014 FlyData Inc. All rights reserved. www.flydata.com
Performance and Scalability
Copyright © 2014 FlyData Inc. All rights reserved. www.flydata.com
● Many companies have their own in-house database
or data warehousing solution to handle their data
management needs
● However, as the pace of data collection grows,
performance and scalability take a hit.
○ As data volume grows, data warehouses need
to be upgraded in order to collect and process
data efficiently
○ Requires time and resources!
○ If you aren’t prepared, even the slightest delay
might result in undesirable consequences
Performance and Scalability
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● In many cases, we would build a solution suitable for
our current needs
○ Needs a lot of planning beforehand!
○ If not prepared, your in-house solution could
cause potential nightmares in the future
● Thankfully, data warehouses like Amazon Redshift
are prepared for these kinds of problems
○ Easily scalable
○ Free trials to see what you can and can’t do
#2 Accessibility
and Availability
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Accessibility and Availability
Copyright © 2014 FlyData Inc. All rights reserved. www.flydata.com
● What use is a data warehouse if no one can access
it?!
○ Few people that have access to the data = less
opportunity to find meaningful information within
data
● You might also have data from multiple sources and
locations that you want to query in a single place
○ You might have so much data that loading it into
a data warehouse might take too much time
○ Data isn’t even there to query = missing out on
valuable insight!
○ This defeats the whole purpose of a data
warehouse
● Very important to plan out for accessibility and
availability of the data
Cost
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● Dilemma:
○ Most 3rd party data warehouses cost too much
money...
○ ...but building, upgrading, and maintaining an in-
house solution requires lots of engineers, time,
and money
● Solution:
○ Cloud-based solutions have very low upfront
costs for getting started
○ Unless you have sunk costs in in-house
infrastructure and employees, solutions such as
Amazon Redshift could prove to be worthwhile.
Cost
● These infrastructure costs are investments that allow
you to take full advantage of your data
○ The outcome: making sound decisions based on
data analysis
○ As opposed to making decisions blindfolded
● The importance of such investments cannot be
overstated!
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