Innovate with machine
learning and blockchain
Hundreds of thousands of businesses are
moving their data to the cloud, but data
migration presents its own unique problems.
Smooth transition: Migrate data with
virtually zero downtime using
AWS Database Migration Service
Wide selection: Find the right cloud
path for your data needs with a variety
of AWS cloud data migration services
5 Steps to Modernize
Your Data Strategy
The flywheel is a self-reinforcing loop made up of initiatives that feed into and are driven by
each other. Recently, AWS unveiled the Data Flywheel: a framework that applies this strategy
to help you derive maximum value from your data. As you build out your Data Flywheel, you're
sure to encounter challenges. But AWS offers solutions that ease the process at every phase.
Move data and
workloads to the cloud
1
PROBLEM: SOLUTION:
44%
of businesses say they
can't afford any downtime
during cloud migration—
or, at most, under an hour¹
To avoid bottlenecks,
you'll need to consider
your unique requirements
for storage, preparation,
validation, transfer
marshaling, scale, etc.²
1
https://info.cloudendure.com/rs/094-DCS-290/images/2016%20Cloud%20Migration%20Survey.pdf
2
https://www.infoworld.com/article/3268954/6-hidden-bottlenecks-in-cloud-data-migration.html
Run fully managed databases,
store all your data
2
Managing databases on your own is
expensive, time-consuming, and complex.
Minimum OpEx, maximum value:
Fully managed AWS databases drive
down operational expenses (OpEx)
while delivering high availability,
scalability, and efficiency, freeing your
staff to focus on innovation.
Save, grow, and innovate faster: Learn
how others are using AWS databases
PROBLEM: SOLUTION:
3
https://cdn2.hubspot.net/hubfs/1624046/2018%20Cloud%20Computing%20Executive%20Summary.pdf
31%
Build data-driven
applications
3
Requirements for data-driven applications
are growing fast—a one size fits all
monolithic approach doesn't work anymore.
Purpose built: Equip your developers to
use the right database for the right job,
so they can build use-case driven, highly
scalable, distributed applications—faster
and more efficiently.
PROBLEM: SOLUTION:
Analyze data
in your data lake
4
Performing critical analytics across all
of your data is next to impossible using
legacy models of siloed data.
No silos: Building data lakes on AWS
using Amazon S3 and AWS Lake
Formation allows you to collect and
store data once in standards-based-
formats, in one centralized repository.
Faster, smarter: With AWS data lakes,
analyze all of your data with the right
tools to get deeper insights—no need to
wait for data to be copied into multiple
analytics engines.
PROBLEM: SOLUTION:
60%
of businesses say
"finding correlations
across multiple disparate
data sources" is the
#1 challenge in their
data-driven initiatives⁴
Poor quality data costs
the U.S. $3.1 trillion
annually⁵
$3.1T
4
https://cdn2.hubspot.net/hubfs/1624046/IDGE_Data_Analysis_2016_final.pdf
5
https://www.ciodive.com/news/the-organizational-costs-of-data-thats-hidden-in-plain-sight/516405/
5
Getting started with Machine Learning
and Blockchain technologies can be
challenging.
Only 18% of companies have a clear
strategy in place for sourcing the data
that makes AI/ML work⁶
Less than 5% of organizations have
incorporated ML extensively into their
processes⁷
On average, blockchain application
developers charge $81-$100/hr⁸, and
demand for blockchain specialists far
outweighs supply⁹
PROBLEM: SOLUTION:
6
https://www.mckinsey.com/featured-insights/artificial-intelligence/ai-adoption-advances-but-foundational-barriers-remain
7
https://www.informationweek.com/strategic-cio/executive-insights-and-innovation/most-ceos-dont-know-where-to-deploy-ai-within-their-business/a/d-id/1333603
8
https://www.codementor.io/freelance-rates/blockchain-developers
⁹ https://www.n-ix.com/outsourcing-blockchain-development-how-to-make-it-work/
Trusted: More than 10,000 customers
worldwide utilize AWS for ML use cases
Ml-enabled: Through Amazon SageMaker,
you can:
Reduce data labeling costs by
up to 70%
Built-in algorithms with 10x
performance
Reduce inference costs by up to 75%
Centralized and decentralized
workloads: Leverage Amazon Managed
Blockchain for building decentralized
applications, or use Amazon QLDB
for centralized applications that need
to store data in an immutable and
verifiable way
4. Analyze
data in your data lake
5. Innovate
with ML and blockchain
1. Move data
and workloads to
the cloud
3. Build
data-driven apps
2. Run
fully-managed databases,
store all your data
of businesses cite "lack of the
right skill sets to manage and
derive maximum value from
cloud investments" as one of
their top three cloud challenges³
Ready to spin up perpetual momentum for your business?
Dig into the Data Flywheel >
USERS LOCALITY
1K 1M+ Local Global
PERFORMANCE VOLUME
Seconds
sub-milliseconds
GB PB+
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In-memory
