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Big Data

Big data is extremely large data sets that may be analyzed computationally to reveal patterns, trends and associations, especially relating to human behavior and interactions.

Doug Laney articulated the now-mainstream definition of big data as the three Vs:

Volume. Organizations collect data from a variety of sources, including business transactions, social media and information from sensor or machine-to-machine data. In the past, storing it would’ve been a problem – but new technologies (such as Hadoop) have eased the burden.

Velocity. Data streams in at an unprecedented speed and must be dealt with in a timely manner. RFID tags, sensors and smart metering are driving the need to deal with torrents of data in near-real time.

Variety. Data comes in all types of formats – from structured, numeric data in traditional databases to unstructured text documents, email, video, audio, stock ticker data and financial transactions.

The importance of big data doesn’t revolve around how much data you have, but what you do with it.

You can take data from any source and analyze it to find answers that enable:

  1. cost reductions
  2. time reductions
  3. new product development and optimized offerings
  4. smart decision making

When you combine big data with high-powered analytics, you can accomplish business-related tasks such as:

  • Determining root causes of failures, issues and defects in near-real time.
  • Generating coupons at the point of sale based on the customer’s buying habits.
  • Recalculating entire risk portfolios in minutes.
  • Detecting fraudulent behavior before it affects your organization.

Related Proficiencies

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Amazon Athena

Start querying data instantly. Get results in seconds. Pay only for the queries you run.

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Amazon EMR

Distribute your data and processing across a Amazon EC2 instances using Hadoop

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Amazon Redshift

Fast, simple, cost-effective data warehouse that can extend queries to your data lake

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Amazon SageMaker

Build, train, and deploy machine learning models at scale