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Ajánljuk, ha...
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az utazás kiiktatásával időt és költséget szeretne megtakarítani
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Data is one of the most valuable assets that your organization possesses. Every day you are creating more data and potentially passing up opportunities to harvest that data and use it to accelerate the achievement of your organization’s strategic objectives. Big Data and Analytics represent an emerging trend around harvesting, analyzing, and capitalizing on the wealth of data that is within the grasp of your enterprise.
“For every 100 open Big Data jobs, there are only two qualified candidates” - fastcompany.com
This one day primer introduces Cloud Computing, Big Data, and the emerging discipline of Data Analytics. Attention will be given to the three V’s of Big Data: Volume, Velocity, and Variety as well as the fourth V of Value. You’ll learn about these critical elements and the powerful value proposition that these capabilities provide. What are the processes, tools, and personnel that will be needed in order to take advantage of this sea change in information management? This essential course will equip you to understand your customers better and how to deliver more value today.
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Big Data and Analytics for Business Users - eBook-English-(en-US)
Topics:
Cloud Computing Basics
Introduction to Big Data
Understanding Data Analytics
Understanding Predictive Analytics
Basics of Analytical Modeling
Unpacking the Value, Volume, Velocity, and Variety
Organizational Considerations
Recommended Next Steps
Kiknek ajánljuk
Managers, Analysts, Architects, and Team Leads
Szükséges előképzettség
nincs
Tematika
Chapter 1: Defining Big Data
Outline of Big Data and Analytics for Business Users Training:
In-Class Discussion
Gartner's Definition of Big Data
More Definitions of Big Data
Transforming Data into Business Information
Challenges Posed by Big Data
Processing Big Data
Apache Hadoop
The Cloud and Big Data
The CAP Theorem
Summary
Chapter 2.
Hadoop Overview
The Client – Server Processing Pattern
Apache Hadoop
Apache Hadoop
LogoTypical Hadoop Applications
Hadoop Clusters
Hadoop Distributions
Hadoop's Main Components
HDFSHDFS BlocksYARN
Hadoop-based Systems for Data Analysis
MapReduceSimilarity with SQL Aggregation Operations
Distributed Computing Economics
Discussion: Divide and Conquer
Apache PigPig Latin
Running PigPig Latin Script
Example: What is Hive?
Hive's Value Proposition
Who uses Hive?
What Hive Does Not Have
HiveQLWorking with Hive Tables
What is HBase?
HBase vs RDBS
Interfacing with HBase
HBase Table Design
DigestA Cell's Value Versioning
Creating and Populating a Table in HBase Shell
Getting a Cell's Value
Counting Rows in an HBase Table
Summary
Chapter 3. Big Data Analytics in the Cloud
Data is King
Big Data Stores in the Cloud
Example: AWS Simple Storage Service (S3) MapReduce (and Hadoop) in the CloudInformation and Data Security Data-at-rest Security Examples
Example of Object Encryption in S3
One S3 Use Case: Backup and Archiving
Data Analytics Services in the Cloud
Analytics Services with AWS
AWS EMR: Software Configuration Screen
AWS EMR: Hardware Configuration Screen
Big Data Analytics Solutions from Google Cloud
Google Data Processing and Analytics Pipelines
Google BigQuery Machine Learning
Microsoft Azure ML Studio
Machine Learning Pipeline
Summary
Chapter 4. Making Big Data Small
Techniques
What is Data Science?Data Science, Machine Learning, AI?
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