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Big data is a term that describes the large volume of data – both structured and unstructured – that inundates a business on a day-to-day basis. But it’s not the amount of data that’s importan

Why Is Big Data Important?

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, and 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.

t. It’s what organizations do with the data that matters. Big data can be analyzed for insights that lead to better decisions and strategic business moves.

 

 

Course Curriculum

Section 1: Introduction
1.1. Introduction To The Course FREE 00:30:00
1.3. Big Data Challenges 00:00:20
1.4. Big Data Characteristics 00:30:00
1.5. Problems In Capitalizing On Big Data 01:00:00
1.6. Solving Big Data Problems 00:25:00
1.7. Challenges Of Relational Databases 00:40:00
Section 2: MapReduce And Hadoop
2.1. MapReduce And Hadoop 00:00:00
2.2. MapReduce Algorithm 00:00:00
2.3. Introducing Hadoop 00:00:00
Section 3: Hadoop Distributed File System
3.1.Hadoop Distributed File System 00:00:00
Section 4: Hadoop Infrastructure
4.1. Hadoop Infrastructure 00:00:00
4.2. YARN 00:00:00
Section 5: Programming Hadoop
5.1. Programming Hadoop 00:00:00
Section 6: Hive
6.1. Hive 00:00:00
6.2. Hive Architecture 00:00:00
6.3. Hive Data Model 00:00:00
6.4. Hive Queries 00:00:00
6.5. When To Use Hive 00:00:00
Section 7: Pig
7.2. Pig Data Model 00:00:00
7.3. Pig Latin 00:00:00
7.4. Pig Example 00:00:00
7.5. When To Use Pig 00:00:00
Section 8: Scalding
8.1. Scalding 00:00:00
8.2. Programming With Scalding 00:00:00
8.3. When To Use Scalding. 00:00:00
Section 9: Hadoop Ecosystem
9.1. Hadoop Ecosystem 00:00:00
9.2. HBase.mp4 00:00:00
9.3. When To Use HBase 00:00:00
9.4. Beyond Classic Hadoop Spark And Flink 00:00:00
Section 10: NoSQL
10.1. SQL Stores 00:00:00
10.2. KeyValue Stores 00:00:00
10.3. Columnar Stores 00:00:00
10.4. Document Stores 00:00:00
10.5. Graph Stores 00:00:00
10.6. Data Modeling For NoSQL Stores 00:00:00
Section 11: Streaming
11.1.Streaming 00:00:00
11.2. Storm 00:00:00
11.3.Spark And Flink Streaming 00:00:00
11.4. Lambda Architecture 00:00:00
Section 12: Big Data And NoSQL In The Enterprise
12.1. Introducing Big Data And NoSQL In The Enterprise 00:00:00
12.2. Polyglot Persistence 00:00:00
12.3. Seven Habits Of Successful Big Data And NoSQL Projects 00:00:00
Section 13: Wrap Up
13.1. WrapUp 00:00:00

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