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Learn MoreBig Data
Rating: 3.5 out of 53.5(36 ratings)
245 students
Big Data
An introductory course about understanding Big Data and its impact and relevance in today's society.
Created byThe Art Of Service
Last updated 3/2015
English
What you'll learn
- Be introduced to Data and its aspects.
- Be aware of the facts, capabilities and benefits of Big Data.
- Learn the elements (3V’s) of Big Data and their characteristics.
- Study Big Data analytics and how it works.
- Learn about implementing Big Data.
- Understand Big Data management and their technologies.
- Find out about the myths and challenges of Big Data.
Explore related topics
Course content
10 sections • 46 lectures • 3h 38m total length
- Introduction and Objectives0:29
In this lecture, we'll discuss some objectives aimed at showing what you can expect to learn from this course.
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Section Outline
Lecture 2: Data Defined
Lecture 3: Data, Information and Knowledge
Lecture 4: Understanding Data
Lecture 5: Data Usage
Lecture 6: Data Duplication
Lecture 7: Data Deduplication - Data Defined3:48
This lecture will lay the foundation for this course by clearly defining and discussing Data.
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Lecture outline:
0:00 Introduction to Data
1:04 Definition of Data
- Data, Information and Knowledge3:09
This lecture will teach you the difference among Data, Information, and Knowledge.
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Lecture outline:
0:00 Overview of the Comparison
1:31 Comparison between Data, Information and Knowledge
1:49 Computing Mechanisms
- Understanding Data3:25
This lecture will focus on understanding data.
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Lecture outline:
0:00 Introduction to Understanding Data
0:36 Things to Understand about Data
1:07 Data Description
1:26 Explore Data
2:24 Verification of Data Quality
- Data Usage3:54
This lecture will cover the different ways we can use data in different areas and platforms.
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Lecture outline:
0:00 Introduction to Data Usage
0:58 Top Applications: Onavo Count and Data Usage
2:05 Top Applications: 3D Watchdog, DataMan and My Data Manager
3:14 Top Applications: myAT&T and My Verizon Mobile
- Data Duplication1:04
This lecture will discuss the definition of Data Duplication and give you a comprehensive understanding of the subject.
- Data Deduplication6:39
This discussion will focus on the definition of deduplication, its benefits and methods.
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Lecture outline:
0:00 Introduction to Data Deduplication
1:04 Benefits of Data Deduplication
2:44 Methods of Data Deduplication
5:52 Reasons Data Deduplication is Used in Secondary Storage Systems
- Introduction and Objectives0:25
In this lecture, we'll discuss some objectives aimed at showing what you can expect to learn from this course.
.
Section Outline
Lecture 10: Big Data
Lecture 11: Facts About Big Data
Lecture 12: Capabilities of Big Data
Lecture 13: Big Data Benefits
Lecture 14: Where Big Data is Used? - Big Data4:41
This lecture will cover the definition of Big Data and introduce its dimensions.
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Lecture outline:
0:00 Introduction to Big Data
0:27 Three Dimensions of Data Growth
- Facts about Big Data4:49
This lecture will discuss the continuously growing numbers in the area of Big Data.
- Capabilities of Big Data5:05
This lecture will focus on what Big Data can do for the organization or on a personal private level.
- Big Data Benefits8:08
This lecture will explore the different benefits of Big Data.
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Lecture outline:
0:00 Introduction to the Benefits of Big Data
0:18 Talking with Customer and Developing your Products
1:54 Performing Risk Analysis and Keeping your Data Safe
3:02 Creating New Revenue Streams and Customizing your Website
4:46 Reducing Maintenance Cost and Offering Tailored Healthcare
6:19 Offering Enterprise-wide insights and Making Smarter Cities
- Where Big Data is Used?3:07
This lecture will cover five areas where Big Data is used.
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Lecture outline:
0:00 Introduction to Where Big Data is Used
0:21 Context for Interactions and Transactions
1:00 Connect with Outside Patterns
1:34 Response Based on Trends
2:11 Insight to Oversight
2:33 Know Yourself and Your Rivals
- Introduction and Objectives0:25
In this lecture, we'll discuss some objectives aimed at showing what you can expect to learn from this course.
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Section Outline
Lecture 17: Variety
Lecture 18: Volume
Lecture 19: Velocity
Lecture 20: A Fourth "V" - Variety5:35
This lecture will talk about the first theory of the elements of Big Data: Variety.
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Lecture outline:
0:00 Introduction to Variety
1:31 Structured and Unstructured Data
2:13 Variety Statistics
- Volume5:28
This lecture will discuss the second theory of the elements of Big Data: Volume.
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Lecture outline:
0:00 Introduction to Volume
1:31 Volume Statistics
2:13 Early Days of Data Processing
3:15 Hadoop
- Velocity5:48
This lecture will explain the third theory of the elements of Big Data: Velocity.
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Lecture outline:
0:00 Introduction to Velocity
1:31 Velocity Statistics
2:13 Why Does Velocity Flow Quickly
3:15 Reasons to Consider Streaming Process
- A Fourth "V"2:44
This lecture will teach you a possible fourth element of Big Data.
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Lecture outline:
0:00 Introduction to the Fourth "V"
1:31 Veracity
2:13 Variability
- Introduction and Objectives0:22
In this lecture, we'll discuss some objectives aimed at showing what you can expect to learn from this course.
.
Section Outline
Lecture 23: Big Data Analytics
Lecture 24: How to Analyze Big Data?
Lecture 25: Big Data Analytics Samples
- Big Data Analytics7:13
This discussion will focus on the analytics of Big Data.
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Lecture outline:
0:00 Introduction to Big Data Analytics
0:26 Objective of Big Data
2:03 Problems Dealing with the 3 "V"'s
2:59 Small Big Data Problem
4:13 Medium Big Data Problem
6:05 Big Big Data Problem
- How to Analyze Big Data?7:02
This lecture will cover the analysis of Big Data.
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Lecture outline:
0:00 Introduction to Analyzing Big Data
1:11 Using Big Data to get Results
2:20 Basic Analytics
2:40 Slicing and Dicing
3:56 Basic Monitoring
4:40 Anomaly Identification
5:21 Advanced Analytics
- Big Data Analytics Samples4:21
This lecture will define and explain Big Data analytic samples such as predictive modeling, text analytics, operationalized analytics, and monetizing analytics.
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Lecture outline:
0:00 Predictive Modeling
1:01 Text Analytics
1:50 Other Statistical and Data-mining Algorithms
2:17 Operationalized Analytics
3:18 Monetizing Analytics
- Introduction and Objectives0:30
In this lecture, we'll discuss some objectives aimed at showing what you can expect to learn from this course.
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Section Outline
Lecture 28: Developing a Strategy
Lecture 29: Approach to Implementing Big Data
Lecture 30: Big Data Strategies
- Developing a Strategy14:16
This discussion will center on developing a strategy for integrating Big Data.
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Lecture outline:
0:00 Introduction in Developing a Strategy
3:05 Standardize Practices
4:31 Go / No-Go Criteria
6:25 Preparing the Data Environment
7:47 Promoting Data Reuse
9:11 Instituting Proper Levels
11:03 Providing a Governed Process
- Approach to Implementing Big Data9:42
This lecture will describe a few techniques in implementing Big Data.
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Lecture outline:
0:00 Introduction in Approaching to Implement Big Data
0:13 Begin with Stakeholders
0:45 Consider Culture
1:17 Finding Data Stewards
2:37 Setting Goals
3:14 Create the Plan
4:10 Establishing Metrics
5:11 Deployment
7:41 Making Big Data Little
8:32 Design for CPI
- Big Data Strategies10:29
This lecture will enumerate and discuss strategies in achieving Big Data.
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Lecture outline:
0:00 Performance Management
1:45 Data Exploration
4:08 Social Analytics
8:05 Decision Science
- Introduction and Objectives0:28
In this lecture, we'll discuss some objectives aimed at showing what you can expect to learn from this course.
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Section Outline
Lecture 33: The Big Data Breakthrough
Lecture 34: Best Practices
Lecture 35: Current Implementation of Big Data
Lecture 36: Key Design Goals
Lecture 37: Emerging Implementation of Big Data - The Big Data Breakthrough2:37
This lecture will discuss some new developments in Big Data.
- Best Practices6:32
This lecture will teach you some practices in implementing a successful Big Data project.
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Lecture outline:
0:00 Introduction to Big Data's Best Practices
0:19 Collate Business Requirements
0:44 A Business Decision, Not an IT Decision
1:15 Agile and Iterative Approach to Implementation
2:11 Evaluate Data Requirements
2:43 Ease Skills Shortage
3:10 Optimize Knowledge Transfer
3:46 Embrace and Plan your Sandbox
4:21 Align with the Cloud Operating Model
5:07 Associate Big Data with Enterprise Data
5:44 Using Intelligence in Operational Routine
- Current Implementation of Big Data7:06
This discussion will focus on areas where Big Data is currently implemented.
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Lecture outline:
0:00 Introduction of Implementing Current Big Data
1:31 Retail Sector
2:13 Healthcare Sector
3:15 Financial Services
- Key Design Goals3:23
This lecture will talk about a few design goals of a Big Data content repository.
- Emerging Implementation of Big Data4:02
This lecture will focus on future trends where Big Data can be applied.
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Lecture outline:
0:00 Integrating Multiple Big Data Strategies
1:31 Building a Big Data Capacity
2:13 Creating a Big Data Policy
- Introduction and Objectives0:28
In this lecture, we'll discuss some objectives aimed at showing what you can expect to learn from this course.
.
Section Outline
Lecture 40: Big Data Management
Lecture 41: Big Data Management Databases
Lecture 42: Storing Big Data
Lecture 43: Hierarchy of Storage
Lecture 44: Key Requirements - Big Data Management4:46
This lecture will cover the management side of Big Data.
- Big Data Management Databases7:22
This lecture will cover the different databases of Big Data management.
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Lecture outline:
0:00 RPBMS
1:31 PostgreSQL
2:13 NoSQL
- Storing Big Data7:26
This lecture will teach you about the potentials and risks of storing Big Data.
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Lecture outline:
0:00 Introduction to Storing Big Data
1:31 Knowing the Potential and Risks
2:13 Data Centers
- Hierarchy of Storage12:08
This lecture will discuss the hierarchy of storage.
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Lecture outline:
0:00 Introduction to the Hierarchy of Storage
1:10 Primary Storage
5:35 Secondary Storage
9:09 Tertiary Storage
10:33 Off-line Storage
- Key Requirements4:34
This lecture will discuss the key requirements in storing Big Data.
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Lecture outline:
0:00 Definition of Enterprise Architecture
1:31 Gartner's definition of Enterprise Architecture
2:13 Continous update of the definition of Enterprise Architecture
3:15 EA Schools of Thought
3:33 Enterprise IT Architecting
4:08 Enterprise Integrating
4:36 Enterprise Ecological Adaptation
- Introduction and Objectives0:28
In this lecture, we'll discuss some objectives aimed at showing what you can expect to learn from this course.
.
Section Outline
Lecture 40: Big Data Management
Lecture 41: Big Data Management Databases
Lecture 42: Storing Big Data
Lecture 43: Hierarchy of Storage
Lecture 44: Key Requirements - Myths About Big Data7:15
This lecture will discuss some myths about Big Data.
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Lecture outline:
0:00 Introduction to the Myths in Big Data
1:09 Myth One
2:45 Myth Two
4:20 Myth Three
5:12 Myth Four
6:18 Myth Five
- Challenges in Big Data15:14
This discussion will focus on some challenges that Big Data faces.
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Lecture outline:
0:00 Heterogeneity and Incompleteness
2:55 Scale
7:11 Timeliness
9:39 Privacy
12:27 Human Collaboration
- Tips for a Successful Big Data Project4:47
This lecture will discuss some helpful tips in building and maintaining a Big Data project.
- Future in Big Data5:51
This lecture will explore how Big Data will fare in the future.
- Big Data Glossary of Terms4:00
This e book is a list of terms and definitions often used in the field of Big Data.
- Final Exam1:00
Now that you've finished your Udemy course, - you are eligible to sit your official Certification exam.
Certification is not mandatory.
Once you've completed the course, email our exam department at support@theartofservice.com to purchase your exam voucher and sit your final exam.Exam access includes more information to better prepare for the exam including a workbook, sample exam plus the final exam.
Please include the course name in your email for us to send the correct information.
Any questions please contact support@theartofservice.com
You will receive a PDF certificate through your email upon passing the examination. - Conclusion - Final Lecture1:27
A final message from our CEO
Requirements
- Basic understanding of the IT industry
- Knowledge of the English language
Description
Big Data is the term for a collection of datasets so large and complex that they become difficult to process using on-hand database management tools or traditional data processing applications. The challenges include capture, curation, storage, search, sharing, transfer, analysis, and visualization.
This introductory course will begin discussions on defining, understanding and using data. The succeeding modules will discuss the facts, capabilities and benefits of Big Data; the 3V’s of Big Data and Big Data Analytics. It will also present implementing data, Big Data Management and Big Data in the real world.
Who this course is for:
- Beneficial to recent graduates looking to get a foothold in the IT Industry.
- IT managers looking to better manage data analysis.
- Businesses looking to organize and analyze large amounts of vital data in order to improve business insights.
- Managers wanting to reach business goals and improve agility.
- IT professionals looking to implement new data analysis tools.