The presentation about Big Data Analytics will help you know why Big Data analytics is required, what is Big Data analytics, the lifecycle of Big Data analytics, types of Big Data analytics, tools used in Big Data analytics and few Big Data application domains. Also, we'll see a use case on how Spotify uses Big Data analytics. Big Data analytics is a process to extract meaningful insights from Big Data such as hidden patterns, unknown correlations, market trends, and customer preferences. One of the essential benefits of Big Data analytics is used for product development and innovations. Now, let us get started and understand Big Data Analytics in detail. Below are explained in this Big Data analytics tutorial: 1. Why Big Data analytics? 2. What is Big Data analytics? 3. Lifecycle of Big Data analytics 4. Types of Big Data analytics 5. Tools used in Big Data analytics 6. Big Data application domains What is this Big Data Hadoop training course about? The Big Data Hadoop and Spark developer course have been designed to impart an in-depth knowledge of Big Data processing using Hadoop and Spark. The course is packed with real-life projects and case studies to be executed in the CloudLab. What are the course objectives? This course will enable you to: 1. Understand the different components of the Hadoop ecosystem such as Hadoop 2.7, Yarn, MapReduce, Pig, Hive, Impala, HBase, Sqoop, Flume, and Apache Spark 2. Understand Hadoop Distributed File System (HDFS) and YARN as well as their architecture, and learn how to work with them for storage and resource management 3. Understand MapReduce and its characteristics, and assimilate some advanced MapReduce concepts 4. Get an overview of Sqoop and Flume and describe how to ingest data using them 5. Create database and tables in Hive and Impala, understand HBase, and use Hive and Impala for partitioning 6. Understand different types of file formats, Avro Schema, using Arvo with Hive, and Sqoop and Schema evolution 7. Understand Flume, Flume architecture, sources, flume sinks, channels, and flume configurations 8. Understand HBase, its architecture, data storage, and working with HBase. You will also understand the difference between HBase and RDBMS 9. Gain a working knowledge of Pig and its components 10. Do functional programming in Spark 11. Understand resilient distribution datasets (RDD) in detail 12. Implement and build Spark applications 13. Gain an in-depth understanding of parallel processing in Spark and Spark RDD optimization techniques 14. Understand the common use-cases of Spark and the various interactive algorithms 15. Learn Spark SQL, creating, transforming, and querying Data frames Learn more at https://www.simplilearn.com/big-data-and-analytics/big-data-and-hadoop-training

1. Machine
Learning Basics
An Introduction

2. What’s in it for you?
Tools used in big data analytics
Lifecycle of big data analytics
Why big data analytics?
What is big data analytics?
1
2
3
4
5
6
Types of big data analytics
Big data application domains

3. What’s in it for you?
Big Data Challenges
What is HDFS?
HDFS Cluster Architecture
HDFS Data Blocks
Data Node Failure
Rack Awareness
General Architecture of HDFS
Read/Write Mechanism
Why big data analytics?

4. I’m sure most of you would have
used a music streaming platform…

5. ….like Spotify!

6. Spotify has nearly 96 million users

7. User behavior includes songs played,
repeatedly used playlists, likes, shares and
search history, all of which represents the big
data used by Spotify

8. Spotify analyzes this big data for suggesting
songs to its users

10. Recommendation systems are data filtering
tools. They collect data and then filter them
using algorithms

11. The recommendation systems accurately
predict what users would like to listen to next
with the help of big data analytics

12. Using big data analytics, Spotify keeps its
users engaged and by doing so, the users use
the application more

13. What’s in it for you?
Big Data Challenges
What is HDFS?
HDFS Cluster Architecture
HDFS Data Blocks
Data Node Failure
Rack Awareness
General Architecture of HDFS
Read/Write Mechanism
What is big data analytics?

14. Big data
Massive amount of data which cannot be stored, processed and analyzed using traditional tools is
known as big data
What is big data?

15. Big data
Massive amount of data which cannot be stored, processed and analyzed using traditional tools is
known as big data
Storing, processing and analyzing big data became
difficult using traditional methods
Analyzing
Storing
Processing
What is big data?

16. Big data analytics is a process to extract meaningful insights from big data such as hidden patterns,
unknown correlations, market trends and customer preferences
What is big data analytics?

17. Big data
analytics
Big data analytics is used for
risk management
Big data analytics is a process to extract meaningful insights from big data such as hidden patterns,
unknown correlations, market trends and customer preferences
What is big data analytics?

18. Banco de Oro, a Philippine banking company uses
big data analytics
What is big data analytics?

19. Banco de Oro, a Philippine banking company uses
big data analytics
Identifying fraudulent activities and
discrepancies is easier using big data
analytics. Thus the organization was able to
narrow down the list of suspects using big data
analytics
What is big data analytics?

20. Big data
analytics
Big data analytics is used for
risk management
Big data analytics is used for
product development and
innovations
Big data analytics is a process to extract meaningful insights from big data such as hidden patterns,
unknown correlations, market trends and customer preferences
What is big data analytics?

21. Rolls-Royce manufactures massive jet engines.
These engines are used by airlines and armed forces
across the world
What is big data analytics?

22. Rolls-Royce manufactures massive jet engines.
These engines are used by airlines and armed forces
across the world
The company uses big data analytics to analyze how good
the engine design is and if there has to be any more
improvement
Big data analytics is used here in designing a product of
higher quality
What is big data analytics?

23. Big data
analytics
Big data analytics is used for
risk management
Big data analytics helps in
quicker and better decision
making in organizations
Big data analytics is used for
product development and
innovations
Big data analytics is a process to extract meaningful insights from big data such as hidden patterns,
unknown correlations, market trends and customer preferences
What is big data analytics?

24. Starbucks uses big data analytics for important
decisions. For example, big data analytics is used to
decide if a particular location would be suitable for a
new outlet or not
What is big data analytics?

25. The analysis is done based on factors such as population
demographics, accessibility of the location, competition in the
vicinity, economic factors, parking adequacy and so on
The business grows if the right location is chosen wisely by
considering the above parameters
Starbucks uses big data analytics for important
decisions. For example, big data analytics is used to
decide if a particular location would be suitable for a
new outlet or not
What is big data analytics?

26. Big data
analytics
Big data analytics is used for
risk management
Big data analytics is used for
product development and
innovations
Big data analytics is used to
improve customer experience
Big data analytics is a process to extract meaningful insights from big data such as hidden patterns,
unknown correlations, market trends and customer preferences
Big data analytics helps in
quicker and better decision
making in organizations
What is big data analytics?

27. Delta airline uses analysis to improve customer
experiences
What is big data analytics?

28. Airline identifies negative tweets and does the needful by
upgrading the customer’s ticket for the next journey if it is
found out to be the airline’s fault.
This helps the airline build good customer relations
Delta airline uses analysis to improve customer
experiences
They monitor tweets to find out their customers’ experience
regarding the journey, delays and so on
What is big data analytics?

29. What’s in it for you?
Big Data Challenges
What is HDFS?
HDFS Cluster Architecture
HDFS Data Blocks
Data Node Failure
Rack Awareness
General Architecture of HDFS
Read/Write Mechanism
Lifecycle of big data analytics

30. Business case
evaluation
Big data analytics lifecycle begins with a business case which
defines the reason and goal behind the analysis
Lifecycle of big data analytics

31. Business case
evaluation
Identification of
data
A broad variety of data sources are identified
Lifecycle of big data analytics

32. Business case
evaluation
Identification of
data
Data filtering
All the identified data from the previous stage is filtered
here to remove the corrupt data
Lifecycle of big data analytics

33. Business case
evaluation
Identification of
data
Data filtering
Data extraction
The data that is not compatible with the tool is extracted and
then transformed to a form that is compatible
Lifecycle of big data analytics

34. Business case
evaluation
Identification of
data
Data filtering
Data extraction
Data aggregation
In the data aggregation stage, data with the same fields
across different datasets are integrated
Lifecycle of big data analytics

35. Business case
evaluation
Identification of
data
Data filtering
Data extraction
Data aggregation
Data analysis
This is the process of evaluating data using analytical and
statistical tools to discover useful information
Lifecycle of big data analytics

36. Business case
evaluation
Identification of
data
Data filtering
Data extraction
Data aggregation
Data analysis
Visualization of
data
Visualization of data is done by graphically communicating the
analysis results. Tools like Tableau, PowerBI and QlikView are
used
Lifecycle of big data analytics

37. Business case
evaluation
Identification of
data
Data filtering
Data extraction
Data aggregation
Data analysis
Visualization of
data
Final analysis
result
Final analysis result is made available to business
stakeholders for decision making
Lifecycle of big data analytics

38. What’s in it for you?
Big Data Challenges
What is HDFS?
HDFS Cluster Architecture
HDFS Data Blocks
Data Node Failure
Rack Awareness
General Architecture of HDFS
Read/Write Mechanism
Types of big data analytics

39. Big data analytics
Descriptive analytics Diagnostic
analytics
Predictive
analytics
Prescriptive analytics
What has happened? Why did it happen? What will happen? What is the
solution?
Types of big data analytics

40. Big data analytics
Descriptive analytics Diagnostic
analytics
Predictive
analytics
Prescriptive analytics
What has happened? Why did it happen? What will happen? What is the
solution?
Types of big data analytics

41. Descriptive analytics It summarizes past data into a form that
is interpretable by humans
Descriptive analytics
What has happened?Q1
Types of big data analytics

42. Descriptive analytics It summarizes past data into a form that
is interpretable by humans
Descriptive analytics
What has happened?Q1
0
10000
20000
30000
40000
50000
60000
70000
80000
2015 2016 2017 2018
A company’s profit graph
Revenue nill Profit
Types of big data analytics

43. Descriptive analytics It summarizes past data into a form that
is interpretable by humans
Descriptive analytics
What has happened?Q1
0
10000
20000
30000
40000
50000
60000
70000
80000
2015 2016 2017 2018
A company’s profit graph
Revenue nill Profit
This analytics helps in creating reports
like company’s revenue, profit, sales and
so on
Tabulation of social media metrics like
Facebook likes and tweets are done
using descriptive analytics
Types of big data analytics

44. Descriptive analytics
The Dow Chemical Company analyzed its past data to increase facility utilization
across its office and lab space
Descriptive analytics
Using descriptive analytics, Dow was able to identify under-utilized space. This space
consolidation helped the company save nearly USD 4 million annually
It summarizes past data into a form that
is interpretable by humansWhat has happened?Q1
Types of big data analytics

45. Big data analytics
Descriptive analytics Diagnostic
analytics
Predictive
analytics
Prescriptive analytics
What has happened? Why did it happen? What will happen? What is the
solution?
Types of big data analytics

46. Descriptive analytics
Descriptive analyticsDiagnostic analytics
This analysis is done to understand
why a problem has occurred. It looks
into the cause of a problem
Types of big data analytics

47. Descriptive analytics
Descriptive analyticsDiagnostic analytics
This analysis is done to understand
why a problem has occurred. It looks
into the cause of a problem
Why did it happen?Q2
Types of big data analytics

48. Descriptive analytics
Descriptive analyticsDiagnostic analytics
This analysis is done to understand
why a problem has occurred. It looks
into the cause of a problem
This analytics is characterized by
techniques such as drill-down, data
mining and data discovery
Why did it happen?Q2
Types of big data analytics

49. Descriptive analytics
Descriptive analyticsDiagnostic analytics
This analysis is done to understand
why a problem has occurred. It looks
into the cause of a problem
Organizations go for diagnostic
analytics as it gives an in-depth insight
into a particular problem
This analytics is characterized by
techniques such as drill-down, data
mining and data discovery
Why did it happen?Q2
Types of big data analytics

50. Descriptive analytics
Descriptive analyticsDiagnostic analytics
This analysis is done to understand
why a problem has occurred. It looks
into the cause of a problem
Organizations go for diagnostic
analytics as it gives an in-depth insight
into a particular problem
This analytics is characterized by
techniques such as drill-down, data
mining and data discovery
Query tool is one of the tools used for
diagnostic analysis. InetSoft's BI query
tool is an example
Why did it happen?Q2
Types of big data analytics

51. Descriptive analytics
Diagnostic analytics
An ecommerce company’s report shows that their
sales have reduced although customers are
adding products to the cart
Types of big data analytics

52. Descriptive analytics
Diagnostic analytics
An ecommerce company’s report shows that their
sales have reduced although customers are
adding products to the cart
Why did we make fewer
online sales although we
had good marketing?
Types of big data analytics

53. Descriptive analytics
Diagnostic analytics
An ecommerce company’s report shows that their
sales have reduced although customers are
adding products to the cart
Why did we make fewer
online sales although we
had good marketing?
A lot of things could have gone wrong :
• The form didn’t load correctly
• The shipping fee was too high
• Not enough payment options available
Types of big data analytics

54. Descriptive analytics
Diagnostic analytics
An ecommerce company’s report shows that their
sales have reduced although customers are
adding products to the cart
Why did we make fewer
online sales although we
had good marketing?
A lot of things could have gone wrong :
• The form didn’t load correctly
• The shipping fee was too high
• Not enough payment options available
Using diagnostic analytics, we can find out the reason
why this happened
Types of big data analytics

55. Big data analytics
Descriptive analytics Diagnostic
analytics
Predictive
analytics
Prescriptive analytics
What has happened? Why did it happen? What will happen? What is the
solution?
Types of big data analytics

56. Descriptive analytics
Descriptive analyticsPredictive analytics Looks into the historical and present data to
make predictions of the futureWhat will happen?Q3
Types of big data analytics

57. Descriptive analytics
Descriptive analyticsPredictive analytics
This type of analytics uses data
mining, artificial intelligence and
machine learning to analyze current
data to make predictions about future
Looks into the historical and present data to
make predictions of the futureWhat will happen?Q3
Types of big data analytics

58. Descriptive analytics
Descriptive analyticsPredictive analytics
It works on predicting the customer
trends, market trends and so on. This
analysis works on probability
This type of analytics uses data
mining, artificial intelligence and
machine learning to analyze current
data to make predictions about future
Looks into the historical and present data to
make predictions of the futureWhat will happen?Q3
Types of big data analytics

59. Descriptive analyticsPredictive analytics
Using predictive analytics, the company uses all the historical payment data, the
user behavior data and builds an algorithm which predicts fraudulent activities
Paypal determines what kind of precautions they have to take to protect their
clients against fraudulent transactions
Looks into the historical and present data to
make predictions of the futureWhat will happen?Q3
Types of big data analytics

60. Big data analytics
Descriptive analytics Diagnostic
analytics
Predictive
analytics
Prescriptive analytics
What has happened? Why did it happen? What will happen? What is the
solution?
Types of big data analytics

61. Descriptive analyticsPrescriptive analytics
This type of analytics prescribes the
solution to a particular problemWhat is the solution?Q4
Types of big data analytics

62. Descriptive analytics
Descriptive analyticsPrescriptive analytics
Prescriptive analytics works with
both descriptive and predictive
analytics
This type of analytics prescribes the
solution to a particular problemWhat is the solution?Q4
Types of big data analytics

63. Descriptive analytics
Descriptive analyticsPrescriptive analytics
Prescriptive analytics works with
both descriptive and predictive
analytics
Most of the times prescriptive analytics
relies on artificial intelligence and
machine learning
This type of analytics prescribes the
solution to a particular problemWhat is the solution?Q4
Types of big data analytics

64. Descriptive analytics
Descriptive analyticsPrescriptive analytics
Business rules, algorithms, computational
modelling procedures are used in
prescriptive analytics
Prescriptive analytics works with
both descriptive and predictive
analytics
Most of the times prescriptive analytics
relies on artificial intelligence and
machine learning
This type of analytics prescribes the
solution to a particular problemWhat is the solution?Q4
Types of big data analytics

65. Descriptive analyticsPrescriptive analytics
This type of analytics prescribes the
solution to a particular problemWhat is the solution?Q4
Types of big data analytics

66. Descriptive analyticsPrescriptive analytics
Prescriptive analytics can be used to maximize an airline’s profit
This type of analytics prescribes the
solution to a particular problemWhat is the solution?Q4
Types of big data analytics

67. Descriptive analyticsPrescriptive analytics
This analytics is used to build an algorithm that will automatically adjust the flight
fares based on numerous factors, including customer demand, weather,
destination, holiday seasons and oil prices
Prescriptive analytics can be used to maximize an airline’s profit
This type of analytics prescribes the
solution to a particular problemWhat is the solution?Q4
Types of big data analytics

68. What’s in it for you?
Big Data Challenges
What is HDFS?
HDFS Cluster Architecture
HDFS Data Blocks
Data Node Failure
Rack Awareness
General Architecture of HDFS
Read/Write Mechanism
Tools used in big data analytics

69. Tools used in big data analytics

70. Hadoop helps in storing and
analyzing big data
Tools used in big data analytics

71. MongoDB is used on datasets that
change frequently
Tools used in big data analytics

72. Talend is a tool used for data
integration and management
Tools used in big data analytics

73. It is a distributed database that is
used for handling chunks of data
Tools used in big data analytics

74. It is used for real time
processing and analyzing large
amount of data
Tools used in big data analytics

75. It is an open source real time
computational system
Tools used in big data analytics

76. It is a distributed streaming platform
that is used for fault tolerant storage
Tools used in big data analytics

77. What’s in it for you?
Big Data Challenges
What is HDFS?
HDFS Cluster Architecture
HDFS Data Blocks
Data Node Failure
Rack Awareness
General Architecture of HDFS
Read/Write Mechanism
Big data application domains

78. Ecommerce
Predicting customer trends, optimizing price are few of the ways e-
commerce uses big data analytics
Big data application domains

79. Marketing
Ecommerce
Big data analytics helps in driving high ROI marketing campaigns
which result in better sales
Big data application domains

80. Education
Marketing
Ecommerce
New courses are developed based on the market requirement using
big data analytics
Big data application domains

81. Education
Marketing
Ecommerce
Healthcare
With the help of a patient’s medical history, big data analytics is used
to predict how likely they are to have health issues
Big data application domains

82. Education
Marketing
Ecommerce
Media and entertainment
Healthcare
Big data analytics is used to understand the demand of shows,
movies, songs and so on to deliver a personalized recommendation
list to its users
Big data application domains

83. Education
Marketing
Ecommerce
Media and entertainment
Banking
Healthcare
Customer income and spend patterns help in predicting the customer
likelihood for choosing various banking offers like loans, credit card
schemes and so on
Big data application domains

84. Education
Marketing
Ecommerce
Media and entertainment
Banking
Telecommunications
Healthcare
Big data analytics is used to forecast network capacity and improve
customer experience in the field of telecommunication
Big data application domains

85. Education
Marketing
Ecommerce
Media and entertainment
Banking
Telecommunications
Healthcare
Big data analytics is used to forecast network capacity and improve
customer experience in the field of telecommunication
Big data application domains

86. Education
Marketing
Ecommerce
Media and entertainment
Banking
Telecommunications
Healthcare
Government
Big data application domains

87. Education
Marketing
Ecommerce
Media and entertainment
Banking
Telecommunications
Healthcare
Government
Big data analytics helps governments in law enforcement
Big data application domains

88. Education
Marketing
Ecommerce
Media and entertainment
Banking
Telecommunications
Healthcare
Government
Big data analytics helps governments in law enforcement
In Durham, the police department was able to reduce the
crime rate using big data analytics
Big data application domains

89. Key Takeaways