Big Data Lecture Notes: Planning to become a Big Data professional. You can avail the best books, which include a comprehensive study plan, all-important information and timetable along with Big Data Lecture Notes. Here, you can get the Pdf Download links along with more details that are required for your effective exam preparation. Students will get information about the latest syllabus, reference books and important questions list for Big Data Lecture Notes.
The Big Data Lecture Notes and Study Materials are the essential study resources, and the reference materials nurture and develop better preparation and assist students in obtaining good grades. Students can refer to the Big Data Lecture Notes as per the latest updated syllabus from this article.
Graduates can avail of the Big Data Lecture Notes PDFs and Reference Books from this article and exceed their preparation with the best study resources and obtain better scores.
- Big Data Lecture Notes PDF and Study Material Free Download
- Big Data Lecture Notes Reference Books
- Big Data Lecture Notes Syllabus
- Big Data Lecture Notes List of Important Questions
- FAQs on Big Data Lecture Notes
- Conclusion
Introduction to Big Data Lecture Notes
Hadoop training material pdf: Big data is a field that undertakes measures to analyze or contrarily deal with data sets that are too comprehensive or complicated to be bartered with by conventional data-processing application software.Data with many rows suggest greater analytical power, while data with higher complexity may guide to a higher false discovery scale.. Big data challenges consist of capturing data, search, sharing, transfer, data storage, data analysis, updating, information privacy, visualization, querying and data source. Big Data often involves data with sizes that surpass the capacity of traditional software to process within adequate value and time.
Big Data Lecture Notes PDF and Study Material Free Download
Big data study material pdf: Candidates pursuing Big Data Courses can avail from the Big Data Lecture Notes and Study Materials updated in this article. Students can increase their preparation with the ideal implementation that helps them secure good grades.
Students can download the notes and study materials and use them as a reference during the revision or preparation process. Application of the Big Data Lecture Notes and Study Materials sources of reference will help graduates get a better idea of the concepts and topics and elevate their grade sheet.
The students can refer and use the Big Data Lecture Notes PDF and Study Materials as a reference. Students pursuing Big Data Courses can download PDF notes.
Big Data Lecture Notes Reference Books
Reference books for Big Data are an essential source of information. It provides necessary information about the topics with essential explanations. Students can develop a solid base when they refer to books that subject experts’ recommend.
Candidates would understand the topics more precisely if they consult the latest version that includes the updated syllabus. Here is a list of the best-recommended books for Big Data Notes.
- “Big Analytics, Big Data, : Analytic Trends for Today’s Businesses and Emerging Business Intelligence”, Michelle Chambers, Michael Minelli and Ambiga Dhiraj, Wiley, 2013.
- Tom Whites, 3rd Edition, O’Reilly – Hadoop: The Definitive Guide.
- Hadoop Practice by Alex Holmes Manning publ.
- Chuck Lam – Hadoop in Action, MANNING Publication.
- Golfarelli and Rizzi – Modern Principles and Methodologies: Data Warehouse Design , McGraw-Hill, 2009
- Eric Sammer, “Hadoop Operations”, O’Reilley, 2012
- E. Capriolo, D. Wampler, and J. Rutherglen, “Programming Hive”, O’Reilley, 2012
- “HBase: The Definitive Guide” Lars George, O’Reilley, 2011.
- Reilley and Eben Hewitt-“The Definitive Guide : Cassandra” 2010.
- “Programming Pig”, Alan Gates, O’Reilley, 2011.
Big Data Lecture Notes Syllabus
The best way to commence your preparation for the Big Data Courses is to understand the syllabus and the topics of the subject. Keeping in mind every student’s requirements, we have presented a comprehensive view of the Big Data Syllabus.
The Syllabus of Big Data courses aims to present the students with a brief idea of what to study, the unit-wise breakup of the topics and how to allot time to each subject.
Students must ensure to cover all the topics and concepts before attempting the exams to ensure that the paper is easy and stress-free at the time of the exam. Graduates must make sure that they are aware of the course Syllabus to prevent unnecessary waste of time on unwanted topics.
Here is an updated list of topics of the Big Data Lecture Notes Syllabus-
| UNIT I
UNDERSTANDING BIG DATA |
What is big data – why big data – convergence of key trends – unstructured data – industry examples of big data – big data and algorithmic trading – big data and healthcare – big data in medicine – advertising and big data – big data technologies – web analytics – big data and marketing -open source technologies – cloud and big data – fraud and big data risk and big data – credit risk management – introduction to Hadoop – mobile business intelligence – Crowd sourcing analytics inter and trans firewall analytics lecture Notes |
| UNIT II NOSQL DATA MANAGEMENT |
NSQL Introduction – aggregate data models – key-value and
document data models – master-slave replication – peer peer replication – relationships – graph databases – schemaless databases – materialized views – distribution models consistency – consistency relaxing – version stamps – map-reduce partitioning and combining – composing map-reduce calculations- – sharding – sharding and lication |
| UNIT III
BASICS OF HADOOP |
Data format – analyzing data with Hadoop – scaling out – data integrity – compression – serialization – Avro – file-based data structures- Hadoop streaming – Hadoop pipes – design of Hadoop distributed file system (HDFS) – HDFS concepts – Java interface – data flow – Hadoop 1/0 |
| UNIT IV
MAPREDUCE APPLICATIONS |
MapReduce workflows -reduce and YARN – unit tests with MRUnit – test data and local tests – anatomy of MapReduce job run – classic Map-reduce – YARN – failures in classic Map- job scheduling – shuffle and sort – task execution – MapReduce types – input |
| UNIT V
HADOOP RELATED TOOLS |
HiveQL data definition HiveQL data manipulation – Cassandra data model – cassandra examples – cassandra clients – Hadoop integration Pig – Grunt – pig data model -Hbase – data model and implementations – Hbase clients – Hbase examples praxis.Cassandra -Pig Latin – developing and testing Pig Latin scripts. Hive – data types and file formats – HiveQL queries |
Big Data Lecture Notes List of Important Questions
Candidates pursuing Big Data Courses can refer to the list of all the essential questions stated below for the Big Data Lecture Notes. All the assigned questions are aimed to help the aspirants to excel in the examination. Here is a list of some essential questions that will help the students to have a better understanding of the subject.
- How is Big Data related to Hadoop?
- Define YARN and HDFS, and talk about their respective elements.
- What is commodity hardware?
- Describe the term FSCK briefly.
- What is the aim of the JPS command in Hadoop?
- Define the different commands for starting up and shutting down Hadoop Daemons.
- Name some of the data management tools used with Edge Nodes in Hadoop?
- How does Big Data add content to businesses?
- Elaborate on the methods that overwrite the replication in HDFS.
- Define the three forms in which you can run Hadoop.
- Define Rack Awareness in Hadoop.
- Name the framework configuration parameters of MapReduce.
- Describe the purpose of a JobTracker.
- How can you manage abstaining values in Big Data?
Frequently Asked Questions on Big Data Notes
Question 1 :
What are the five V’s in Big Data?
Answer :
The five V’s in Big Data are volume, variety, velocity, veracity and value.
Question 2 :
What are the elements of Big Data?
Answer :
The main elements of Big data are
- Machine Learning
- Natural Language Processing
- Business Intelligence
- Cloud Computing
Question 3.
How is big data created?
Answer :
The amount of big data generated originates from three primary sources: machine data, social data and transactional data.
Question 4.
What is Data Ingestion in Big Data?
Answer :
In Data Ingestion, we gather data from varied sources, be it business documents, social media platforms, log files, or anything relevant to the business. Data can either be extorted by real-time streaming or in batch jobs.
Conclusion
The Big Data Lecture Notes and Study Materials written above are aimed to assist the students at the time of exam preparations. They are reliable and have authoritative references focused on helping students and improving their knowledge and understanding of the subject during the time of preparation of the exam. Students can refer and practice from the provided notes for Big Data curriculum and essential questions from this article.