#1 Best Selling IGNOU Assignments in All Available in Market
Bought By: 1494 Students
Rating:
Get IGNOU MCS-226 Assignments Soft Copy ready for Download in PDF for (January 2024 - July 2024) in English Language.
Are you looking to download a PDF soft copy of the Solved Assignment MCS-226 - Data Science and Big Data? Then GullyBaba is the right place for you. We have the Assignment available in English language.
This particular Assignment references the syllabus chosen for the subject of Computer Application, for the January 2024 - July 2024 session. The code for the assignment is MCS-226 and it is often used by students who are enrolled in the MCA (Revised) Degree.
Once students have paid for the Assignment, they can Instantly Download to their PC, Laptop or Mobile Devices in soft copy as a PDF format. After studying the contents of this Assignment, students will have a better grasp of the subject and will be able to prepare for their upcoming tests.
Q1: What is Exploratory Data Analysis (EDA) and why is it important in the data science workflow? What are the key components of the data science process?
Q2: Discuss the implications of hypothesis testing results in decision-making. Provide examples of realworld situations where statistical hypothesis testing is commonly used.
Q3: What is data preprocessing, and why is it a crucial step in the data science workflow? Why is it important to identify and handle outliers in a dataset during data preprocessing?
Q4: Discuss the significance of the three Vs (Volume, Velocity, Variety) in the context of big data. Provide examples of each of the three Vs in real-world scenarios. How does MapReduce facilitate parallel processing of large datasets? Explain the functionality of the Map function in the MapReduce paradigm with the help of an example.
Q5: Explain the purpose of Apache Hive in the Hadoop ecosystem. How does Spark address limitations of the traditional MapReduce model?
Q6: Define NoSQL databases and explain the primary motivations behind their development. Provide examples of scenarios where each type of NoSQL database is suitable.
Q7: How does collaborative filtering contribute to enhancing user experience and engagement in recommendation systems? Provide examples of industries or platforms where collaborative filtering is widely used.
Q8: What is a Data Stream Bloom Filter? Explain its primary purpose in data stream processing. Also, introduce the Flajolet-Martin Algorithm and its role in estimating the cardinality of a data stream.
Q9: Describe the role of link analysis in the PageRank algorithm. How are links between web pages interpreted in the context of PageRank?
Q10: Explain the concept of decision trees in classification. Provide an example of building and visualizing a decision tree using R. How can K-means clustering be applied to a dataset in R?
Q1: Describe data science. What uses does it have? In the context of data analysis, define the terms descriptive, exploratory, and predictive.
Q2: Discuss the need for Statistical Hypothesis Testing with the help of an example. Explain types of Errors in Hypothesis Testing.
Q3: Why do need Data Preprocessing? Explain different Quality Measures in Data Preprocessing. Discuss the different strategies for Data Handling.
Q4: A class has 25 students. Create a data set of marks of the students in Mathematics out of a maximum of 50 marks. Discuss and draw, which chart will be best for Visualization & Interpretation. Justify your reasons in support of your answer.
Q5: What is the need for Big data? Explain 3 V’s. Discuss the master/slave Hadoop architecture with the help of an example.
Q6: Explain the concept of Map-Reduce with the help of an example.
Q7: What is the purpose of using Apache SPARK, HIVE and HBASE, explain with supporting example.
Q8: What is NoSQL database? Discuss how does a Column Database and Document database Work? List and briefly discuss Graph database examples.
Q9: Explain the Jaccard similarity of sets with the help of an example. What are the ways offinding similarity between two documents? Also, define the term collaborative filtering.
Q10: Explain Data Stream Bloom filter with the help of an example. Why do we need for Bloom filter? Discuss the working of Bloom filter. Explain the Flajolet-Martin algorithm.
Q11: What is PageRank? Discuss the basic principle of flow model in PageRank. Explain different mechanisms of finding pagerank?
Q12: Explain the process and issues of the following: Advertising on web, Recommendation system, Mining of social networks.
Q13: Discuss different data structures in R. Write program using R for the following tasks:
(i) Computation of income tax of a vector of size 10, consisting of the total annual income of 10 different persons. The tax computation should be 10%, if annual income is below 5 lakhs and 20% if it is above 5 lakhs.
(ii) Matrix addition, subtraction and multiplication
(iii) Finding inverse of a matrix
Q14: Create a sample data of the marks of 20 students in five different subjects using MSExcel. Discuss the different chart and graphing library packages supported by R programming language. Write programs using R programming language to create four different plots using this data.
Q15: Discuss the function supported in R language to differentiate between linear regression and multiple regression. Write programs using R programming language to support your answer with any sample data.
Q16: Discuss the Classification, Clustering and Association Rules with different examples. Explain, where we can use Random Forest Algorithm? Use R programming language to discuss Random Forest Algorithm.
The IGNOU open learning format requires students to submit study Assignments. Here is the final end date of the submission of this particular assignment according to the university calendar.
Here are the PDF files that you can Download for this Assignment. You can pick the language of your choice and see other relevant information such as the Session, File Size and Format.
In this section you can find other relevant information related to the Assignment you are looking at. It will give you an idea of what to expect when downloading a PDF soft copy from GullyBaba.
In addition to this Assignment, there are also other Assignments related to the MCA (Revised) Computer Application you are preparing for. Here we have listed other Assignments that were bought along with this one.