Design, implement and implement scalable solutions

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Reference no: EM134002613

Big Data

Assessment - Tableau & Splunk Project

Problems to be addressed in the report

Higher education institutions and organizations have high volumes of heterogenous data with volume, velocity, variety, variability and value. You will design, implement and implement scalable solutions to help with strategic and operational decision making for student information systems (student retention, course viability, resource allocation)

Part A: Scenario: Multi Campus university big data Analytics

A university operating across multiple campuses in Australia processes:
10+ years of student enrolment data
Learning Management System (LMS) logs
Financial records
Attendance and engagement data
Demographic information
University is experiencing issues like; Slow retention analysis, no predictive attrition modelling, Fragmented reporting systems, no real-time academic performance insights, Increasing data volume each semester
Your responsibilities include analyzing the data, applying any required transformations, and facilitating the extraction of valuable insights from the processed data. No AI shortcuts — Get genuine assignment help from experienced, real tutors.

You must design and implement a scalable high volume data solution.

Dataset: Use any Student data set from Kaggle

Task 1: Problem analysis
5Vs of Big Data

Data growth challenges
Processing bottlenecks
Limitations of traditional RDBMS systems
Batch vs real-time requirements

Task 2: Distributed processing
Load large-scale dataset (Kaggle student dataset or simulated multi-year dataset)
Perform distributed transformations:
Cleaning & preprocessing
Aggregations
Cohort analysis
Campus-wise enrolment growth
Implement: Partitioning strategy, Caching strategy

Task 3: Visual analytics using Tableau
Create a dashboard showing:
Retention by program and enrolments
Demographic breakdown
Performance analysis & distribution

The research report must have the format:

Table of contents
Institute detail/information (Executive Summary)
Problem Identification
Implementation
Tableau visualisation report
Analysis and Discussion
Recommendations
References
(include diagrams whenever possible big data architecture) Part B:
In this part of the assessment, you must analyze the log details of the Student Enrollment System in Australia with Splunk

Execute a search to identify all failed login attempts in the last 24 hours. Export the results as a report.
Identify the top 10 IP addresses generating the highest number of events. Present the results in tabular format.
Create a query to calculate the average response time per host.
Filter events that occurred between two specific timestamps and display only the host and source fields.
Take a screenshot of your ‘Activity Jobs Menu' detailing the current job saved with expiration date
Take a screenshot of your search history. Set a filter to narrow down your search results.

Show where selected fields are, interesting fields and all located. How do you use fields to perform a search.
How do you add time range when performing search.

This assignment consists of two integrated parts:

Part A: Tableau Research Report (Business Data Analysis)
Part B: Splunk Practical Exercises (Network Log Analysis)

Screenshot requirements:
Screenshots must clearly show the full Splunk interface (not cropped too tightly).
Your Student ID and the current date must be visible on every screenshot.
Screenshots should be pasted directly into the report under each task (a-h), followed by your short explanation.
Screenshots without Student ID visible will not be accepted.

Additional information regarding this Assessment:
Report document standards
Normal font is Calibri, size 11 point for the body of all documents with the text fully justified.
Headings should not exceed 14 points in size except on a title page where larger fonts are appropriate for the title of a report.
Documents should use 1.15 spacing within a paragraph and have an 8-point space between paragraphs.
Footers should be created on the report that includes a page number.
Up to 15% of the Report contents may be quoted or paraphrased from other sources provided you with knowledge and cite the original source of the material you use.
Use IEEE referencing all quoted or paraphrased material.

Reference no: EM134002613

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