Data Analytics (MCA)

Elective-3: data analysis process, statistical methods, data mining, stream analytics and Hadoop-based tools.

6 महीनेअवधि 5Chapters29टॉपिक

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01Unit 1: Introduction to Data Analytics 6 टॉपिक

Sources and nature of data
Structured, semi-structured and unstructured data
Characteristics of big data: the Vs
Analysis versus reporting; modern analytic tools
Data analytics life cycle: discovery, preparation, model planning, model building, communicating results, operationalisation
Key roles in an analytics project

02Unit 2: Data Analysis Methods 6 टॉपिक

Regression modelling
Multivariate analysis
Bayesian modelling and inference
Support vector machines and kernel methods
Time series analysis
Principal component analysis and rule induction

03Unit 3: Mining Data Streams 6 टॉपिक

Stream data model and architecture
Sampling data in a stream
Filtering streams: Bloom filter
Counting distinct elements: Flajolet-Martin algorithm
Counting ones in a window: DGIM algorithm
Decaying windows and real-time analytics applications

04Unit 4: Frequent Itemsets and Clustering 6 टॉपिक

Market basket analysis
Support, confidence and association rules
Apriori algorithm
PCY and SON algorithms
Clustering: k-means and hierarchical
CLIQUE and PROCLUS; clustering in non-Euclidean spaces

05Unit 5: Frameworks and Visualisation 5 टॉपिक

Hadoop, HDFS and MapReduce
Pig and Hive
HBase, NoSQL databases and sharding
Data visualisation techniques
Introduction to R for analytics

परिचय

आप यह कर पाएँगे

Classify data sources and describe big data characteristics and the data analytics life cycle
Apply regression, multivariate analysis, Bayesian methods and PCA to data
Explain stream data models and algorithms such as Bloom filters, Flajolet-Martin and DGIM
Find frequent itemsets and association rules using Apriori and its variants
Group data using k-means, hierarchical and grid-based clustering
Describe Hadoop, MapReduce, Pig, Hive, HBase and NoSQL tools and visualise results

यह किसके लिए है

MCA students of Semester 4 (AKTU, Lucknow)
Students aiming for data analyst or big data roles

आपको क्या चाहिए

Basic statistics and probability
Database and programming knowledge from earlier semesters

सवाल

Which syllabus does this Data Analytics course follow?

It follows the AKTU (Lucknow) MCA syllabus for Semester 4. If your own university's syllabus differs, the centre follows your university's syllabus and unit order.

This is an elective. What if my college offers a different elective?

The centre teaches the elective your college has allotted; this course covers the AKTU syllabus of this elective.

Do we use real tools?

Yes. Examples are shown in Python / R and on a small Hadoop setup so that students see each method working.

Are numericals asked?

Yes. Support and confidence, Apriori, Flajolet-Martin and regression problems are practised step by step.