This document contains three summaries of assignments related to big data analytics: 1) A case study on ACID properties in bank account transactions, focusing on how atomicity ensures transactions are processed in their entirety or not at all. 2) A fill-in-the-blank quiz on concepts in big data analytics, testing knowledge of terms like unstructured data, JSON, data types, and consistency models. 3) Three crossword puzzles related to big data analytics terminology and techniques.

1. BIG DATA ANALYTICS Tutorial Assignment - 1 Date: 21-10-2019
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Case Study of ACID properties in transaction of Bank Accounts
Submitted by: Submitted to:
Shweta M P Dr. S.M. Hatture
M.Tech 1st Semester Dept ofComputer Science & Engg
Dept ofComputer Science & Engg BEC, Bagalkot
BEC, Bagalkot
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Introduction
The transactions in any Fund transfer or Banking includes money transfer and this includes
transferring money from "Available" account to "Borrowed" account and visa-verse. These
transactions should be a single logical unit of work in order to maintain the consistency of database.
And to ensure the consistency of database certain rules should be followed which are called ACID
properties.
 ACID stand for,
-Atomicity
-Consistency
-Isolation
-Durability
- Atomicity: Atomicity means that a transaction must exhibit “all or nothing” behaviour.
- Consistency: Consistency refers to the state of data both before and after the transaction is
executed.
- Isolation: Isolation means that transactions can run at same time.
- Durability: Durability refers to the impact of an outage or failure on running transactions.
 ACID qualities contribute the ability of integrity.
Let's see how atomicity the first property of ACID is followed in any Banking transaction.
Example-
 Consider two transactions (Xacts):
 1st xact transfers $100 from B’s account to A’s
 2nd credits both accounts with 6% interest.
 Assume at first A and B each have $1000. What are the legal outcomes of running T1
and T2???
o $2000 *1.06 = $2120
 There is no guarantee that T1 will execute before T2 or vice-versa, if both are submitted
together. But, the net effect must be equivalent to these two transactions running serially
in some order.
 Legal outcomes: A=1166,B=954 or A=1160,B=960
 Consider a possible interleaved schedule:

2.  This is OK (same as T1;T2). But what about:
 Result: A=1166, B=960; A+B = 2126, bank loses $6
 The DBMS’s view of the second schedule:

3. BIG DATA ANALYTICS Tutorial Assignment -2 Date:
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Fill in the blanks type questions with answers in Big Data
Analytics
Submitted by: Submitted to:
Shweta M P Dr. S.M. Hatture
M.Tech 1st Semester Dept ofComputer Science & Engg
Dept ofComputer Science & Engg BEC, Bagalkot
BEC, Bagalkot
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1. White paper is example of _____________type of digital data.
Answer: Unstructured data
2. __________is used to transmit data between server and web application.
Answer: JSON
3. How sensitive is this data? States _____________ characteristics of data.
Answer: Context
4. Today’s big may be tomorrow’s_________.
Answer: Normal
5. Volume in big data deals with_____________.
Answer: Growth of data
6. _______implies every read fetches last writes.
Answer: Consistency
7. Variety deals with a wide range of _____________and __________.
Answer: data types, sources of data
8. __________is the science of extracting knowledge from data.
Answer: Data
9. Abbreviation of BASE__________________ consistency.
Answer: Basic Available Soft state Eventual
10. CAP theorem is impossible to provide the following ____________,__________and
____________.Any two of among are possible at a time.
Answer: Consistency, Availability and Partition tolerance
11. BASE is used in ________computing.
Answer: distributed
12. Big-Data analytics is all about a tight handshake between 3 communities:_______,_____ and
______.
Answer: IT, Business user and Data Scientist.

4. 13. A system that has achieved eventual consistency is said to have converged or achieved is called
as____.
Answer: replica convergence
14. _______________is analytics in use to derive direct business revenue.
Answer: Monetized analytics.
15. Abbreviation of UIMA ____________________
Answer: Unstructured Information Management Architecture
16. Responsibilities of Data Scientist are__________,__________ and _________
Answer: Data Management, Analytical Techniques and Business Analytics.
17. In __________ architecture, central memory is shared by multiple processors.
Answer: Shared Memory.
18. Predictive analytics helps to answer the questions like_____________
Answer: “What will happen?”, “Why will it happen?”
19. SMP is also referred as __________.
Answer: Tightly coupled Multiprocessing
20. Popular data mining algorithms are ___________,___________
Answer: Association rule mining, Regression mining.

5. BIG DATA ANALYTICS Tutorial Assignment -3 Date:
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Cross word puzzels in Big Data Analytics
Submitted by: Submitted to:
Shweta M P Dr. S.M. Hatture
M.Tech 1st Semester Dept ofComputer Science & Engg
Dept ofComputer Science & Engg BEC, Bagalkot
BEC, Bagalkot
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CROSS WORD PUZZLE 1
ANSWER

6. CROSS WORD PUZZLE 2
ANSWER

7. CROSS WORD PUZZLE 3
ANSWER