Pay with your ATM Card, USSD code or Bank Transfer to get immediate access to the download links page (download links will also be sent to your email address) for SS3 First and Third Term Data Processing lesson notes. Payments are securely handled by Paystack. [select-faq faq_id='5273']
Pay with your ATM Card, USSD code or Bank Transfer to get immediate access to the download links page (download links will also be sent to your email address) for SS3 First and Third Term Data Processing lesson notes. Payments are securely handled by Paystack.
Our lesson notes are downloaded in Ms-Word Format.
HOW TO PLACE ORDER:
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Contact the admin on Whatsapp via 08075777704 (Click here to send Whatsapp message) or via Email on email@example.com if you missed the download link for any reason (this rarely happens) or have difficulty placing order.
These lesson notes cover the following topics for SS3 First and Second Term Data Processing:
- INDEXES:- Definition, Clustered versus Unclustered indexes
- INDEXES:- Dense versus Sparse, Primary and Secondary Indexes, Indexes using Composite Search Keys
- MAINTENANCE OF COMPUTER:- Computer Hardware, Process Of Maintaining Hardware
- MAINTENANCE OF COMPUTER:- Procedure for Software Maintenance, Software for Hardware and Software Maintenance
- DATABASE SECURITY:- Definition and Explanation, Access Control and Encryption
- DATABASE SECURITY:- Importance, Integrity and Availability, the Role of a Database Administrator
- CRASH RECOVERY:- Introduction to ARIES, other Recovery Related Data Structure.
- CRASH RECOVERY:- Definition and Explanation of Check Pointing, Explain Media Recovery
REFERENCE TEXTBOOK: UNDERSTANDING DATA PROCESSING for SENIOR SECONDARY SCHOOLS BY: DINEHIN VICTORIA
SECOND TERM EXCEPT
A parallel database system seeks to improve performance through parallelization of various operations, such as loading data, building indexes and evaluating queries. Although data may be stored in a distributed fashion, the distribution is governed solely by performance considerations. Parallel databases improve processing and input/output speeds by using multiple CPUs and disks in parallel. Centralized and client–server database systems are not powerful enough to handle such applications. In parallel processing, many operations are performed simultaneously, as opposed to serial processing, in which the computational steps are performed sequentially.
Architectures of parallel Database
Shared memory architecture
Where multiple processors share the main memory (RAM)space but each processor has its own disk (HDD). If many processes run simultaneously, the speed is reduced, the same as a computer when many parallel tasks run and the computer slows down.
Shared disk architecture
Where each node has its own main memory, but all nodes share mass storage, usually a storage area network. In practice, each node usually also has multiple processors.
Shared nothing architecture
Where each node has its own…