This document discusses database management systems (DBMS). A DBMS is software that allows for the storage, management, and retrieval of large amounts of data. It provides benefits like data independence, concurrency control, crash recovery, and security. A DBMS typically uses a multi-layer architecture and implements concepts like transactions, locking, and logging to ensure data integrity and consistency when multiple users access the database concurrently. Database administrators are responsible for designing database schemas and tuning the system to meet evolving needs.
Temporal database, Multimedia database, Access control, Flow controlPooja Dixit
Temporal database, There are mainly two different notions of time, Multimedia database , Content of Multimedia Database management system :, Types of multimedia applications :
Summary:
A database, often abbreviated as DB, is a collection of information organized in such a way that a computer program can quickly select desired pieces of data.
You can think of a traditional database as an electronic filing system, organized by fields, records, and files.
A field is a single piece of information; a record is one complete set of fields; a file is a collection of records.
Temporal database, Multimedia database, Access control, Flow controlPooja Dixit
Temporal database, There are mainly two different notions of time, Multimedia database , Content of Multimedia Database management system :, Types of multimedia applications :
Summary:
A database, often abbreviated as DB, is a collection of information organized in such a way that a computer program can quickly select desired pieces of data.
You can think of a traditional database as an electronic filing system, organized by fields, records, and files.
A field is a single piece of information; a record is one complete set of fields; a file is a collection of records.
For more detail visit : https://techforboost.blogspot.com
https://youtu.be/OcQZVc7pZZA
A multimedia database is a database that include one or more primary media file types such as .txt (documents), .jpg (images), .swf (videos), .mp3 (audio), etc.
Database management system full theory portion is covered. It's helpful to students who are in any management courses.all the best to all of you, this ppt might be helpful for you.Database management system full theory portion is covered. It's helpful to students who are in any management courses.all the best to all of you, this ppt might be helpful for you.Database management system full theory portion is covered. It's helpful to students who are in any management courses.all the best to all of you, this ppt might be helpful for you.Database management system full theory portion is covered. It's helpful to students who are in any management courses.all the best to all of you, this ppt might be helpful for you.
For more detail visit : https://techforboost.blogspot.com
https://youtu.be/OcQZVc7pZZA
A multimedia database is a database that include one or more primary media file types such as .txt (documents), .jpg (images), .swf (videos), .mp3 (audio), etc.
Database management system full theory portion is covered. It's helpful to students who are in any management courses.all the best to all of you, this ppt might be helpful for you.Database management system full theory portion is covered. It's helpful to students who are in any management courses.all the best to all of you, this ppt might be helpful for you.Database management system full theory portion is covered. It's helpful to students who are in any management courses.all the best to all of you, this ppt might be helpful for you.Database management system full theory portion is covered. It's helpful to students who are in any management courses.all the best to all of you, this ppt might be helpful for you.
Importance of Data - Where to find it, how to store, manipulate, and characterize it
Artificial Intelligence (AI)- Introduction to AI & ML Technologies/ Applications
Machine Learning (ML), Basic Machine Learning algorithms.
Applications of AI & ML in Marketing, Sales, Finance, Operations, Supply Chain
& Human Resources Data Governance
Legal and Ethical Issues
Robotic Process Automation (RPA)
Internet of Things (IoT)
Cloud Computing
A distributed system in its most simplest definition is a group of computers working together as to
appear as a single computer to the end-user. These machines have a shared state, operate
concurrently and can fail independently without affecting the whole system’s uptime.
This is in line with ever-growing technological expansion of the world, distributed systems are
becoming more and more widespread. Take a look at the increasing number of available
computer technologies/innovation around, this is sporadically increasing, and this result in
intense computational requirement.
Yeah, Moore’s law proposed more computing power by fitting more transistors (which
approximately doubles every two years) into a simple chip using cost-efficient approach - cool,
but over the past 5 years, there has been little deviation from this - ability to scale horizontally
and not just vertically alone.
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
Opendatabay - Open Data Marketplace.pptxOpendatabay
Opendatabay.com unlocks the power of data for everyone. Open Data Marketplace fosters a collaborative hub for data enthusiasts to explore, share, and contribute to a vast collection of datasets.
First ever open hub for data enthusiasts to collaborate and innovate. A platform to explore, share, and contribute to a vast collection of datasets. Through robust quality control and innovative technologies like blockchain verification, opendatabay ensures the authenticity and reliability of datasets, empowering users to make data-driven decisions with confidence. Leverage cutting-edge AI technologies to enhance the data exploration, analysis, and discovery experience.
From intelligent search and recommendations to automated data productisation and quotation, Opendatabay AI-driven features streamline the data workflow. Finding the data you need shouldn't be a complex. Opendatabay simplifies the data acquisition process with an intuitive interface and robust search tools. Effortlessly explore, discover, and access the data you need, allowing you to focus on extracting valuable insights. Opendatabay breaks new ground with a dedicated, AI-generated, synthetic datasets.
Leverage these privacy-preserving datasets for training and testing AI models without compromising sensitive information. Opendatabay prioritizes transparency by providing detailed metadata, provenance information, and usage guidelines for each dataset, ensuring users have a comprehensive understanding of the data they're working with. By leveraging a powerful combination of distributed ledger technology and rigorous third-party audits Opendatabay ensures the authenticity and reliability of every dataset. Security is at the core of Opendatabay. Marketplace implements stringent security measures, including encryption, access controls, and regular vulnerability assessments, to safeguard your data and protect your privacy.
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
1. 1
Database Systems
I F F A T A R A
Dept. of Geomatics
Geographic Information System
GOM-311
2. 2
What is DBMS?
Need for information management
A very large, integrated collection of data.
Models real-world enterprise.
– Entities (e.g., students, courses)
– Relationships (e.g., John is taking CS662)
A Database Management System (DBMS) is a
software package designed to store and
manage databases.
3. 3
Why Use a DBMS?
Data independence and efficient access.
Data integrity and security.
Uniform data administration.
Concurrent access, recovery from crashes.
Replication control
Reduced application development time.
4. 4
Why Study Databases??
Shift from computation to information
– at the “low end”: access to physical world
– at the “high end”: scientific applications
Datasets increasing in diversity and volume.
– Digital libraries, interactive video, Human
Genome project, e-commerce, sensor networks
– ... need for DBMS/data services exploding
DBMS encompasses several areas of CS
– OS, languages, theory, AI, multimedia, logic
5. 5
Data Models
A data model is a collection of concepts for
describing data.
A schema is a description of a particular
collection of data, using the a given data
model.
The relational model of data is the most widely
used model today.
– Main concept: relation, basically a table with rows
and columns.
– Every relation has a schema, which describes the
columns, or fields.
6. 6
Levels of Abstraction
Many views, single
conceptual (logical) schema
and physical schema.
– Views describe how users
see the data.
– Conceptual schema defines
logical structure
– Physical schema describes
the files and indexes used.
* Schemas are defined using DDL; data is modified/queried using DML.
8. 8
Example: University Database
Conceptual schema:
– Students(sid: string, name: string, login: string,
age: integer, gpa:real)
– Courses(cid: string, cname:string, credits:integer)
– Enrolled(sid:string, cid:string, grade:string)
Physical schema:
– Relations stored as unordered files.
– Index on first column of Students.
External Schema (View):
– Course_info(cid:string, enrollment:integer)
9. 9
Data Independence
Applications insulated from how data is
structured and stored.
Logical data independence: Protection from
changes in logical structure of data.
Physical data independence: Protection from
changes in physical structure of data.
* One of the most important benefits of using a DBMS!
10. 10
Concurrency Control
Concurrent execution of user programs is
essential for good DBMS performance.
– Because disk accesses are frequent, and relatively
slow, it is important to keep the CPU humming by
working on several user programs concurrently.
Interleaving actions of different user programs
can lead to inconsistency: e.g., check is cleared
while account balance is being computed.
DBMS ensures such problems don’t arise: users
can pretend they are using a single-user system.
11. 11
Transaction: An Execution Unit of a DB
Key concept is transaction, which is an atomic
sequence of database actions (reads/writes).
Each transaction, executed completely, must leave
the DB in a consistent state if DB is consistent when
the transaction begins.
– Users can specify some simple integrity constraints on
the data, and the DBMS will enforce these constraints.
– Beyond this, the DBMS does not really understand the
semantics of the data. (e.g., it does not understand how
the interest on a bank account is computed). Why not?
– Thus, ensuring that a transaction (run alone) preserves
consistency is ultimately the user’s responsibility!
12. 12
Scheduling Concurrent Transactions
DBMS ensures that execution of {T1, ... , Tn} is
equivalent to some serial execution T1’ ... Tn’.
– Before reading/writing an object, a transaction requests
a lock on the object, and waits till the DBMS gives it the
lock. All locks are released at the end of the transaction.
(Strict 2PL locking protocol.)
– Idea: If an action of Ti (say, writing X) affects Tj (which
perhaps reads X), one of them, say Ti, will obtain the
lock on X first and Tj is forced to wait until Ti completes;
this effectively orders the transactions.
– What if Tj already has a lock on Y and Ti later requests a
lock on Y? What is it called? What will happen?
13. 13
Ensuring Atomicity
DBMS ensures atomicity (all-or-nothing property)
even if system crashes in the middle of a Xact.
Idea: Keep a log (history) of all actions carried out
by the DBMS while executing a set of Xacts:
– Before a change is made to the database, the
corresponding log entry is forced to a safe location.
(WAL protocol.)
– After a crash, the effects of partially executed
transactions are undone using the log. (Thanks to WAL, if
log entry wasn’t saved before the crash, corresponding
change was not applied to database!)
14. 14
The Log
The following actions are recorded in the log:
– Ti writes an object: the old value and the new value.
u Log record must go to disk before the changed page!
– Ti commits/aborts: a log record indicating this action.
Log records chained together by Xact id, so it’s easy to
undo a specific Xact (e.g., to resolve a deadlock).
Log is often duplexed and archived on “stable” storage.
All log related activities (and in fact, all CC related
activities such as lock/unlock, dealing with deadlocks
etc.) are handled transparently by the DBMS.
15. 15
Databases make these folks happy ...
End users and DBMS vendors
DB application programmers
– e.g. webmasters
Database administrator (DBA)
– Designs logical /physical schemas
– Handles security and authorization
– Data availability, crash recovery
– Database tuning as needs evolve
Must understand how a DBMS works!
16. 16
Structure of a DBMS
A typical DBMS has a
layered architecture.
The figure does not
show the concurrency
control and recovery
components.
This is one of several
possible architectures;
each system has its own
variations.
Query Optimization
and Execution
Relational Operators
Files and Access Methods
Buffer Management
Disk Space Management
DB
These layers
must consider
concurrency
control and
recovery
17. 17
Summary
DBMS used to maintain, query large datasets.
Benefits include recovery from system crashes,
concurrent access, quick application development,
data integrity and security.
Levels of abstraction give data independence.
A DBMS typically has a layered architecture.
DBAs hold responsible jobs and are well-paid!
DBMS R&D is one of the broadest & mature areas
in information system sector.