An overview of the Database Management System, various uses and applications of database, internal architecture of popular RDBMS servers and thier features
Database Terminology, Characteristics of Database, DBMS, Types of DBMS, Database Security and Recovery, Data Mining, Data Warehousing, Data Marts, SQL Overview, Java Database Connectivity, Indexes, Clustered and Non-Clustered Indexes, Failure Management with DB2 Cluster Services
Database Terminology, Characteristics of Database, DBMS, Types of DBMS, Database Security and Recovery, Data Mining, Data Warehousing, Data Marts, SQL Overview, Java Database Connectivity, Indexes, Clustered and Non-Clustered Indexes, Failure Management with DB2 Cluster Services
ADVANCE DATABASE MANAGEMENT SYSTEM CONCEPTS & ARCHITECTURE by vikas jagtapVikas Jagtap
The data that indicates the earth location (latitude & longitude, or height & depth ) of these rendered objects is known as spatial data.
When the map is rendered, objects of this spatial data are used to project the location of the objects on 2-Dimentional piece of paper.
The spatial data management systems are designed to make the storage, retrieval, & manipulation of spatial data (i.e points, lines and polygons) easier and natural to users, such as GIS.
While typical databases can understand various numeric and character types of data, additional functionality needs to be added for databases to process spatial data types.
These are typically called geometry or feature.
Prerequisies of DBMS
Course Objectives of DBMS
Syllabus
What is the meaning of data and database
DBMS
History of DBMS
Different Databases available in Market
Storage areas
Why to Learn DBMS?
Peoples who work with Databases
Applications of DBMS
ADVANCE DATABASE MANAGEMENT SYSTEM CONCEPTS & ARCHITECTURE by vikas jagtapVikas Jagtap
The data that indicates the earth location (latitude & longitude, or height & depth ) of these rendered objects is known as spatial data.
When the map is rendered, objects of this spatial data are used to project the location of the objects on 2-Dimentional piece of paper.
The spatial data management systems are designed to make the storage, retrieval, & manipulation of spatial data (i.e points, lines and polygons) easier and natural to users, such as GIS.
While typical databases can understand various numeric and character types of data, additional functionality needs to be added for databases to process spatial data types.
These are typically called geometry or feature.
Prerequisies of DBMS
Course Objectives of DBMS
Syllabus
What is the meaning of data and database
DBMS
History of DBMS
Different Databases available in Market
Storage areas
Why to Learn DBMS?
Peoples who work with Databases
Applications of DBMS
About the course:
This Oracle performance tuning online course is designed for the audience who want to learn basics and core concepts of Oracle PT. You will be learning about Introduction, basic tuning diagnostics, how to use automatic workload repository, defining of problems, how to create AWR baselines, monitoring of applications Etc. All Oracle performance tuning classes will be live and interactive.
Course Target:
Oracle performance tuning online training is designed to teach you fundamentals of PT.
Understand basic tuning diagnostics.
Learn how to use Automatic workload repository.
Obtain knowledge of using metrics and alerts.
Clear understanding of how to monitor applications.
Need to identify problem SQL statements
Learn how to influence the optimizer.
Understand SQL performance management.
Tuning the shared pool, I/0, Buffer cache, PGA and temporary space.
Course Targeted Audience:
Any candidate can join our Oracle performance tuning online course.
People who are from professional background can join.
Researches can also participate in this course.
Prerequisites:
Candidates with basic knowledge of computer.
Basics of database are recommended.
Training Format:
Kernel Training provides Oracle performance tuning online course led by real time expert.
Registered Candidates can interact with instructor in live interactive sessions.
Candidates will have life time access to learning material.
Companies Using Oracle PT:
Major international IT companies perform Oracle performance tuning for their operations.
Introduction to oracle database (basic concepts)Bilal Arshad
Introduction To Oracle Database
Oracle is an Relational Database
Database Management System
What is Oracle Schema ??
Schema !!
More about Schema !!!
Table
Indexes
Oracle Table Spaces
Datafiles
The Oracle Schema or User
Data Access
PL/SQL and Java
Best Practices for Building and Deploying Data Pipelines in Apache SparkDatabricks
Many data pipelines share common characteristics and are often built in similar but bespoke ways, even within a single organisation. In this talk, we will outline the key considerations which need to be applied when building data pipelines, such as performance, idempotency, reproducibility, and tackling the small file problem. We’ll work towards describing a common Data Engineering toolkit which separates these concerns from business logic code, allowing non-Data-Engineers (e.g. Business Analysts and Data Scientists) to define data pipelines without worrying about the nitty-gritty production considerations.
We’ll then introduce an implementation of such a toolkit in the form of Waimak, our open-source library for Apache Spark (https://github.com/CoxAutomotiveDataSolutions/waimak), which has massively shortened our route from prototype to production. Finally, we’ll define new approaches and best practices about what we believe is the most overlooked aspect of Data Engineering: deploying data pipelines.
Data Scientists mainly use tools like SQL and Pandas to perform tasks like exploring data sets, understanding their structure, content, and relationships.
Managing large chain of Hotels and ERP database comprises of core areas such as HRMS & PIP.HRMS (Human Resource Management System), which further includes areas such as Soft Joining, Promotion, Transfer, Confirmation, Leave Attendance and Exit, etc. PIP (Payroll Information Portal), wherein employees can view their individual Salary details, submit investment declaration, Reimbursement claim & CTC structuring, etc. Management of Large Chain of Hotels and ERP Database in AWS Cloud involves continuous monitoring with regards to the areas such as Performance of resource usages and optimization techniques relating to the use of PL/SQL. High Availability (HA) of data is accomplished through the Backup and Recovery mechanism and security of the data by Encryption & Decryption mechanism.
Oracle DBA Tutorial for Beginners -Oracle training institute in bangaloreTIB Academy
Get Oracle DBA Training through free Oracle DBA Tutorial, In this Oracle DBA Tutorial specially made for Beginners. You can download Oracle DBA Tutrial
Evolution of the DBA to Data Platform Administrator/SpecialistTony Rogerson
DBA's used to be Relational Database centric for instance managing Microsoft SQL Server or Oracle, in this changing world of polyglot database environments their role has expanded not just into new platforms other than SQL but also new legal governance, modelling techniques, architecture etc. They need to have a base knowledge of Kimball, Inmon, Data Vault, what CAP theorem is, LAMBDA, Big Data, Data Science etc.
An perspective into the raise of NoSQL systems and an comparison between RDBMS and NoSQL technologies.
The basic idea of the presentation originated while trying to understand the different alternatives available for managing data while building a fast, highly scalable, available, and reliable enterprise application.
MySQL 8.0 is a big advancement over previous versions with a true data dictionary, invisible indexes, histograms, windowing functions, improved JSON support, CATS, and more
Learn about the features that can help you modernize your mission critical applications, where security and performance can go hand in hand. From the wide range of SQL Server features available, we will take a closer look at In-Memory performance, Automatic Tuning, Advanced Security Features like Always Encrypted, Polybase and integration with Machine Learning through R and Python.
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Empowering the Data Analytics Ecosystem: A Laser Focus on Value
The data analytics ecosystem thrives when every component functions at its peak, unlocking the true potential of data. Here's a laser focus on key areas for an empowered ecosystem:
1. Democratize Access, Not Data:
Granular Access Controls: Provide users with self-service tools tailored to their specific needs, preventing data overload and misuse.
Data Catalogs: Implement robust data catalogs for easy discovery and understanding of available data sources.
2. Foster Collaboration with Clear Roles:
Data Mesh Architecture: Break down data silos by creating a distributed data ownership model with clear ownership and responsibilities.
Collaborative Workspaces: Utilize interactive platforms where data scientists, analysts, and domain experts can work seamlessly together.
3. Leverage Advanced Analytics Strategically:
AI-powered Automation: Automate repetitive tasks like data cleaning and feature engineering, freeing up data talent for higher-level analysis.
Right-Tool Selection: Strategically choose the most effective advanced analytics techniques (e.g., AI, ML) based on specific business problems.
4. Prioritize Data Quality with Automation:
Automated Data Validation: Implement automated data quality checks to identify and rectify errors at the source, minimizing downstream issues.
Data Lineage Tracking: Track the flow of data throughout the ecosystem, ensuring transparency and facilitating root cause analysis for errors.
5. Cultivate a Data-Driven Mindset:
Metrics-Driven Performance Management: Align KPIs and performance metrics with data-driven insights to ensure actionable decision making.
Data Storytelling Workshops: Equip stakeholders with the skills to translate complex data findings into compelling narratives that drive action.
Benefits of a Precise Ecosystem:
Sharpened Focus: Precise access and clear roles ensure everyone works with the most relevant data, maximizing efficiency.
Actionable Insights: Strategic analytics and automated quality checks lead to more reliable and actionable data insights.
Continuous Improvement: Data-driven performance management fosters a culture of learning and continuous improvement.
Sustainable Growth: Empowered by data, organizations can make informed decisions to drive sustainable growth and innovation.
By focusing on these precise actions, organizations can create an empowered data analytics ecosystem that delivers real value by driving data-driven decisions and maximizing the return on their data investment.
StarCompliance is a leading firm specializing in the recovery of stolen cryptocurrency. Our comprehensive services are designed to assist individuals and organizations in navigating the complex process of fraud reporting, investigation, and fund recovery. We combine cutting-edge technology with expert legal support to provide a robust solution for victims of crypto theft.
Our Services Include:
Reporting to Tracking Authorities:
We immediately notify all relevant centralized exchanges (CEX), decentralized exchanges (DEX), and wallet providers about the stolen cryptocurrency. This ensures that the stolen assets are flagged as scam transactions, making it impossible for the thief to use them.
Assistance with Filing Police Reports:
We guide you through the process of filing a valid police report. Our support team provides detailed instructions on which police department to contact and helps you complete the necessary paperwork within the critical 72-hour window.
Launching the Refund Process:
Our team of experienced lawyers can initiate lawsuits on your behalf and represent you in various jurisdictions around the world. They work diligently to recover your stolen funds and ensure that justice is served.
At StarCompliance, we understand the urgency and stress involved in dealing with cryptocurrency theft. Our dedicated team works quickly and efficiently to provide you with the support and expertise needed to recover your assets. Trust us to be your partner in navigating the complexities of the crypto world and safeguarding your investments.
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
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.
3. More about me12 years of Oracle DBA experience
Various Industry verticals
Retail, Insurance, Freight and Logistics
Interests: Linux, Perl, Python, C
Likes: Music, Food, Travel, …
6. Database Fundamentals
+ What is a Database Management System
+ Database Concepts
+ Popular Database Softwares
+ Database Applications
+ Working with Databases
+ Job roles and duties of Database Professionals
7. What is a Database
A Database Management System
Or just a database is a collection of
software programmes for
managing data,
It helps to STORE, RETRIEVE, and
MANIPULATE data in an efficient
manner.
8. Database Concepts
Database Model
A database model is a
type of data model
that defines the logical
structure of a
database and
determines in which
manner data can be
stored, organized, and
manipulated.
By Marcel Douwe Dekker - Own work, CC BY-SA 3.0, https://commons.wikimedia.org/w/index.php?curid=5679857
9. Database Concepts
The Relational model
Proposed by Edgar F. Codd in 1970 broke of
from the tradition of hierarchical model
and insisted that applications should
search for data by content, rather than
following links. The relational model
employs sets of ledger-style tables, each
used for a different type of entity.
By mid-1980s relational systems (DBMSs
plus applications) became popular owing
to the advent of better computer
hardware. (Source : Wikipedia)
By U.S. Department of Transportationvectorization: Own work - Data Integration Glossary., Public Domain, https://commons.wikimedia.org/w/index.php?curid=17875170
10. Database Concepts
Tables / Relations
A table is an accepted
visual representation
of a relation; a tuple is
similar to the concept
of a row. It is a set of
column definitions
along with the data
appearing in that
structure.
Columns /Attributes
Attribute is the term
used in the theory for
what is commonly
referred to as
a column.
Rows / Tuples
A row is a collection of
column values in a
specific order which
has a one to one
mapping with the
attribute name.
11. Database Concepts
Constraints
Constraints enforce
consistency of data in a
relational database.
Rules that govern data
stored in tables.
Rules to define
relationships between two
tables.
Primary Key, Foreign Key,
Not Null, Check, Unique.
Transaction
A transaction can be
defined as a group of
tasks. A single task is
the minimum
processing unit which
cannot be divided
further.
Transaction is
completed with a
Commit/Rollback
ACID Properties of
Transactions
Atomicity − This property states
that a transaction must be treated
as an atomic unit, that is, either all
of its operations are executed or
none.
Consistency − The database must
remain in a consistent state after
any transaction.
Durability − The database should be
durable enough to hold all its latest
updates even if the system fails or
restarts.
Isolation − In a multi transactional
database system, No transaction
will affect the existence of any other
transaction.
15. Working with databases
SQL (Structured Query
Language)
Declarative, Non-
Programming Language used
to Interact with the database.
Allows to CREATE, ALTER and
DROP Data objects i.e. Tables
and one can SELECT, INSERT,
UPDATE and DELETE data
from tables using SQL.
SQL Users
+ Database Application
Developers
+ Database Administrators
+ Data Analysts
16. Working with databases
SQL Basics
SQL Statements fall under the
following categories
+ DDL (Data Definition
Language)
+ DML (Data Manipulation
Language)
+ SELECT (query data from
one or more tables)
+ DCL (Data Control
Language)
+ TCL (Transaction Control
Language)
SQL Examples
create table emp(
empno number(4,0),
ename varchar2(10),
job varchar2(9),
mgr number(4,0),
hiredate date,
sal number(7,2),
comm number(7,2),
deptno number(2,0),
constraint pk_emp primary key (empno),
constraint fk_deptno foreign key (deptno) references dept (deptno)
);
insert into emp values( 7839, 'KING', 'PRESIDENT',
null, to_date('17-11-1981','dd-mm-yyyy'), 5000, null, 10);
SELECT EMP.*,DNAME,LOC FROM Emp, Dept WHERE Dname IN
('ACCOUNTING','RESEARCH') AND EMP.DEPTNO = DEPT.DEPTNO
ORDER BY EMP.DEPTNO
17. Working with databases
Programmability
Most popular databases have
a feature called STORED
PROCEDURES which are
program units that can be
created and stored within the
database
Helps to store business
specific logic within the
database which improves
performance
18. Job roles and duties of Database Professionals
Developers
• Responsible for creating and
managing application, Write code for
creating and managing frontent UI
• Write code for creating and
managing backend or business logic
• Design relational and logical design
of database and Perform
Normalization of tables
DBA
• Responsible for creating and
managing databases
• Take care of data security
• Support DB users when there is a
database problem
• Responsible for Managing DR and HA
Data Analysts
• Work on BI tools
• Create Business reports
• Perform trend analysis
21. Database Client Components
Database Client Drivers
+ Programmable APIs
written in a 3GL
+ Enables client applications
to connect and Interact
with RDBMS systems
independent of the RDBMS
implementation.
+ Eg : ODBC, JDBC, ADO.net
etc
Database Native Tools
+ Tools provided by the
RDBMS vendor to connect
and interact with the
RDBMS System
+ Vendor Specific
implementation/APIs
+ Provides more features
22. Database Server Components
DBMS Engine
+ Manage user
connections/sessions
+ Manage File I/O
+ Ensure data recoverability
and Consistency
Query Processor
+ Parse and Execute SQL
+ Ensure Read Consistency of
SELECT queries
+ Return Rows to users in the
case of SELECTs
+ Invoke transaction
processor for DMLsTransaction Processor
+ Begin and End Transactions
+ Manage ACID properties for the transaction
+ Assist query processor to maintain read
consistency
23. Database Server Components
Data Dictionary
+ Metadata repository
+ Set of tables which store
data about the DB objects
Job Scheduler
+ Manage database jobs
+ Monitor Job execution
+ Log job execution status
Query Optimizer
+ Prepare Execution plans for SQL
+ Optimizes Execution plan for better
performance.
30. Advantages
+ Cost Savings (Pay per use
model)
+ Need Based Provisioning
+ Reduce Investments,
Increase Returns
+ Lower operating costs
+ Standardization
Database in the Cloud : DBaaS
Technical Features
+ Consolidation Platform
+ Virtualization
+ Multi Tenancy
+ Provider Managed High
Availability and Disaster
Recovery
32. + Table and Index Partitions
+ Geo Spatial Data
+ Full Text Search
+ Database Replication
+ Database High Availability
+ Disaster Recovery
Database Features
40. Credits
Special thanks to all the people who made and
released these awesome resources for free:
+ Presentation template by SlidesCarnival
+ Photographs by Unsplash