SQL: Structured Query Language
Includes:
Introduction
It is a computer programming language that is used for storage, retrieval and manipulation of data that is stored in relational database. This is a standard computer programming language used for RDMS (Relational Database Management Systems).
IBM’s Ted Cod a.k.a Father of Relational databases gave the concept of relational model for database in 1970. It was 4 years later SQL appeared in 1974. This was just an idea, which got conceptualized in the form of Systems/R in 1978 and was released by IBM. The ANSI standards and first prototype of relational databases was released in 1986, which is popularly knows as Oracle
Advantages:
Used for accessing data in RDBMS.
Used for describing data.
Definition of data and its manipulation.
Can be used with other programming language by embedding SQL modules into other languages code, pre-compilers and libraries.
Possible to create and drop data base using this programming language.
Setting permission on views, table and procedures.
Can be used for creating views, procedures and functions.
Commands
Commands in SQL are categorized into three category namely
DDL – Data definition language
DML – Data Manipulation language
DCL – Data Control language
Data Definition Language (DDL)
Commands that are classified under DDL category are as follows:
CREATE – Used for creating an object, table/view.
ALTER – Used for modifying an existing database object.
DROP – Object, table an views created using CREATE can be deleted/removed.
Data Manipulation Language (DML)
Commands that are classified under DML are as follows:
SELECT – Used for retrieving a set of records from one/more than one tables.
DELETE – Used for deleting records.
UPDATE – Used for modifying / updating records.
INSERT – Used for inserting records.
Data Control Language (DCL)
Commands that have been classified under DCL are:
GRANT – Users can be granted permission / privileges using this command
REVOKE – Privileges to the user can be taken back using this command.
Constraints
Rules are enforced on the columns of the table that contain data specific for the field for all the record in the table. These rules are referred to as constraints, which are generally used to ensure that field only gets a particular type of value. For instance if there is a field called “Age” in the table, then this field can only take numeric value.
Constraints set up for the table apply to all the data stored in the table.
Some of the common constraints are:
NOT NULL:
This constraints ensure that the field value is never set to NULL
DEFAULT:
Typically used to fill in a default value for any field left blank.
UNIQUE:
If the constraints is set on a column, then all value set for this field will have to be unique
Data Definition Language (DDL), Data Definition Language (DDL), Data Manipulation Language (DML) , Transaction Control Language (TCL) , Data Control Language (DCL) - , SQL Constraints
Data Definition Language (DDL), Data Definition Language (DDL), Data Manipulation Language (DML) , Transaction Control Language (TCL) , Data Control Language (DCL) - , SQL Constraints
Consists of the explanations of the basics of SQL and commands of SQL.Helpful for II PU NCERT students and also degree studeents to understand some basic things.
in this presentation the commands let you help to understand the basic of the database system software. how to retrieve data, how to feed data and manipulate it very efficiently by using this commands.
Structured Query Language
SQL Commands:
• The standard SQL commands to interact with relational databases are CREATE, SELECT, INSERT, UPDATE, DELETE and DROP
Consists of the explanations of the basics of SQL and commands of SQL.Helpful for II PU NCERT students and also degree studeents to understand some basic things.
in this presentation the commands let you help to understand the basic of the database system software. how to retrieve data, how to feed data and manipulate it very efficiently by using this commands.
Structured Query Language
SQL Commands:
• The standard SQL commands to interact with relational databases are CREATE, SELECT, INSERT, UPDATE, DELETE and DROP
Health Care Analytics
Table of Content:
What is Healthcare Analytics
Objectives of Healthcare Analytics
Types of Analytics
Source of Data
What do Healthcare companies achieve with healthcare analytics
Booming technologies in the Healthcare Industries with some of their uses
Existing Healthcare analytics tool in the market
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Objectives of Healthcare Analytics
The fundamental objective of healthcare analytics is to help people make and execute rational decisions.
Data - Driven
Analytics in healthcare can help ensure that all decisions are made based on the best possible evidence derived from accurate and verified sources of information.
Transparent
Healthcare analytics can break down silos based on program, department or even facility by promoting the sharing of accurate, timely and accessible information
Verifiable
The selected option can be tested and verified, based on the available data and decision-making model, to be as good as or better than other alternatives.
Robust
Healthcare is a dynamic environment; decisions making models must be robust enough to perform in non-optimal conditions such as missing data, calculation error, failure to consider all available options and other issues.
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Types of Analytics
Descriptive Analytics
Uses business Intelligence and data mining to ask: “What has Happened”
Diagnostics Analytics
Examines data to answer, “Why did it happen ?”
Predictive Analytics
Uses optimization and simulation to ask: “What should we do”
Prescriptive Analytics
Uses optimization and simulation to ask: “What should we do”
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Sources of Data
Human Generated data
Web and social media data
Machine to Machine data
Transaction data
Biometric data
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What do Healthcare companies achieve with healthcare analytics
Hospitals
Reducing Cost
Reducing cost of analytics by building an easy-to-use analytics platform
Identifying and preventing anomalies such as fraud
Automating external and internal reporting
Improving patient outcomes
Clinical decision support
Pharmacy
Randomized clinical trials are expensive to conduct and are not effective at identifying rare events, heterogeneous treatment effects, long-term outcomes. Pharma companies rely on healthcare analytics to identify such relationships. However, inferring causal relations can be difficult as data can be easily misinterpreted to view unrelated factors as inter-dependent.
Contents:
Behavior Driven Development (BDD)
Features of BDD
BDD Tools
BDD Framework
Examples of Cucumber/SpecFlow/BDD test
Gherkin – BDD Language
The Problem
Example of Gherkin
The Conclusion
SpecFlow Feature File
Keywords for the Feature File creation
This PPT gives a brief description about Geomatics, the disciplines and techniques constituting Geomatics, Geographic Information System or GIS, GIS data (Spatial Data and Non- Spatial Data), GIS data models, GIS application in Petroleum Exploration, Coordinate System, Geodetic Datum and ArcGIS.
A brief summary of Oil and Gas Upstream. PPT includes basic Chemistry, Basic Geology, Oil formation, Migration of Petroleum, Reservoir, porosity, permeability, Geological structures for petroleum entrapment, Exploration methods, Geological methods, Geophysical methods, geophysical methods, seismic methods, seismic methods, gravity methods, magnetic methods, well drilling, preparation to drill, setting the rig, drilling, enhanced oil recovery, EOR, primary oil recovery, secondary oil recovery, thermal recovery, gas injection and chemical injection
An Overview of CNG and PNG
Compressed Natural Gas (CNG): is natural gas compressed to a pressure of 200-250 Kg/cm² (g) (due to its low density) to enhance the vehicle onboard storage capacity. Thus, the compressed form of natural gas is used as a fuel for transportation purposes.
At present CNG Retail Outlets of GAIL and Its JVCs are available in Delhi, Maharastra, Uttar Pradesh, Gujarat, Andhra Pradesh, Tripura, and Madhya Pradesh States with more than 400 CNG Retail outlets catering to approximately 6,80,000 vehicles.
Indraprastha Gas Ltd, a JV of GAIL (India) Ltd, has 209 CNG Retail outlets and Mahanagar Gas Ltd another JV of GAIL (India) Ltd has set up 148 CNG stations
Similarly, other JVCs like MNGL has 13 Outlets, BGL has 14 outlets , GGL with 10 outlets each, and AGL & CGUL with 9 retail outlets each and TNGCL with one outlet.
GAIL Gas Limited, a wholly owned subsidiary of GAIL (India) Limited has currently 17 CNG outlets at Dewas, Sonepat, Kota, Meerut, Vijaipur, Dibiyapur, Firozabad, Vadodara and Panvel. It will be commissioning its other outlets very soon.
Piped Natural Gas (PNG) is natural gas used as a fuel for households, Industries (with a demand of less than 50000 scmd) and commercial units
Problem of odor pollution and its management solutionRohit Bisht
The term odour refers to perception regarding smell or scientifically it can be called as “a sensation resulting from the reception of stimulus by the olfactory sensory system”. It can be unpleasant or pleasant but it is caused by inhaling air borne inorganics or organics.
The ever growing population, urbanization and industrialisation has led to odour problem which has increased in to a large proportion and thus a need to control the problem has risen. The major reason of odour problem is no proper sanitation facilities for urbanization. Industrialisation is taking place at a very fast pace and it has added to the problem. Undesirable odour detoriates the air quality and affects the human lifestyle. Odour problem is one the most complex form of pollution.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
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During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
2. INTRODUCTION
• It is a computer programming language that is used for storage,
retrieval and manipulation of data that is stored in relational database.
This is a standard computer programming language used for RDMS
(Relational Database Management Systems).
• IBM’s Ted Cod a.k.a Father of Relational databases gave the concept of
relational model for database in 1970. It was 4 years later SQL appeared
in 1974. This was just an idea, which got conceptualized in the form of
Systems/R in 1978 and was released by IBM. The ANSI standards and
first prototype of relational databases was released in 1986, which is
popularly knows as Oracle
3. ADVANTAGE
• Used for accessing data in RDBMS.
• Used for describing data.
• Definition of data and its manipulation.
• Can be used with other programming language by embedding SQL
modules into other languages code, pre-compilers and libraries.
• Possible to create and drop data base using this programming
language.
• Setting permission on views, table and procedures.
• Can be used for creating views, procedures and functions.
4. COMMANDS
Commands in SQL are categorized into three category namely
• DDL – Data definition language
• DML – Data Manipulation language
• DCL – Data Control language
5. DATA DEFINITION LANGUAGE (DDL)
Commands that are classified under DDL category are as follows:
• CREATE – Used for creating an object, table/view.
• ALTER – Used for modifying an existing database object.
• DROP – Object, table an views created using CREATE can be
deleted/removed.
6. DATA MANIPULATION LANGUAGE (DML)
Commands that are classified under DML are as follows:
• SELECT – Used for retrieving a set of records from one/more than one
tables.
• DELETE – Used for deleting records.
• UPDATE – Used for modifying / updating records.
• INSERT – Used for inserting records.
7. DATA CONTROL LANGUAGE
Commands that have been classified under DCL are:
GRANT – Users can be granted permission / privileges using this command
REVOKE – Privileges to the user can be taken back using this command.
8. CONSTRAINTS
Rules are enforced on the columns of the table that contain data specific
for the field for all the record in the table. These rules are referred to as
constraints, which are generally used to ensure that field only gets a
particular type of value. For instance if there is a field called “Age” in the
table, then this field can only take numeric value.
Constraints set up for the table apply to all the data stored in the table.
9. Some of the common constraints are:
NOT NULL:
This constraints ensure that the field value is never set to NULL
DEFAULT:
Typically used to fill in a default value for any field left blank.
UNIQUE:
If the constraints is set on a column, then all value set for this field will have to be unique
PRIMARY KEY:
When this constraint is set for a column, it indicates that the field is the primary key/the
field value is a unique identifier for every record existent in the table. One Primary key
per table.
10. FOREIGN KEY:
When this constraint is set for a column, it indicates that the field is the
foreign key/the field value is a unique identifier for every record existent in
another table.
CHECK:
Checks if the values for a field satisfy pre-defined conditions
INDEX:
Can be used as an index (column) which shall be used for faster data
retrieval from the table.
11. DATA INTEGRITY
It is the measure of the accuracy and consistency of data stored in the
data-base.
ENTITY INTEGRITY:
Refers to the accuracy and consistency of each entity in the database,
which is each record. Therefore, every record must be unique and no
duplicates of any of the records must be there.
DOMAIN INTEGRITY:
Ensures that every field gets valid entries by imposing restrictions on the
type, format and range of values that a field can hold
12. REFERENTIAL INTEGRITY
Records/rows that are being used by other able in the database cannot be
deleted.
USER-DEFINED INTEGRITY
Any rules that the user wishes to impose on columns and that are not
covered in the other data integrity categories form a part of user defined
integrity category
14. SYNTAX
• Every SQL statement should start with a keyword. Some example of this
include SELECT, CREATE, INSERT, DELETE & ALTER.
• Every SQL statement terminates with a semicolon (;)
• SQL is case insensitive
15. SYNTAX RULES
col Column
t_name Table Name
col_name Column Name
V Value
i_name Index Name
db_name Database Name
cond Conditions
Asterisk (*) means all
16. SHOW DATABASE:
To see the complete list of commands
SHOW TABLES:
To view a list of tables for the currently selected database
SHOW COLUMNS:
Displays information about the columns in a given table
Eg. SHOW COLUMNS FROM customers;
SELECT:
Is used to select data from a database. The result is stored in a result table, which is called
result – set.
Eg. SELECT first name FROM customers;
17. MULTIPLE QUERIES:
SELECT first name FROM customer;
SELECT city FROM customers;
SELECTING MULTIPLE QUERIES:
SELECT first name, last name, city FROM customers;
SELECTING ALL COLUMNS:
To retrieve all of the information contained in your table, place an asterisk
(*) sign after the SELECT command.
Eg. SELECT * FROM customers;
18. DISTINCT:
In situations in which you have multiple duplicates records in a table, it
might make more sense to return only unique records, instead of fetching
duplicates.
Eg. SELECT DISTINCT column_name1, column_name2 FROM table_name.
LIMIT:
By default, all results that satisfy the conditions specified in the SQL
statement are returned. However, sometimes we need to retrieve just a
subset of records. In MySQL, this is accomplished by using the LIMIT
keyword.
SELECT column list FROM table_name LIMIT [Number of records]
Also allows to pick up a set of records from a particular offset.
Eg. We pick up 4 records, starting from the third position
SELECT ID, first name, last name, city FROM customers LIMIT 3,4;
19. FULLY QUALIFIED NAME:
In SQL, you can provide the table name prior to the column name by
separating them with a dot.
Eg. SELECT city FROM customer;
SELECT customer.city from customer;
ORDER BY:
It is used with SELECT to sort the return data.
SELECT * FROM customers ORDER BY first name;
For multiple columns, the ORDER BY command starts ordering in the same
sequence as the columns It will order by the first column listed, then by the
second and so on.
SELECT * FROM customers ORDER BY last name, age;
20. WHERE:
Where clause is used to extract only those records that fulfill a specified
condition.
SELECT column_list FROM table_name WHERE condition
21. COMPARISON OPERATORS
Comparison and Logical Operators are used in the WHERE clause to filter
the data to be used.
OPERATOR DESCRIPTON
= Equal
!= Not Equal
> Greater than
< Less than
>= Greater than/Equal
<= Less than/Equal
BETWEEN Between an exclusive range
22. Examples of Comparison Operators:
SELECT * FROM customer WHERE id !=5;
SELECT * FROM customer WHERE id BETWEEN 3 AND 7
SELECT id, first name, last name, city FROM customer WHERE city = “New
York”;
FYI incase the text contains apostrophe, use ‘Can’‘t’.