Design at least 10 SQL queries for suitable database
application using SQL DML statements:
Insert, Select, Update, Delete with operators, functions, and set operator.
This document discusses distributed database and distributed query processing. It covers topics like distributed database, query processing, distributed query processing methodology including query decomposition, data localization, and global query optimization. Query decomposition involves normalizing, analyzing, eliminating redundancy, and rewriting queries. Data localization applies data distribution to algebraic operations to determine involved fragments. Global query optimization finds the best global schedule to minimize costs and uses techniques like join ordering and semi joins. Local query optimization applies centralized optimization techniques to the best global execution schedule.
The document shows the steps taken to create and populate a MySQL database called pbd. The following tables were created: siswa, guru, mahasiswa, matakuliah, and krs. Data was inserted into the siswa and guru tables. Columns in the tables were updated, rows were deleted, and selections were made to view the data.
Introduction to Pandas and Time Series Analysis [PyCon DE]Alexander Hendorf
Most data is allocated to a period or to some point in time. We can gain a lot of insight by analyzing what happened when. The better the quality and accuracy of our data, the better our predictions can become.
Unfortunately the data we have to deal with is often aggregated for example on a monthly basis, but not all months are the same, they may have 28 days, 31 days, have four or five weekends,…. It’s made fit to our calendar that was made fit to deal with the earth surrounding the sun, not to please Data Scientists.
Dealing with periodical data can be a challenge. This talk will show to how you can deal with it with Pandas.
This document provides an introduction to naive Bayesian classification. It begins with an agenda that outlines key topics such as introduction, solved examples, advantages, and disadvantages. The introduction section defines naive Bayesian classification and provides the Bayes' theorem formula. Four examples are then shown applying naive Bayesian classification to classification problems involving predicting whether someone buys a computer, has the flu, has an item stolen, or plays golf. Each example calculates the probabilities and classifies a data sample. The document concludes by listing advantages such as being simple, scalable, and able to handle different data types, and disadvantages such as the independence assumption and data scarcity issues. References are also provided.
EX-6-Implement Matrix Multiplication with Hadoop Map Reduce.pptxvishal choudhary
1. This document describes the MapReduce algorithm for matrix multiplication and provides code examples to implement it in Hadoop.
2. Key aspects include preprocessing the input matrices as key-value pairs, a map function that emits pairs of rows and columns, and a reduce function that calculates the inner products to obtain the output matrix.
3. Code examples provide the mapper, reducer, driver classes along with commands to compile a jar file, upload sample input, and execute the job to perform matrix multiplication using MapReduce on Hadoop.
Generalization involves grouping entities together based on similar characteristics, such as classifying cows, oxen, and goats as animals. Specialization is the opposite, where a group is divided into subgroups based on distinguishing characteristics, like identifying a person as both a student and teacher.
The document discusses the Apriori algorithm, which is used for mining frequent itemsets from transactional databases. It begins with an overview and definition of the Apriori algorithm and its key concepts like frequent itemsets, the Apriori property, and join operations. It then outlines the steps of the Apriori algorithm, provides an example using a market basket database, and includes pseudocode. The document also discusses limitations of the algorithm and methods to improve its efficiency, as well as advantages and disadvantages.
This document discusses MySQL databases and how to interact with them using PHP. It begins by introducing MySQL as the world's most popular open source database and describes some basic database server concepts. It then provides code examples for how to connect to a MySQL database from PHP, select a database, perform queries to read, insert, update, and delete records, and more. The document is intended as a tutorial for learning the basic functions and syntax for accessing and manipulating data in a MySQL database with PHP.
The Boyer-Moore string matching algorithm was developed in 1977 and is considered one of the most efficient string matching algorithms. It works by scanning the pattern from right to left and shifting the pattern by multiple characters if a mismatch is found, using preprocessing tables. The algorithm constructs a bad character shift table during preprocessing that stores the maximum number of positions a mismatched character can shift the pattern. It then aligns the pattern with the text and checks for matches, shifting the pattern right by the value in the table if a mismatch occurs.
Aneka is a cloud application development platform that provides a middleware for managing and scaling distributed applications across physical and virtual resources connected through a network. It includes APIs for developing applications, a software development kit, and a runtime environment that supports multiple infrastructures. The Aneka framework consists of low-level fabric services for resource management and monitoring, foundational services for storage, accounting and billing, and application services for scheduling and executing distributed applications using programming models like task, thread, MapReduce and parameter sweep. Aneka provides tools for infrastructure, platform and application management through its cloud management studio.
The document discusses techniques used by a database management system (DBMS) to process, optimize, and execute high-level queries. It describes the phases of query processing which include syntax checking, translating the SQL query into an algebraic expression, optimization to choose an efficient execution plan, and running the optimized plan. Query optimization aims to minimize resources like disk I/O and CPU time by selecting the best execution strategy. Techniques for optimization include heuristic rules, cost-based methods, and semantic query optimization using constraints.
This presentation discusses semi-joins and their effectiveness in distributed environments. It begins by defining distributed systems and relational algebra operations like joins. It then explains that a semi-join returns rows from the first table that match rows in the second table, without duplicate rows. Examples are provided to illustrate how semi-joins can reduce communication costs compared to conventional joins. The presentation concludes by stating that semi-joins are an efficient way to join data across multiple tables in a query in distributed systems.
This document provides an overview of how to create and manage various schema objects in Oracle, including views, sequences, indexes, and synonyms. It discusses how to create simple and complex views, retrieve data from views, and perform DML operations on views. It also covers how to create, use, modify and cache sequences, and how to create nonunique indexes to improve query performance. Finally, it discusses how to create synonyms to provide alternative names for objects.
The document discusses various SQL concepts like views, triggers, functions, indexes, joins, and stored procedures. Views are virtual tables created by joining real tables, and can be updated, modified or dropped. Triggers automatically run code when data is inserted, updated or deleted from a table. Functions allow reusable code and improve clarity. Indexes allow faster data retrieval. Joins combine data from different tables. Stored procedures preserve data integrity.
The document appears to be a lab report submitted by a student for their Network Programming lab course. It includes 13 experiments performed on topics like writing echo programs using TCP and UDP, creating a client-server chat program, file transfer programs, and remote command execution. For each experiment, the student has provided the code for the client and server sides to demonstrate how to complete the task. The report is submitted to their professor and includes their name, course codes, semester and year details.
This presentation introduces clustering analysis and the k-means clustering technique. It defines clustering as an unsupervised method to segment data into groups with similar traits. The presentation outlines different clustering types (hard vs soft), techniques (partitioning, hierarchical, etc.), and describes the k-means algorithm in detail through multiple steps. It discusses requirements for clustering, provides examples of applications, and reviews advantages and disadvantages of k-means clustering.
Query Decomposition and data localization Hafiz faiz
This document discusses query processing in distributed databases. It describes query decomposition, which transforms a high-level query into an equivalent lower-level algebraic query. The main steps in query decomposition are normalization, analysis, redundancy elimination, and rewriting the query in relational algebra. Data localization then translates the algebraic query on global relations into a query on physical database fragments using fragmentation rules.
Join dependency occurs when a table can be recreated by joining multiple tables, with each table containing a subset of the original table's attributes. A join dependency exists if the join of two relations over a common attribute is equal to the original relation. Relations that have a join dependency between them form a lossless-join decomposition of the original relation.
PL/SQL is Oracle's standard language for accessing and manipulating data in Oracle databases. It allows developers to integrate SQL statements with procedural constructs like variables, conditions, and loops. PL/SQL code is organized into blocks that define a declarative section for variable declarations and an executable section containing SQL and PL/SQL statements. Variables can be scalar, composite, reference, or LOB types and are declared in the declarative section before being used in the executable section.
The document describes a Java program to create a color palette applet with the following features:
1. Create a matrix of buttons to display a color palette.
2. Allow the user to select a color from the palette to set the background or foreground of a text area control.
3. Use a checkbox control as radio buttons to select whether the selected color sets the background or foreground.
The algorithm defines the necessary classes and objects, adds the controls to the applet using init(), arranges the controls with setBounds(), sets button backgrounds with setBackground(), adds listeners, and conditionally sets the text area background or foreground based on the checkbox selection.
In DBMS (DataBase Management System), the relation algebra is important term to further understand the queries in SQL (Structured Query Language) database system. In it just give up the overview of operators in DBMS two of one method relational algebra used and another name is relational calculus.
This document discusses kernel methods and radial basis function (RBF) networks. It begins with an introduction and overview of Cover's theory of separability of patterns. It then revisits the XOR problem and shows how it can be solved using Gaussian hidden functions. The interpolation problem is explained and how RBF networks can perform strict interpolation through a set of training data points. Radial basis functions that satisfy Micchelli's theorem allowing for a nonsingular interpolation matrix are presented. Finally, the structure and training of RBF networks using k-means clustering and recursive least squares estimation is covered.
Difference between molap, rolap and holap in ssasUmar Ali
MOLAP, ROLAP, and HOLAP are different storage modes in SQL Server Analysis Services (SSAS). MOLAP stores aggregated data and source data in a multidimensional structure for fast queries. ROLAP stores aggregations in indexed views in the relational database, while HOLAP combines MOLAP and ROLAP by storing aggregations in a multidimensional structure but not source data. Queries against aggregated data are faster with MOLAP and HOLAP, while ROLAP is slower but uses less storage.
This document discusses time-series data and methods for analyzing it. Time-series data consists of sequential values measured over time that can be analyzed to identify patterns, trends, and outliers. Key methods discussed include trend analysis to identify long-term movements, seasonal variations, and irregular components; similarity search to find similar sequences; and dimensionality reduction and transformation techniques to reduce data size before analysis or indexing.
The document provides instructions on how to create tables, insert data, and write queries for a database with tables for students, library memberships, books, and book issue records. It includes examples of creating the tables with primary and foreign keys, inserting sample data, and queries to list student names and issued books, count books issued per student, and create views of issue records and daily issues.
CGI (Common Gateway Interface) is an interface that allows a web server to launch external applications dynamically in response to requests. It defines standard communication variables between the web server and CGI programs. CGI programs can be written in any programming language and are executed by the web server to generate dynamic web page content on the fly based on request parameters and structured data. However, CGI has performance and security limitations due to creating new processes for each request.
This document contains SQL queries and HTML code. The SQL section includes 16 queries on an EMP table with sample data. Queries retrieve and filter employee data by name, salary, department, hire date and more. The HTML section includes one form with fields to collect a user's name, password, country, computer type, comments and a submit button.
The document details the creation of a database called "empresa" with tables for employees and departments. Data is inserted into the tables and various queries are run to analyze the employee data, such as finding the department with the highest total salaries and the employee with the highest salary.
This document discusses MySQL databases and how to interact with them using PHP. It begins by introducing MySQL as the world's most popular open source database and describes some basic database server concepts. It then provides code examples for how to connect to a MySQL database from PHP, select a database, perform queries to read, insert, update, and delete records, and more. The document is intended as a tutorial for learning the basic functions and syntax for accessing and manipulating data in a MySQL database with PHP.
The Boyer-Moore string matching algorithm was developed in 1977 and is considered one of the most efficient string matching algorithms. It works by scanning the pattern from right to left and shifting the pattern by multiple characters if a mismatch is found, using preprocessing tables. The algorithm constructs a bad character shift table during preprocessing that stores the maximum number of positions a mismatched character can shift the pattern. It then aligns the pattern with the text and checks for matches, shifting the pattern right by the value in the table if a mismatch occurs.
Aneka is a cloud application development platform that provides a middleware for managing and scaling distributed applications across physical and virtual resources connected through a network. It includes APIs for developing applications, a software development kit, and a runtime environment that supports multiple infrastructures. The Aneka framework consists of low-level fabric services for resource management and monitoring, foundational services for storage, accounting and billing, and application services for scheduling and executing distributed applications using programming models like task, thread, MapReduce and parameter sweep. Aneka provides tools for infrastructure, platform and application management through its cloud management studio.
The document discusses techniques used by a database management system (DBMS) to process, optimize, and execute high-level queries. It describes the phases of query processing which include syntax checking, translating the SQL query into an algebraic expression, optimization to choose an efficient execution plan, and running the optimized plan. Query optimization aims to minimize resources like disk I/O and CPU time by selecting the best execution strategy. Techniques for optimization include heuristic rules, cost-based methods, and semantic query optimization using constraints.
This presentation discusses semi-joins and their effectiveness in distributed environments. It begins by defining distributed systems and relational algebra operations like joins. It then explains that a semi-join returns rows from the first table that match rows in the second table, without duplicate rows. Examples are provided to illustrate how semi-joins can reduce communication costs compared to conventional joins. The presentation concludes by stating that semi-joins are an efficient way to join data across multiple tables in a query in distributed systems.
This document provides an overview of how to create and manage various schema objects in Oracle, including views, sequences, indexes, and synonyms. It discusses how to create simple and complex views, retrieve data from views, and perform DML operations on views. It also covers how to create, use, modify and cache sequences, and how to create nonunique indexes to improve query performance. Finally, it discusses how to create synonyms to provide alternative names for objects.
The document discusses various SQL concepts like views, triggers, functions, indexes, joins, and stored procedures. Views are virtual tables created by joining real tables, and can be updated, modified or dropped. Triggers automatically run code when data is inserted, updated or deleted from a table. Functions allow reusable code and improve clarity. Indexes allow faster data retrieval. Joins combine data from different tables. Stored procedures preserve data integrity.
The document appears to be a lab report submitted by a student for their Network Programming lab course. It includes 13 experiments performed on topics like writing echo programs using TCP and UDP, creating a client-server chat program, file transfer programs, and remote command execution. For each experiment, the student has provided the code for the client and server sides to demonstrate how to complete the task. The report is submitted to their professor and includes their name, course codes, semester and year details.
This presentation introduces clustering analysis and the k-means clustering technique. It defines clustering as an unsupervised method to segment data into groups with similar traits. The presentation outlines different clustering types (hard vs soft), techniques (partitioning, hierarchical, etc.), and describes the k-means algorithm in detail through multiple steps. It discusses requirements for clustering, provides examples of applications, and reviews advantages and disadvantages of k-means clustering.
Query Decomposition and data localization Hafiz faiz
This document discusses query processing in distributed databases. It describes query decomposition, which transforms a high-level query into an equivalent lower-level algebraic query. The main steps in query decomposition are normalization, analysis, redundancy elimination, and rewriting the query in relational algebra. Data localization then translates the algebraic query on global relations into a query on physical database fragments using fragmentation rules.
Join dependency occurs when a table can be recreated by joining multiple tables, with each table containing a subset of the original table's attributes. A join dependency exists if the join of two relations over a common attribute is equal to the original relation. Relations that have a join dependency between them form a lossless-join decomposition of the original relation.
PL/SQL is Oracle's standard language for accessing and manipulating data in Oracle databases. It allows developers to integrate SQL statements with procedural constructs like variables, conditions, and loops. PL/SQL code is organized into blocks that define a declarative section for variable declarations and an executable section containing SQL and PL/SQL statements. Variables can be scalar, composite, reference, or LOB types and are declared in the declarative section before being used in the executable section.
The document describes a Java program to create a color palette applet with the following features:
1. Create a matrix of buttons to display a color palette.
2. Allow the user to select a color from the palette to set the background or foreground of a text area control.
3. Use a checkbox control as radio buttons to select whether the selected color sets the background or foreground.
The algorithm defines the necessary classes and objects, adds the controls to the applet using init(), arranges the controls with setBounds(), sets button backgrounds with setBackground(), adds listeners, and conditionally sets the text area background or foreground based on the checkbox selection.
In DBMS (DataBase Management System), the relation algebra is important term to further understand the queries in SQL (Structured Query Language) database system. In it just give up the overview of operators in DBMS two of one method relational algebra used and another name is relational calculus.
This document discusses kernel methods and radial basis function (RBF) networks. It begins with an introduction and overview of Cover's theory of separability of patterns. It then revisits the XOR problem and shows how it can be solved using Gaussian hidden functions. The interpolation problem is explained and how RBF networks can perform strict interpolation through a set of training data points. Radial basis functions that satisfy Micchelli's theorem allowing for a nonsingular interpolation matrix are presented. Finally, the structure and training of RBF networks using k-means clustering and recursive least squares estimation is covered.
Difference between molap, rolap and holap in ssasUmar Ali
MOLAP, ROLAP, and HOLAP are different storage modes in SQL Server Analysis Services (SSAS). MOLAP stores aggregated data and source data in a multidimensional structure for fast queries. ROLAP stores aggregations in indexed views in the relational database, while HOLAP combines MOLAP and ROLAP by storing aggregations in a multidimensional structure but not source data. Queries against aggregated data are faster with MOLAP and HOLAP, while ROLAP is slower but uses less storage.
This document discusses time-series data and methods for analyzing it. Time-series data consists of sequential values measured over time that can be analyzed to identify patterns, trends, and outliers. Key methods discussed include trend analysis to identify long-term movements, seasonal variations, and irregular components; similarity search to find similar sequences; and dimensionality reduction and transformation techniques to reduce data size before analysis or indexing.
The document provides instructions on how to create tables, insert data, and write queries for a database with tables for students, library memberships, books, and book issue records. It includes examples of creating the tables with primary and foreign keys, inserting sample data, and queries to list student names and issued books, count books issued per student, and create views of issue records and daily issues.
CGI (Common Gateway Interface) is an interface that allows a web server to launch external applications dynamically in response to requests. It defines standard communication variables between the web server and CGI programs. CGI programs can be written in any programming language and are executed by the web server to generate dynamic web page content on the fly based on request parameters and structured data. However, CGI has performance and security limitations due to creating new processes for each request.
This document contains SQL queries and HTML code. The SQL section includes 16 queries on an EMP table with sample data. Queries retrieve and filter employee data by name, salary, department, hire date and more. The HTML section includes one form with fields to collect a user's name, password, country, computer type, comments and a submit button.
The document details the creation of a database called "empresa" with tables for employees and departments. Data is inserted into the tables and various queries are run to analyze the employee data, such as finding the department with the highest total salaries and the employee with the highest salary.
The document describes various data manipulation language (DML) commands in Oracle such as INSERT, SELECT, UPDATE, DELETE, logical operators, pattern matching, aggregate functions, and date functions. Examples are provided to demonstrate inserting, selecting, updating, deleting records from a table and using functions to analyze and retrieve data based on conditions.
This document contains a log of questions and answers related to SQL queries on sample tables. It includes 12 questions on topics like selecting data, filtering results, aggregation, joins and updates. The questions involve writing queries on tables for employees, departments, items and transactions to retrieve, calculate and update stored data.
Analytic SQL functions, or "window functions have been there since 8.1.6, but they are still dramatically underused by application developers. This session looks at the syntax and usage of analytic functions, and how they can supercharge your SQL skillset.
Covers analytics from their inception in 8.1.6 all the through to enhancements in 18 and 19
This document contains examples of SQL queries being run on database tables to retrieve various data. The queries demonstrate selecting data from tables, filtering on conditions, using aggregation functions like COUNT and AVG, joining tables, and more. The tables being queried include EMP, DEPT, and other tables containing employee and department data.
The document describes a series of SQL commands used to create, alter, insert data into, and query tables named EMP_TAB and DEPT_TAB. The commands create the tables with various columns and constraints, insert sample data, and add, modify and delete columns. Queries are written to find matching records and aggregate data from the tables.
Perth APAC Groundbreakers tour - SQL TechniquesConnor McDonald
This document discusses using SQL to perform various tasks like summarizing and transforming data, handling errors, and self-documenting queries. It provides examples of using pivot/unpivot clauses to change data orientation, query block naming to add descriptive comments to queries, and DBMS_ERRLOG to log errors from DML statements. It also discusses using partitioned outer joins to report bookings by hour including empty timeslots.
The document discusses SQL DML statements like SELECT, INSERT, UPDATE, and DELETE. It provides examples of using each statement to manipulate data in tables. It also covers additional SQL clauses and functions like WHERE, ORDER BY, GROUP BY, JOIN, and aggregate functions that can be used with the SELECT statement to filter, sort, group, and perform calculations on the result set.
Slides from the ILOUG 2019 conference. At every conference, you’ll see plenty about the latest and greatest release of Oracle. You’ll sigh as you think that it will be 10 years before you get to these versions at your workplace. This presentation is for you – we’ll look at the cool underused SQL features available going all the way back to Oracle 8.
The document provides an overview of basic SQL statements and capabilities. It discusses using SELECT statements to project columns, select rows, and join tables. It also covers arithmetic expressions, column aliases, concatenation, and eliminating duplicate rows. SQL statements are executed through the SQL*Plus environment, which allows editing, saving, and running SQL code and commands.
The document provides an introduction to SQL and covers various SQL clauses and functions including:
- Data retrieval using SELECT statements with projections, selections, joins, and WHERE clauses
- Data manipulation using INSERT, DELETE, UPDATE statements
- Data definition using CREATE, ALTER, DROP statements
- Single row functions like concatenation and conversion and multirow functions like SUM and GROUP BY
SQL stands for Structured Query Language and is used to manage relational database objects and data. SQL commands are divided into categories like DDL, DML, DQL etc. DDL commands are used to define database schemas and objects, DML commands manipulate the data within database tables, and DQL commands are used to query or retrieve data from databases. Some key SQL commands include CREATE, ALTER, DROP, SELECT, INSERT, UPDATE, DELETE. SQL also supports integrity constraints, data types, joins, aggregations and more.
1. The document discusses various SQL commands for creating, manipulating, and querying database tables. It covers commands like CREATE TABLE, INSERT, SELECT, UPDATE, DELETE, ALTER TABLE, COMMENT, and more.
2. Mathematical functions like COUNT, MAX, MIN, ROUND, TRUNC are described along with logical and comparison operators.
3. The document provides examples of using operators, functions, joins and grouping with detailed explanations.
Slides from OpenWorld 2013 presentation.
Analytics have been there since 8.1.6, but they are still dramatically underused by application developers. This session looks at the syntax and usage of analytic functions, and how they can supercharge your SQL skillset.
By expanding our knowledge of SQL facilities, we can let all the boring work be handled via SQL rather than a lot of middle-tier code, and we can get performance benefits as an added bonus. Here are some SQL techniques to solve problems that would otherwise require a lot of complex coding, freeing up your time to focus on the delivery of great applications.
This document discusses various SQL join queries using the EMP and DEPT tables in the Oracle database. It provides examples of inner joins, outer joins, natural joins, cross joins, and lateral joins. It explores different join types and syntax as well as filtering criteria and partitioning.
1- Return the names- IDS- and average salary of the top 10 employees w.docxtodd991
The document contains 3 SQL queries:
1. Finds the top 10 senior engineers with average salary over $110,000 ordered by average salary descending.
2. Finds the top 10 employees who earned over $200,000 between 2000-2002 ordered by total wages descending.
3. Uses a subquery to display the bottom 10 average salaries of employees not in the 'Staff' category.
Sangam 18 - Great Applications with Great SQLConnor McDonald
Get more out of the database by exploiting the rich suite of features available with the SQL language. We cover pivot, unpivot, rollup, pagination, error logging, query block naming
The Annual G20 Scorecard – Research Performance 2019 bhavesh lande
The 2019 G20 Summit takes place in Osaka, Japan
on June 28-29. What happens in the G20 affects
the world and the G20 group is undoubtedly
a driver in the global research system.
information control and Security systembhavesh lande
Get an overview of threats to the Organization
• Learn about technologies for handling Security
• Get an overview of wireless technology
• Understand managing security
information technology and infrastructures choicesbhavesh lande
Understand information technology infrastructures
• Get an overview on infrastructure decision
• Learn about infrastructure components
• Understand infrastructure solutions
The document discusses several ethical and social issues concerning information systems. It covers topics like privacy, workplace monitoring, the concept of an information panopticon, challenges of e-waste management, and how information systems can impact work practices and worker health/alienation. Specific issues addressed include privacy concerns for both individuals and governments, the various ways workplaces monitor employees, how this relates to power dynamics, and the health and environmental problems caused by improper e-waste disposal.
The document discusses key challenges in managing IT functions, including the modern dynamic IT environment, centralization vs decentralization debates, standardization, security issues, technology selection criteria, vendor management, the role of the CIO, and IT governance models. It notes the first, second, and third order impacts of introducing IT to an organization and examines debates around centralized vs decentralized infrastructure and standardization. It also outlines factors to consider in technology selection, the vendor management lifecycle, and different IT governance archetypes involving business and IT leadership.
• Know what are the main drivers of innovation in IT
• Understand how innovations spread
• •Understand impact of firms innovating with IT
• •Get an overview of some recent innovations driven by IT
1.Industry transformation
2.Diversity and variety
3.Personalisation
4.Experimentation
5.Plug-and-play innovations
6.New marketing opportunities
7.Use of smart technologies
8.Natural language interfaces
9.Analytics
10.Crowd sourcing
The document discusses key topics relating to managing information systems in business, including:
1) The competitive environment of business and factors that influence competition like partnering, bargaining power, barriers to entry, and threats of substitutes.
2) How information goods have properties that are expensive to produce but cheap to reproduce, and how technology lock-in, switching costs, and network externalities impact information goods.
3) How information systems can enable a company's competitive strategy and support activities in the value chain.
Implement Mapreduce with suitable example using MongoDB.bhavesh lande
The document implements a MapReduce operation using MongoDB to count the number of posts by each user with status "active" stored in a collection called c1. Four documents were inserted into the c1 collection. A MapReduce operation was run with a mapping function to emit each user_name with a count of 1, and a reducing function to sum the counts. The results of the operation were stored in a collection called "post_total". The find operation then displays the four documents inserted into the original c1 collection.
Linear regression and logistic regression are two machine learning algorithms that can be implemented in Python. Linear regression is used for predictive analysis to find relationships between variables, while logistic regression is used for classification with binary dependent variables. Support vector machines (SVMs) are another algorithm that finds the optimal hyperplane to separate data points and maximize the margin between the classes. Key terms discussed include cost functions, gradient descent, confusion matrices, and ROC curves. Code examples are provided to demonstrate implementing linear regression, logistic regression, and SVM in Python using scikit-learn.
WHY
WHERE
HOW
WHEN
WHO
FOR WHAT
Defining Data Science
• What Does a Data Science Professional Do?
• Data Science in Business
• Use Cases for Data Science
Jupyter Notebook is a popular open-source tool that allows users to create documents containing code, equations, visualizations, and text. It supports Python, R, Scala, and Julia and is commonly used for tasks like data cleaning, transformation, modeling, and visualization. R Studio is also open-source and used for operations on data using the R language, including packages for manipulation and visualization. SAS was one of the first analytics tools and was designed for descriptive and predictive analytics. It has been used for over 40 years for statistical analysis and decision making.
Defining Data Science
• What Does a Data Science Professional Do?
• Data Science in Business
• Use Cases for Data Science
• Installation of R and R studio
A substation at an airport is a vital infrastructure component that ensures reliable and efficient power distribution for all airport operations. It acts as a crucial link, converting high-voltage electricity from the main grid to the lower voltages needed for various airport facilities. This essay will explore the functions, components, and importance of a substation at an airport.
Functions of an Airport Substation:
Voltage Conversion:
Substations step down high-voltage electricity to lower levels suitable for airport operations, like terminal buildings, runways, and other facilities.
Power Distribution:
They distribute electricity to various loads, including lighting, air conditioning, navigation systems, and ground support equipment.
Grid Stability:
Substations help maintain the stability of the power grid by controlling voltage levels and managing power flows.
Redundancy and Reliability:
Airports often have redundant substations or interconnected systems to ensure uninterrupted power supply, even in case of a fault.
Switching and Control:
Substations provide switching capabilities to connect or disconnect circuits, enabling maintenance and power management.
Protection:
Substations incorporate protective devices, like circuit breakers and relays, to safeguard the power system from faults and ensure safe operation.
Key Components of an Airport Substation:
Transformers: These convert high-voltage electricity to lower voltage levels.
Circuit Breakers: These devices switch circuits on or off, protecting the system from faults.
Busbars: These are large, conductive bars that distribute electricity from transformers to other equipment.
Switchgear: This includes equipment that controls the flow of electricity, such as isolators and switches.
Control and Protection Systems: These systems monitor the substation's performance, detect faults, and automatically initiate corrective actions.
Capacitors: These improve the power factor and reduce losses in the system.
Importance of Airport Substations:
Reliable Power Supply:
Substations are essential for providing reliable power to critical airport functions, ensuring safety and efficiency.
Safe and Efficient Operations:
They contribute to the safe and efficient operation of runways, terminals, and other airport facilities.
Airport Infrastructure:
Substations are an integral part of the airport's infrastructure, enabling various operations and services.
Economic Impact:
Substations support the economic activities of the airport, including passenger and cargo handling.
Modernization and Sustainability:
Modern substations incorporate advanced technologies and systems to improve efficiency, reduce energy consumption, and enhance sustainability.
In conclusion, an airport substation is a crucial component of airport infrastructure, ensuring reliable and efficient power distribution, grid stability, and safe operations.
Impurities of Water and their Significance.pptxdhanashree78
Impart Taste, Odour, Colour, and Turbidity to water.
Presence of organic matter or industrial wastes or microorganisms (algae) imparts taste and odour to water.
Presence of suspended and colloidal matter imparts turbidity to water.
May 2025: Top 10 Read Articles Advanced Information Technologyijait
International journal of advanced Information technology (IJAIT) is a bi monthly open access peer-reviewed journal, will act as a major forum for the presentation of innovative ideas, approaches, developments, and research projects in the area advanced information technology applications and services. It will also serve to facilitate the exchange of information between researchers and industry professionals to discuss the latest issues and advancement in the area of advanced IT. Core areas of advanced IT and multi-disciplinary and its applications will be covered during the conferences.
Rigor, ethics, wellbeing and resilience in the ICT doctoral journeyYannis
The doctoral thesis trajectory has been often characterized as a “long and windy road” or a journey to “Ithaka”, suggesting the promises and challenges of this journey of initiation to research. The doctoral candidates need to complete such journey (i) preserving and even enhancing their wellbeing, (ii) overcoming the many challenges through resilience, while keeping (iii) high standards of ethics and (iv) scientific rigor. This talk will provide a personal account of lessons learnt and recommendations from a senior researcher over his 30+ years of doctoral supervision and care for doctoral students. Specific attention will be paid on the special features of the (i) interdisciplinary doctoral research that involves Information and Communications Technologies (ICT) and other scientific traditions, and (ii) the challenges faced in the complex technological and research landscape dominated by Artificial Intelligence.
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