This document provides an overview of Chapter 3 from the textbook "Database System Concepts, 6th Ed." by Silberschatz, Korth and Sudarshan. It introduces SQL, covering its history, data definition language, data types, CREATE TABLE statement, integrity constraints, updating tables, basic query structure using SELECT, FROM, and WHERE clauses, and examples of joins, renaming, and self joins.
This document provides an overview of SQL and relational database concepts. It describes the history and standards of SQL, data definition and domain types in SQL, basic query structure including the SELECT, FROM, and WHERE clauses, and DML operations like INSERT, DELETE, and ALTER TABLE. Examples of table schemas and queries involving joins, aggregation, and renaming are provided to illustrate SQL syntax and capabilities.
This document provides an overview of Chapter 3 from the textbook "Database System Concepts, 7th Ed." by Silberschatz, Korth and Sudarshan. It covers the history and components of SQL, data definition and manipulation languages, basic query structure, predicates, null values, and set operations in SQL. Key topics include the CREATE TABLE statement, data types, integrity constraints, SELECT statements, joins, ordering results, and aggregate functions.
This document discusses the SQL query language and database concepts. It covers the basic structure of SQL queries including the SELECT, FROM, and WHERE clauses. It describes how to define schemas and relations using the SQL data definition language including data types, primary keys, and foreign keys. It also discusses operations to modify databases such as INSERT, DELETE, ALTER TABLE, and DROP TABLE.
This document discusses the SQL query language and database concepts. It covers the basic structure of SQL queries including the SELECT, FROM, and WHERE clauses. It describes how to define schemas and relations using the SQL data definition language including data types, primary keys, and foreign keys. It also discusses operations to modify databases such as INSERT, DELETE, ALTER TABLE, and DROP TABLE.
This document summarizes the contents of Chapter 3 from the textbook "Database System Concepts, 5th Ed." by Silberschatz, Korth and Sudarshan. The chapter covers the basics of the SQL language, including data definition, query structure, set operations, aggregate functions, null values, views and modification of databases. Key SQL concepts are explained such as creating tables, inserting and deleting tuples, integrity constraints, joins, and aggregation. Examples are provided to illustrate SQL statements and relational algebra translations.
This document provides an overview of Chapter 3 of the textbook "Database System Concepts". It discusses the following topics in SQL:
1. Data definition language allows specification of schemas, integrity constraints, and authorization information for relations.
2. Basic queries in SQL involve SELECT, FROM, and WHERE clauses that correspond to projection, Cartesian product, and selection in relational algebra.
3. SQL supports data types, integrity constraints, insertion and deletion of tuples, and modification of tables through DROP, ALTER, and CREATE statements.
4. Advanced query features include aggregation, null values, subqueries, joins, views and modification of the database.
The document summarizes key concepts from Chapter 2 of the textbook "Database System Concepts". It introduces the relational model and relational algebra. The relational model uses relations (tables) to store data and relational algebra contains operations like select, project, join etc. to manipulate these relations. Some key points covered are the structure of relational databases, database schema, keys, relational query languages like SQL, and the core operators of relational algebra.
The document discusses SQL database concepts including:
- The SQL data definition language allows specification of schemas, integrity constraints, and other metadata.
- Relations are defined using CREATE TABLE statements which specify attributes and their data types.
- Basic queries use SELECT, FROM, and WHERE clauses to retrieve and filter tuples from one or more relations.
- Integrity constraints like PRIMARY KEY and NOT NULL can be defined to enforce data validity.
- SQL supports operations like JOIN, aggregation, sorting, and more.
This document provides an overview of SQL and relational database concepts. It describes the history and standards of SQL, data definition and domain types in SQL, basic query structure including the SELECT, FROM, and WHERE clauses, and DML operations like INSERT, DELETE, and ALTER TABLE. Examples of table schemas and queries involving joins, aggregation, and renaming are provided to illustrate SQL syntax and capabilities.
This document provides an overview of Chapter 3 from the textbook "Database System Concepts, 7th Ed." by Silberschatz, Korth and Sudarshan. It covers the history and components of SQL, data definition and manipulation languages, basic query structure, predicates, null values, and set operations in SQL. Key topics include the CREATE TABLE statement, data types, integrity constraints, SELECT statements, joins, ordering results, and aggregate functions.
This document discusses the SQL query language and database concepts. It covers the basic structure of SQL queries including the SELECT, FROM, and WHERE clauses. It describes how to define schemas and relations using the SQL data definition language including data types, primary keys, and foreign keys. It also discusses operations to modify databases such as INSERT, DELETE, ALTER TABLE, and DROP TABLE.
This document discusses the SQL query language and database concepts. It covers the basic structure of SQL queries including the SELECT, FROM, and WHERE clauses. It describes how to define schemas and relations using the SQL data definition language including data types, primary keys, and foreign keys. It also discusses operations to modify databases such as INSERT, DELETE, ALTER TABLE, and DROP TABLE.
This document summarizes the contents of Chapter 3 from the textbook "Database System Concepts, 5th Ed." by Silberschatz, Korth and Sudarshan. The chapter covers the basics of the SQL language, including data definition, query structure, set operations, aggregate functions, null values, views and modification of databases. Key SQL concepts are explained such as creating tables, inserting and deleting tuples, integrity constraints, joins, and aggregation. Examples are provided to illustrate SQL statements and relational algebra translations.
This document provides an overview of Chapter 3 of the textbook "Database System Concepts". It discusses the following topics in SQL:
1. Data definition language allows specification of schemas, integrity constraints, and authorization information for relations.
2. Basic queries in SQL involve SELECT, FROM, and WHERE clauses that correspond to projection, Cartesian product, and selection in relational algebra.
3. SQL supports data types, integrity constraints, insertion and deletion of tuples, and modification of tables through DROP, ALTER, and CREATE statements.
4. Advanced query features include aggregation, null values, subqueries, joins, views and modification of the database.
The document summarizes key concepts from Chapter 2 of the textbook "Database System Concepts". It introduces the relational model and relational algebra. The relational model uses relations (tables) to store data and relational algebra contains operations like select, project, join etc. to manipulate these relations. Some key points covered are the structure of relational databases, database schema, keys, relational query languages like SQL, and the core operators of relational algebra.
The document discusses SQL database concepts including:
- The SQL data definition language allows specification of schemas, integrity constraints, and other metadata.
- Relations are defined using CREATE TABLE statements which specify attributes and their data types.
- Basic queries use SELECT, FROM, and WHERE clauses to retrieve and filter tuples from one or more relations.
- Integrity constraints like PRIMARY KEY and NOT NULL can be defined to enforce data validity.
- SQL supports operations like JOIN, aggregation, sorting, and more.
The document discusses key concepts of relational databases and relational algebra. It defines what a relation is as a set of tuples with attributes, and covers attribute types, keys, relations schemas and instances. It also summarizes the core relational algebra operations of selection, projection, join, union, difference and Cartesian product and how they are used to manipulate and query relations.
The document provides an overview of the basic structure and features of the SQL language, including: select, from, where clauses; aggregate functions; set operations; null values; and more. It describes the typical components of an SQL query, how they map to relational algebra operations, and provides examples to illustrate various SQL concepts and capabilities.
Relational Algebra and relational queries .pptShahidSultan24
This document describes chapter 6 of the textbook "Database System Concepts, 6th Ed." which covers formal relational query languages. It introduces relational algebra as a procedural query language with basic operators like select, project, union, set difference, cartesian product, and rename. It also covers tuple and domain relational calculus. Examples of relational algebra queries are provided to find the largest salary or names of instructors and courses taught. Additional relational algebra concepts like composition of operations, set intersection, natural join, assignment, and outer join are also summarized.
This document contains lecture slides about Chapter 4 of the textbook "Database System Concepts, 7th Ed." by Silberschatz, Korth and Sudarshan. The chapter covers intermediate SQL topics like join expressions, integrity constraints, SQL data types and schemas, views, transactions, indexes and authorization. Specific topics discussed include natural joins, outer joins, integrity constraints, user-defined types, schemas and views.
This document discusses formal relational query languages, including relational algebra, tuple relational calculus, and domain relational calculus. Relational algebra is a procedural query language that uses operators like select, project, join, and set difference. Tuple relational calculus and domain relational calculus are nonprocedural query languages that use predicates and quantifiers to specify queries. Examples of queries written in each language are provided to illustrate their syntax and capabilities.
This document provides an overview of SQL (Structured Query Language) including its history, data definition and manipulation capabilities. Key topics covered include SQL's data types, basic queries using SELECT, FROM and WHERE clauses, joins, aggregation, null values, triggers and indexes. The document also discusses SQL standards over time and commercial database implementations of SQL features.
This chapter discusses SQL (Structured Query Language), the most popular language for interacting with relational database management systems. The chapter covers SQL's data definition language for defining schemas, domains, and integrity constraints. It also covers the basic SELECT statement structure for queries with FROM, WHERE, and JOIN clauses. Additional topics include views, data modification, and aggregation functions.
This chapter discusses the SQL (Structured Query Language) which is used for managing data in relational database management systems. It covers key topics in SQL including data definition, basic query structure using SELECT, FROM and WHERE clauses, set operations, aggregate functions, null values, nested subqueries, views, data modification and joined relations. The document provides examples of SQL statements for creating tables, defining domains, inserting data, querying, and modifying data.
The document discusses key concepts of the relational database model from Chapter 2 of the textbook "Database System Concepts, 6th Edition". It describes the structure of relations, which are tables made up of rows and columns. It defines entity types like attributes and tuples, and explains primary keys, foreign keys, and relationship types like one-to-one and one-to-many. It also introduces the algebraic operations of the relational algebra, which provides a declarative query language for relational databases including selection, projection, join, union and set differences.
This document provides an overview of formal relational query languages, including relational algebra, tuple relational calculus, and domain relational calculus. It discusses the basic operators of relational algebra like select, project, union, and difference. It also provides examples of queries expressed in both tuple relational calculus and domain relational calculus, and covers concepts like safety of expressions. The document is from the 6th edition of the textbook "Database System Concepts" and is intended to teach formal query languages for relational databases.
i. Being able to communicate effectively is perhaps the most important of all life skills. It is what enables us to pass information to other people, and to understand what is said to us. You only have to watch a baby listening intently to its mother and trying to repeat the sounds that she makes to understand how fundamental is the urge to communicate.
ii. Communication, at its simplest, is the act of transferring information from one place to another. It may be vocally (using voice), written (using printed or digital media such as books, magazines, websites or emails), visually (using logos, maps, charts or graphs) or non-verbally (using body language, gestures and the tone and pitch of voice). In practice, it is often a combination of several of these.
iii. Communication skills may take a lifetime to master—if indeed anyone can ever claim to have mastered them. There are, however, many things that you can do fairly easily to improve your communication skills and ensure that you are able to transmit and receive information effectively.
The document summarizes key concepts in SQL, including:
1) SQL allows defining schemas, inserting/deleting tuples, and modifying databases through commands like CREATE TABLE, INSERT, DELETE.
2) Basic queries use SELECT, FROM, WHERE clauses to project, join and filter relations similarly to relational algebra.
3) SQL supports additional features like aggregation, null values, subqueries and views.
MySQL is an SQL-based relational database management system that is compatible with standard SQL. SQL is used for data definition and modification. Data definition statements like CREATE DATABASE and CREATE TABLE are used to define the schema. Data modification statements like INSERT, UPDATE, and DELETE are used to add, modify, and remove data from tables. Queries use SELECT statements to retrieve data from one or more tables, along with WHERE and JOIN clauses to filter rows and aggregate functions to perform calculations on groups of data.
This document summarizes key concepts from Chapter 2 of the textbook "Database System Concepts" by Silberschatz, Korth and Sudarshan. It discusses the relational model, including the structure of relational databases, relational algebra operations, keys such as primary and foreign keys, and query languages. Example relations are provided to illustrate concepts like the select, project, union and cartesian product operations in relational algebra.
This document provides an overview of SQL and relational database concepts. It begins with a brief history of SQL and standards. It then covers data definition language to define database schemas, basic query structure using SELECT, FROM, and WHERE clauses, and additional SQL features like joins, null values, aggregate functions, and modifying databases. It provides examples of creating tables, inserting and deleting data, and performing various types of queries.
The document introduces common data types in SQL such as char, varchar, int, numeric, and date. It describes how to create databases and tables using SQL statements like CREATE DATABASE, CREATE TABLE, INSERT INTO, and ALTER TABLE. It also covers SQL queries using SELECT, FROM, WHERE, ORDER BY, LIKE and other clauses to retrieve and filter data from one or more tables.
This document discusses implementing information retrieval systems using relational database management systems (RDBMS). It describes representing structured document metadata and inverted indexes of terms and their frequencies in relations. It also summarizes approaches for supporting Boolean, proximity, and relevance ranking queries using SQL queries, user-defined functions, and workarounds for limitations of commercial RDBMSs. The key benefits of using RDBMSs for IR include recovery, performance, data migration, and access control.
This document summarizes key aspects of SQL (Structured Query Language) covered in Chapter 3:
1) SQL is used to define the schema of database relations, perform queries on those relations, and modify the data. It is based on relational algebra operations.
2) The basic structure of an SQL query includes SELECT, FROM, and WHERE clauses to project attributes, specify relations, and apply selection predicates respectively.
3) Data definition language (DDL) commands like CREATE TABLE define relations and their attributes. Integrity constraints can also be specified.
4) Queries return relations and can use operators, expressions, and aggregation functions on attributes in the SELECT clause.
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
The document discusses key concepts of relational databases and relational algebra. It defines what a relation is as a set of tuples with attributes, and covers attribute types, keys, relations schemas and instances. It also summarizes the core relational algebra operations of selection, projection, join, union, difference and Cartesian product and how they are used to manipulate and query relations.
The document provides an overview of the basic structure and features of the SQL language, including: select, from, where clauses; aggregate functions; set operations; null values; and more. It describes the typical components of an SQL query, how they map to relational algebra operations, and provides examples to illustrate various SQL concepts and capabilities.
Relational Algebra and relational queries .pptShahidSultan24
This document describes chapter 6 of the textbook "Database System Concepts, 6th Ed." which covers formal relational query languages. It introduces relational algebra as a procedural query language with basic operators like select, project, union, set difference, cartesian product, and rename. It also covers tuple and domain relational calculus. Examples of relational algebra queries are provided to find the largest salary or names of instructors and courses taught. Additional relational algebra concepts like composition of operations, set intersection, natural join, assignment, and outer join are also summarized.
This document contains lecture slides about Chapter 4 of the textbook "Database System Concepts, 7th Ed." by Silberschatz, Korth and Sudarshan. The chapter covers intermediate SQL topics like join expressions, integrity constraints, SQL data types and schemas, views, transactions, indexes and authorization. Specific topics discussed include natural joins, outer joins, integrity constraints, user-defined types, schemas and views.
This document discusses formal relational query languages, including relational algebra, tuple relational calculus, and domain relational calculus. Relational algebra is a procedural query language that uses operators like select, project, join, and set difference. Tuple relational calculus and domain relational calculus are nonprocedural query languages that use predicates and quantifiers to specify queries. Examples of queries written in each language are provided to illustrate their syntax and capabilities.
This document provides an overview of SQL (Structured Query Language) including its history, data definition and manipulation capabilities. Key topics covered include SQL's data types, basic queries using SELECT, FROM and WHERE clauses, joins, aggregation, null values, triggers and indexes. The document also discusses SQL standards over time and commercial database implementations of SQL features.
This chapter discusses SQL (Structured Query Language), the most popular language for interacting with relational database management systems. The chapter covers SQL's data definition language for defining schemas, domains, and integrity constraints. It also covers the basic SELECT statement structure for queries with FROM, WHERE, and JOIN clauses. Additional topics include views, data modification, and aggregation functions.
This chapter discusses the SQL (Structured Query Language) which is used for managing data in relational database management systems. It covers key topics in SQL including data definition, basic query structure using SELECT, FROM and WHERE clauses, set operations, aggregate functions, null values, nested subqueries, views, data modification and joined relations. The document provides examples of SQL statements for creating tables, defining domains, inserting data, querying, and modifying data.
The document discusses key concepts of the relational database model from Chapter 2 of the textbook "Database System Concepts, 6th Edition". It describes the structure of relations, which are tables made up of rows and columns. It defines entity types like attributes and tuples, and explains primary keys, foreign keys, and relationship types like one-to-one and one-to-many. It also introduces the algebraic operations of the relational algebra, which provides a declarative query language for relational databases including selection, projection, join, union and set differences.
This document provides an overview of formal relational query languages, including relational algebra, tuple relational calculus, and domain relational calculus. It discusses the basic operators of relational algebra like select, project, union, and difference. It also provides examples of queries expressed in both tuple relational calculus and domain relational calculus, and covers concepts like safety of expressions. The document is from the 6th edition of the textbook "Database System Concepts" and is intended to teach formal query languages for relational databases.
i. Being able to communicate effectively is perhaps the most important of all life skills. It is what enables us to pass information to other people, and to understand what is said to us. You only have to watch a baby listening intently to its mother and trying to repeat the sounds that she makes to understand how fundamental is the urge to communicate.
ii. Communication, at its simplest, is the act of transferring information from one place to another. It may be vocally (using voice), written (using printed or digital media such as books, magazines, websites or emails), visually (using logos, maps, charts or graphs) or non-verbally (using body language, gestures and the tone and pitch of voice). In practice, it is often a combination of several of these.
iii. Communication skills may take a lifetime to master—if indeed anyone can ever claim to have mastered them. There are, however, many things that you can do fairly easily to improve your communication skills and ensure that you are able to transmit and receive information effectively.
The document summarizes key concepts in SQL, including:
1) SQL allows defining schemas, inserting/deleting tuples, and modifying databases through commands like CREATE TABLE, INSERT, DELETE.
2) Basic queries use SELECT, FROM, WHERE clauses to project, join and filter relations similarly to relational algebra.
3) SQL supports additional features like aggregation, null values, subqueries and views.
MySQL is an SQL-based relational database management system that is compatible with standard SQL. SQL is used for data definition and modification. Data definition statements like CREATE DATABASE and CREATE TABLE are used to define the schema. Data modification statements like INSERT, UPDATE, and DELETE are used to add, modify, and remove data from tables. Queries use SELECT statements to retrieve data from one or more tables, along with WHERE and JOIN clauses to filter rows and aggregate functions to perform calculations on groups of data.
This document summarizes key concepts from Chapter 2 of the textbook "Database System Concepts" by Silberschatz, Korth and Sudarshan. It discusses the relational model, including the structure of relational databases, relational algebra operations, keys such as primary and foreign keys, and query languages. Example relations are provided to illustrate concepts like the select, project, union and cartesian product operations in relational algebra.
This document provides an overview of SQL and relational database concepts. It begins with a brief history of SQL and standards. It then covers data definition language to define database schemas, basic query structure using SELECT, FROM, and WHERE clauses, and additional SQL features like joins, null values, aggregate functions, and modifying databases. It provides examples of creating tables, inserting and deleting data, and performing various types of queries.
The document introduces common data types in SQL such as char, varchar, int, numeric, and date. It describes how to create databases and tables using SQL statements like CREATE DATABASE, CREATE TABLE, INSERT INTO, and ALTER TABLE. It also covers SQL queries using SELECT, FROM, WHERE, ORDER BY, LIKE and other clauses to retrieve and filter data from one or more tables.
This document discusses implementing information retrieval systems using relational database management systems (RDBMS). It describes representing structured document metadata and inverted indexes of terms and their frequencies in relations. It also summarizes approaches for supporting Boolean, proximity, and relevance ranking queries using SQL queries, user-defined functions, and workarounds for limitations of commercial RDBMSs. The key benefits of using RDBMSs for IR include recovery, performance, data migration, and access control.
This document summarizes key aspects of SQL (Structured Query Language) covered in Chapter 3:
1) SQL is used to define the schema of database relations, perform queries on those relations, and modify the data. It is based on relational algebra operations.
2) The basic structure of an SQL query includes SELECT, FROM, and WHERE clauses to project attributes, specify relations, and apply selection predicates respectively.
3) Data definition language (DDL) commands like CREATE TABLE define relations and their attributes. Integrity constraints can also be specified.
4) Queries return relations and can use operators, expressions, and aggregation functions on attributes in the SELECT clause.
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
Sudheer Mechineni, Head of Application Frameworks, Standard Chartered Bank
Discover how Standard Chartered Bank harnessed the power of Neo4j to transform complex data access challenges into a dynamic, scalable graph database solution. This keynote will cover their journey from initial adoption to deploying a fully automated, enterprise-grade causal cluster, highlighting key strategies for modelling organisational changes and ensuring robust disaster recovery. Learn how these innovations have not only enhanced Standard Chartered Bank’s data infrastructure but also positioned them as pioneers in the banking sector’s adoption of graph technology.
UiPath Test Automation using UiPath Test Suite series, part 5DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 5. In this session, we will cover CI/CD with devops.
Topics covered:
CI/CD with in UiPath
End-to-end overview of CI/CD pipeline with Azure devops
Speaker:
Lyndsey Byblow, Test Suite Sales Engineer @ UiPath, Inc.
HCL Notes and Domino License Cost Reduction in the World of DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-and-domino-license-cost-reduction-in-the-world-of-dlau/
The introduction of DLAU and the CCB & CCX licensing model caused quite a stir in the HCL community. As a Notes and Domino customer, you may have faced challenges with unexpected user counts and license costs. You probably have questions on how this new licensing approach works and how to benefit from it. Most importantly, you likely have budget constraints and want to save money where possible. Don’t worry, we can help with all of this!
We’ll show you how to fix common misconfigurations that cause higher-than-expected user counts, and how to identify accounts which you can deactivate to save money. There are also frequent patterns that can cause unnecessary cost, like using a person document instead of a mail-in for shared mailboxes. We’ll provide examples and solutions for those as well. And naturally we’ll explain the new licensing model.
Join HCL Ambassador Marc Thomas in this webinar with a special guest appearance from Franz Walder. It will give you the tools and know-how to stay on top of what is going on with Domino licensing. You will be able lower your cost through an optimized configuration and keep it low going forward.
These topics will be covered
- Reducing license cost by finding and fixing misconfigurations and superfluous accounts
- How do CCB and CCX licenses really work?
- Understanding the DLAU tool and how to best utilize it
- Tips for common problem areas, like team mailboxes, functional/test users, etc
- Practical examples and best practices to implement right away
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
Infrastructure Challenges in Scaling RAG with Custom AI modelsZilliz
Building Retrieval-Augmented Generation (RAG) systems with open-source and custom AI models is a complex task. This talk explores the challenges in productionizing RAG systems, including retrieval performance, response synthesis, and evaluation. We’ll discuss how to leverage open-source models like text embeddings, language models, and custom fine-tuned models to enhance RAG performance. Additionally, we’ll cover how BentoML can help orchestrate and scale these AI components efficiently, ensuring seamless deployment and management of RAG systems in the cloud.
Driving Business Innovation: Latest Generative AI Advancements & Success StorySafe Software
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
TrustArc Webinar - 2024 Global Privacy SurveyTrustArc
How does your privacy program stack up against your peers? What challenges are privacy teams tackling and prioritizing in 2024?
In the fifth annual Global Privacy Benchmarks Survey, we asked over 1,800 global privacy professionals and business executives to share their perspectives on the current state of privacy inside and outside of their organizations. This year’s report focused on emerging areas of importance for privacy and compliance professionals, including considerations and implications of Artificial Intelligence (AI) technologies, building brand trust, and different approaches for achieving higher privacy competence scores.
See how organizational priorities and strategic approaches to data security and privacy are evolving around the globe.
This webinar will review:
- The top 10 privacy insights from the fifth annual Global Privacy Benchmarks Survey
- The top challenges for privacy leaders, practitioners, and organizations in 2024
- Key themes to consider in developing and maintaining your privacy program
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
Communications Mining Series - Zero to Hero - Session 1DianaGray10
This session provides introduction to UiPath Communication Mining, importance and platform overview. You will acquire a good understand of the phases in Communication Mining as we go over the platform with you. Topics covered:
• Communication Mining Overview
• Why is it important?
• How can it help today’s business and the benefits
• Phases in Communication Mining
• Demo on Platform overview
• Q/A
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
available on those devices, but many of the features provide convenience and capability but sacrifice security. This best practices guide outlines steps the users can take to better protect personal devices and information.
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!SOFTTECHHUB
As the digital landscape continually evolves, operating systems play a critical role in shaping user experiences and productivity. The launch of Nitrux Linux 3.5.0 marks a significant milestone, offering a robust alternative to traditional systems such as Windows 11. This article delves into the essence of Nitrux Linux 3.5.0, exploring its unique features, advantages, and how it stands as a compelling choice for both casual users and tech enthusiasts.
Building Production Ready Search Pipelines with Spark and MilvusZilliz
Spark is the widely used ETL tool for processing, indexing and ingesting data to serving stack for search. Milvus is the production-ready open-source vector database. In this talk we will show how to use Spark to process unstructured data to extract vector representations, and push the vectors to Milvus vector database for search serving.