Emerging Technologies in IT

The document discusses the impact of information technology on society. It states that as IT advances, society will divide into two groups: technophiles who embrace new technologies, and technophobes who resist them, potentially growing to 25% of the population. It also argues that IT will radically change the definition of society, with personal interests becoming more important than shared customs, culture or location. The conclusion suggests that technological researchers should consider social impacts and work to seamlessly integrate new technologies into peoples' lives to avoid technologies failing due acceptance issues.

Mike McBride will provide a look at the Industrial IoT (IIoT) landscape and the OT/IT convergence. He will cover several use cases including healthcare, entertainment and smart buildings. He will cover the challenges IIoT networking faces with emerging technologies and how edge computing will provide increased performance, security and reliability. Mike will discuss the various Edge Computing standards & opensource forums along with proposed architectures. And Mike will present new solutions being proposed (ICN, slicing, Blockchain) to support the bandwidth, latency and security requirements within Industrial verticals. About the speaker: As Sr. Director of Innovation & Strategy, within Huawei's IP Network BU, Mike leads Industrial IoT, Edge Computing and IP/SDN architecture, standardization, and strategy across product lines and industry forums. He leads architecture and standardization activities within the IIc and BBF and has served as an IETF Working Group chair for 15 years. Mike has led emerging technology projects within opensource communities and played a key role in the formation of OPEN-O (Now ONAP). He is an Ericsson alum where he developed and directed SDN/NFV network architectures. And for many years with Cisco, Mike supported customers, worked in development teams and managed mobility, wireless and video projects across BUs. Mike began his career supporting customers at Apple Computer. He resides in Orange County, CA

Big data is large amounts of unstructured data that require new techniques and tools to analyze. Key drivers of big data growth are increased storage capacity, processing power, and data availability. Big data analytics can uncover hidden patterns to provide competitive advantages and better business decisions. Applications include healthcare, homeland security, finance, manufacturing, and retail. The global big data market is expected to grow significantly, with India's market projected to reach $1 billion by 2015. This growth will increase demand for data scientists and analysts to support big data solutions and technologies like Hadoop and NoSQL databases.

If it’s that time to make analysis for the predicament of the management system or simply to present deafening data in front of your qualified team then you have reached the right match. SlideTeam presents you classy and eternally approaching PowerPoint slides for big data analytics. Data analysis agendas and big data plans are shown through captivating icons and subheadings for a precise and interesting approach. This unique PPT slide is useful for studying business and marketing related topics, approaching the correct conclusions and keeping a track on business growth. Make an outstanding presentation for your viewers with this unique PPT slide and deliver your message in an effective manner using Big data analytics Powerpoint Presentation slide and make your pathways more defining. Most of the elements of the slide are highly customizable. The text boxes help you in adding more information about the point mentioned and its associated icon. Every detail in our Big Data Analytics Powerpoint Presentation Slide is doubly cross checked. You can be certain of it's authenticity. https://bit.ly/3fvnRVK

This document provides an overview of data science including what is big data and data science, applications of data science, and system infrastructure. It then discusses recommendation systems in more detail, describing them as systems that predict user preferences for items. A case study on recommendation systems follows, outlining collaborative filtering and content-based recommendation algorithms, and diving deeper into collaborative filtering approaches of user-based and item-based filtering. Challenges with collaborative filtering are also noted.

Artificial intelligence (AI) is the ability of a computer or a robot controlled by a computer to do tasks that are usually done by humans because they require human intelligence and discernment. The field was founded on the assumption that human intelligence "can be so precisely described that a machine can be made to simulate it". This raises philosophical arguments about the mind and the ethics of creating artificial beings endowed with human-like intelligence.

The document discusses current trends in information technology and its impact. It covers how IT has improved productivity, efficiency, and customer service in organizations and for consumers. It also discusses how IT challenges businesses to keep pace with new technologies in competitive environments. The document defines information technology and provides examples of common IT uses in businesses like databases, word processing, computer networks, and the internet.

A brief overview of artificial intelligence (AI), followed by a few examples of practical use within small businesses, large enterprises, and nonprofits.

This document discusses digital twin technology, including its definition, history, importance, enabling technologies, and applications. A digital twin is a virtual representation of a physical object that can dynamically change as the physical object is monitored. Gartner predicts that by 2021, 50% of large industrial companies will use digital twins to gain a 10% improvement in effectiveness. Digital twins are enabled by technologies like IoT, cloud computing, big data analytics, blockchain, and VR/AR. They have applications in customer experience, performance tuning, digital machine learning, healthcare, smart cities, and maintenance. While digital twins allow for improved products, some cons include high costs and a complex infrastructure requirement.

This Data Science Presentation will help you in understanding what is Data Science, why we need Data Science, prerequisites for learning Data Science, what does a Data Scientist do, Data Science lifecycle with an example and career opportunities in Data Science domain. You will also learn the differences between Data Science and Business intelligence. The role of a data scientist is one of the sexiest jobs of the century. The demand for data scientists is high, and the number of opportunities for certified data scientists is increasing. Every day, companies are looking out for more and more skilled data scientists and studies show that there is expected to be a continued shortfall in qualified candidates to fill the roles. So, let us dive deep into Data Science and understand what is Data Science all about. This Data Science Presentation will cover the following topics: 1. Need for Data Science? 2. What is Data Science? 3. Data Science vs Business intelligence 4. Prerequisites for learning Data Science 5. What does a Data scientist do? 6. Data Science life cycle with use case 7. Demand for Data scientists This Data Science with Python course will establish your mastery of data science and analytics techniques using Python. With this Python for Data Science Course, you’ll learn the essential concepts of Python programming and become an expert in data analytics, machine learning, data visualization, web scraping and natural language processing. Python is a required skill for many data science positions, so jumpstart your career with this interactive, hands-on course. Why learn Data Science? Data Scientists are being deployed in all kinds of industries, creating a huge demand for skilled professionals. Data scientist is the pinnacle rank in an analytics organization. Glassdoor has ranked data scientist first in the 25 Best Jobs for 2016, and good data scientists are scarce and in great demand. As a data you will be required to understand the business problem, design the analysis, collect and format the required data, apply algorithms or techniques using the correct tools, and finally make recommendations backed by data. The Data Science with python is recommended for: 1. Analytics professionals who want to work with Python 2. Software professionals looking to get into the field of analytics 3. IT professionals interested in pursuing a career in analytics 4. Graduates looking to build a career in analytics and data science 5. Experienced professionals who would like to harness data science in their fields

This presentation was shown at the Artificial Intelligence in Health Care event in Toronto Nov 16 2017. The discussion was to introduce various applications of artificial intelligence and machine learning in the health care field.

Introduction to various data science. From the very beginning of data science idea, to latest designs, changing trends, technologies what make then to the application that are already in real world use as we of now.

This document presents a paper on artificial intelligence by Ashish Anil Sadavarti of NIT Polytechnic Electronics & Telecommunications branch. It discusses artificial intelligence techniques including rule/logic-based approaches using logical rules and machine learning based on detecting patterns in data. Machine learning is the dominant AI approach today, powering applications like self-driving vehicles and recommendations. Hybrid systems also combine approaches. While AI can automate complex tasks, it remains limited compared to human intelligence and often requires human oversight.

A digital twin is a digital profile of a physical object or system that uses sensor data to help optimize performance. Sensors on physical objects collect data and send it to the digital twin, and the interaction between the physical object and digital twin can optimize performance through predictive maintenance. Digital twins are useful because they bridge the physical and digital worlds by translating real-world sensor data into information that can be processed digitally to help optimize businesses and systems. Examples of applications of digital twins include performance tuning, digital machine building, healthcare, smart cities, and predictive maintenance.

The document presents an overview of artificial intelligence (AI) created by a group of students. It defines AI as the simulation of human intelligence by machines. The document then discusses the history of AI, current applications including healthcare, education, and aviation, as well as goals, approaches, tools, platforms, advantages, and disadvantages. It notes that while AI can perform tasks efficiently with little error, it may also decrease human labor and pose ethical issues. The future of AI is discussed, with predictions that speech and image recognition will improve human-device interaction and AI will start to operate more autonomously.

Introduction to Artificial Intelligence is for the mid level managers giving information about what is AI, AI levels, types of AI, where AI is used. You can also know the difference between AI vs Machine learning vs Deep learning to understand expert system in a better way for business growth. https://bit.ly/2V0reNa

A Seminar Presentation on Big Data for Students. Big data refers to a process that is used when traditional data mining and handling techniques cannot uncover the insights and meaning of the underlying data. Data that is unstructured or time sensitive or simply very large cannot be processed by relational database engines. This type of data requires a different processing approach called big data, which uses massive parallelism on readily-available hardware.

DBMS stands for Database Management System and is software that manages databases. It provides tools for creating, organizing, and managing databases. A database is a collection of related data organized for easy access, management, and updating. There are different data models like hierarchical, network, and relational models that describe how data is structured and stored. Common DBMS software includes Oracle, SQL Server, and Access. DBMS provides advantages like data consistency, redundancy control, and backup/recovery capabilities.

The document provides an overview of database management systems (DBMS). It begins with introducing the presenters and objective to make the audience knowledgeable about DBMS fundamentals and improvements. The contents section outlines topics like introduction, data, information, database components, what is a DBMS, database administrator, database languages, advantages and disadvantages of DBMS, examples of DBMS like SQL Server, and applications of DBMS.

What is Data ? What is Information? Data Models, Schema and Instances Components of Database System What is DBMS ? Database Languages Applications of DBMS Introduction to Databases Fundamentals of Data Modeling and Database Design Database Normalization Types of keys in database management system Distributed Database

This document provides an overview of data management and IT infrastructure. It discusses data versus information, basic concepts of data, databases, and database management systems. It covers database models including hierarchical, network, relational, and object-oriented. It also discusses database applications, benefits of a database approach, centralized versus distributed databases, relational databases, data warehouses, and data mining. Finally, it provides an introduction to IT infrastructure and discusses the evolution of IT infrastructure from the 1950s to present.

The document provides an overview of key concepts in database management systems including: - The benefits of using a DBMS over file systems such as data independence, data integrity, and concurrent access. - The three levels of abstraction in a DBMS - physical, logical, and view level. - Common data models including relational, entity-relationship, and object-oriented models. - Database languages including data manipulation languages (DML) like SQL and data definition languages (DDL) to define schemas. - Key components of a DBMS including storage management, query processing, and transaction management. - Roles of database users and administrators.

This document provides an overview of a database management systems course, including slides related to key concepts. The slides cover topics such as database applications, the benefits of using a DBMS over file systems, data models, SQL, database users and administrators, data storage and querying, and database system architectures. The document is intended to introduce students to fundamental DBMS concepts through explanatory slides.

The document provides a history of database development from the 1950s to the present. It describes how data storage evolved from magnetic tapes to hard disks, allowing for direct data access. In the late 1960s and 1970s, network and hierarchical data models became widespread and Ted Codd defined the relational data model, winning an ACM Turing award for this work. The relational model then became the standard in commercial database systems during the 1980s. Object-oriented and distributed database systems emerged in subsequent decades as data storage capabilities expanded enormously.

The document discusses database essentials including database management systems, database applications, the purpose of database systems, data models, database languages, database architecture, and the relational data model. Specifically, it defines what a DBMS is, provides examples of common database applications, describes why databases were developed to address limitations of file processing systems, outlines several data models including the relational model, discusses database languages for defining and manipulating data, presents the client-server architecture of database systems, and explains key concepts of the relational model including tables, tuples, attributes, relations, and domains.

This chapter discusses databases and database management systems. It defines what a database is, including tables, fields, records and keys. It describes important database concepts like data integrity, security and privacy. It also covers different database classifications, models and how databases are commonly used on the web. The relational model is highlighted as the most widely used today for organizing data in tables related by common fields.

This chapter discusses databases and database management systems. It defines what a database is, including tables, fields, records and keys. It describes common database classifications like relational, object-oriented and multidimensional databases. It also discusses important database concepts like data integrity, security and normalization. The chapter explains how to design, create and maintain a relational database, and how databases are often used on the web.

The document provides an overview of database management systems (DBMS). It defines DBMS as software that creates, organizes, and manages databases. It discusses key DBMS concepts like data models, schemas, instances, and database languages. Components of a database system including users, software, hardware, and data are described. Popular DBMS examples like Oracle, SQL Server, and MS Access are listed along with common applications of DBMS in various industries.

A DBMS is a software package that controls the creation, organization, storage, retrieval, sharing, and security of data in a database. It allows for multi-user access and uses query languages to search, sort, and retrieve data. There are several data models including hierarchical, network, relational, multidimensional, and object models. A DBMS is used in many applications such as banking, airlines, universities, sales, manufacturing, and more. It provides advantages like representing complex relationships, controlling redundancy, and sharing data across applications but also has disadvantages such as complex design, high costs, and required training.

The document discusses different database concepts: 1) A database is a collection of organized data that can be easily retrieved, inserted, and deleted. Database management systems (DBMS) like MySQL and Oracle are software used to manage databases. 2) The two main data models are the relational model, which organizes data into tables and relations, and the object-oriented model, which represents data as objects with properties and methods. 3) DBMS provide advantages like data sharing, backup/recovery, security, and independence between data and applications. However, they also have disadvantages such as higher costs and complexity.

This document provides an overview of database management systems (DBMS). It defines what a DBMS is, its main components, and what it is used for. A DBMS is software that allows users to create, access, and manage a database. It discusses what data and information are, examples of databases, data models and schemas, database languages, architectures, examples of popular DBMS software, and applications of DBMS.

The document provides an overview of database management systems (DBMS). It discusses the history of DBMS beginning in the early 1960s. It also covers data models like hierarchical, network, relational, object-oriented, and deductive. The document describes the architecture and components of a DBMS. It lists advantages like data independence and security as well as disadvantages such as costs. Key concepts covered include data storage, processing, and retrieval.

The document discusses the history of database management and database models through 6 generations from 1900 to present. It describes the evolution from early manual record keeping systems to current big data technologies. Key database models discussed include hierarchical, network, relational, object-oriented, and dimensional models. The document also covers topics like data warehousing and data mining.

Prerequisies of DBMS Course Objectives of DBMS Syllabus What is the meaning of data and database DBMS History of DBMS Different Databases available in Market Storage areas Why to Learn DBMS? Peoples who work with Databases Applications of DBMS

This document provides information about a database management systems (DBMS) course syllabus. It includes the course objectives, which are to understand basic database concepts, master SQL, understand relational database design principles, and become familiar with transaction processing and concurrency control. The syllabus outlines 5 units that will be covered: data models and languages, the relational model and SQL, normalization, transaction management and recovery, and query processing. Required textbooks and references are also listed.

This document outlines the syllabus for a Database Management Systems course. It includes 5 units that cover database concepts, the relational model, SQL, normalization, transaction management, recovery, and query processing. The objectives are to understand basic database concepts, master SQL, understand relational design principles, and become familiar with transaction processing, storage structures, and query optimization techniques. Key topics include the entity-relationship model, relational algebra, normalization, concurrency control, crash recovery, and query processing and optimization.

The document discusses several aspects of database design including: - Logical design which involves deciding on the database schema and relation schemas. - Physical design which involves deciding on the physical layout of the database. - Entity-relationship modeling which involves modeling an enterprise as entities and relationships. - Extensions to the relational model to include object orientation and complex data types.

1. What are the differences between a DBMS and RDBMS? 2. Explain the terms database and DBMS. Also, mention the different types of DBMS. 3. What are the advantages of DBMS? 4. Mention the different languages present in DBMS 5. What do you understand by query optimization? 6. Do we consider NULL values the same as that of blank space or zero? 7. What do you understand by aggregation and atomicity? 8. What are the different levels of abstraction in the DBMS? 9. What is an entity-relationship model? 10. What do you understand by the terms Entity, Entity Type, and Entity Set in DBMS? 11. What are relationships and mention different types of relationships in the DBMS 12. What is concurrency control? 13. What are the ACID properties in DBMS? 14. What is normalization and what are the different types of normalization? 15. What are the different types of keys in the database? 16. What do you understand by correlated subqueries in DBMS? 17. Explain Database partitioning and its importance. 18. What do you understand by functional dependency and transitive dependency in DBMS? 19. What is the difference between two and three-tier architectures? 20. Mention the differences between Unique Key and Primary Key 21. What is a checkpoint in DBMS and when does it occur? 22. Mention the differences between Trigger and Stored Procedures 23. What are the differences between Hash join, Merge join and Nested loops? 24. What do you understand by Proactive, Retroactive and Simultaneous Update? 25. What are indexes? Mention the differences between the clustered and non-clustered index 26. What do you understand by intension and extension? 27. What do you understand by cursor? Mention the different types of cursor A cursor is a database object which helps in manipulating data, row by row and represents a result set. 28. Explain the terms specialization and generalization 29. What do you understand by Data Independence? 30. What are the different integrity rules present in the DBMS? 31. What does Fill Factor concept mean with respect to indexes? 32. What is Index hunting and how does it help in improving query performance? 33. What are the differences between network and hierarchical database model? 34. Explain what is a deadlock and mention how it can be resolved? 35. What are the differences between an exclusive lock and a shared lock?

=>Concept of Governance =>Risk and Control (GRC) as applicable to IT operational risk =>Importance of documentation =>DATA FLOW DIAGRAM for every application =>Review of changes in the Data flow, reporting, etc. =>Parameters for review =>Importance of review on SLA compliance =>Reporting to IT Strategy committee, Board etc.

This document provides an introduction to database management systems (DBMS). It defines key terms like database, DBMS, and database system. It describes the common components of a database including database administrators, designers, and end users. It outlines advantages of DBMS over file processing systems and discusses data models, database schemas and instances, DBMS architecture including internal, conceptual and external schemas, and data independence.

CASE (COMPUTER AIDED SOFTWARE ENGINEERING) CASE and its Scope CASE support in software life cycle documentation project management Internal Interface Reverse Software Engineering Architecture of CASE environment.

SOFTWARE RELIABILITY AND QUALITY ASSURANCE Reliability issues Reliability metrics Reliability growth modeling Software quality ISO 9000 certification for software industry SEI capability maturity model comparison between ISO and SEI CMM

Different Types of Software Testing Verification Validation Unit Testing Beta Testing Alpha Testing Black Box Testing White Box testing Error Bug

Software Testing Different Types of Software Testing Verification Validation Unit Testing Beta Testing Alpha Testing Black Box Testing White Box testing Error Bug

Coding Top-Down and Bottom –Up programming Structured programming Information hiding Programming style and Internal documentation

Software Design Design principles Problem partitioning Abstraction Top down and bottom up-design Structured approach Functional versus object oriented approach Design specifications and verification Monitoring and control Cohesiveness Coupling Fourth generation techniques Functional independence Software Architecture Transaction and Transform Mapping

This document discusses different software development life cycle (SDLC) models including iterative and spiral models. The iterative model involves building a product incrementally in iterations, with requirements evolving in each iteration based on user feedback. The spiral model similarly progresses in iterations but places more emphasis on risk analysis. Each spiral involves planning, risk analysis, engineering, and evaluation phases. The document also covers advantages and disadvantages of each model, as well as the role of management in software projects, including planning, monitoring and control, and termination analysis.

Software Lifecycle Models / Software Development Models Types of Software development models Waterfall Model Features of Waterfall Model Phase of Waterfall Model Prototype Model Advantages of Prototype Model Disadvantages of Prototype model V Model Advantages of V-model Disadvantages of V-model When to use the V-model Incremental Model ITERATIVE AND INCREMENTAL DEVELOPMENT INCREMENTAL MODEL LIFE CYCLE When to use the Incremental model Rapid Application Development RAD Model phases in the rapid application development (RAD) model Advantages of the RAD model Disadvantages of RAD model When to use RAD model Agile Model Advantages of Agile model Disadvantages of Agile model When to use Agile model

Introduction to software engineering Software products Why Software is Important? Software costs Features of Software? Software Applications Software—New Categories Software Engineering Importance of Software Engineering Essential attributes / Characteristics of good software Software Components Software Process Five Activities of a Generic Process framework Relative Costs of Fixing Software Faults Software Qualities Software crisis Software Development Stages/SDLC What is Software Verification Advantages of Software Verification Advantages of Validation

Cloud Computing Categories of Cloud Computing SaaS PaaS IaaS Threads of Cloud Computing Insurance Challenges Cloud Solutions Security of the Insurance Industry Cloud Solutions Insurance Security in the Insurance Industry with respect to Indian market

Application Software Applications Software Software Types Task-Oriented Productivity Software Business Software Application Software and Ethics Computers and People

Application Software – Horizontal & Vertical Software Software applications Common software features General-purpose applications Software suites Integrated software

Software: Systems and Application Software Identify and briefly describe the functions of the two basic kinds of software Outline the role of the operating system and identify the features of several popular operating systems Discuss how application software can support personal, workgroup, and enterprise business objectives Identify three basic approaches to developing application software and discuss the pros and cons of each Outline the overall evolution and importance of programming languages and clearly differentiate among the generations of programming languages Identify several key software issues and trends that have an impact on organizations and individuals

Programming Languages A formal language for describing computation? A “user interface” to a computer? Syntax + semantics? Compiler, or interpreter, or translator? A tool to support a programming paradigm?

This document discusses various number coding systems and data storage methods used in computing. It covers 2's complement for binary numbers, binary coded decimal, Gray codes, and ASCII character encoding. Data is stored in binary registers and can be transferred between registers using digital logic circuits. Building the processing, storage, and communication components of a computer allows information to be input, stored, and transferred.

Introduction to Computer Programming Higher Level Programming Low Level Programming Interpreters and Compilers

PROGRAMMING AND LANGUAGES Describe the six steps of programming Discuss design tools Describe program testing Describe CASE tools & object-oriented software development Explain the five generations of programming languages

NLC Grade 3 PPT week 1 ................................................

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Join educators from the US and worldwide at this year’s conference, themed “Strategies for Proficiency & Acquisition,” to learn from top experts in world language teaching.

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Howe Writing Center - Orientation Summer 2024

Presentations by Adriano Linzarini and Daniel Catarino da Silva of the OECD Rethinking Assessment of Social and Emotional Skills project from the OECD webinar "Innovations in measuring social and emotional skills and what AI will bring next" on 5 July 2024

Sequence numbers are mainly used to identify or differentiate each record in a module. Sequences are customizable and can be configured in a specific pattern such as suffix, prefix or a particular numbering scheme. This slide will show how to create sequence numbers in odoo 17.

NLC Lessons Grade 10

Slide 1 Is Email Marketing Really Effective in 2024? Yes, Email Marketing is still a great method for direct marketing. Slide 2 In this article we will cover: - What is Email Marketing? - Pros and cons of Email Marketing. - Tools available for Email Marketing. - Ways to make Email Marketing effective. Slide 3 What Is Email Marketing? Using email to contact customers is called Email Marketing. It's a quiet and effective communication method. Mastering it can significantly boost business. In digital marketing, two long-term assets are your website and your email list. Social media apps may change, but your website and email list remain constant. Slide 4 Types of Email Marketing: 1. Welcome Emails 2. Information Emails 3. Transactional Emails 4. Newsletter Emails 5. Lead Nurturing Emails 6. Sponsorship Emails 7. Sales Letter Emails 8. Re-Engagement Emails 9. Brand Story Emails 10. Review Request Emails Slide 5 Advantages Of Email Marketing 1. Cost-Effective: Cheaper than other methods. 2. Easy: Simple to learn and use. 3. Targeted Audience: Reach your exact audience. 4. Detailed Messages: Convey clear, detailed messages. 5. Non-Disturbing: Less intrusive than social media. 6. Non-Irritating: Customers are less likely to get annoyed. 7. Long Format: Use detailed text, photos, and videos. 8. Easy to Unsubscribe: Customers can easily opt out. 9. Easy Tracking: Track delivery, open rates, and clicks. 10. Professional: Seen as more professional; customers read carefully. Slide 6 Disadvantages Of Email Marketing: 1. Irrelevant Emails: Costs can rise with irrelevant emails. 2. Poor Content: Boring emails can lead to disengagement. 3. Easy Unsubscribe: Customers can easily leave your list. Slide 7 Email Marketing Tools Choosing a good tool involves considering: 1. Deliverability: Email delivery rate. 2. Inbox Placement: Reaching inbox, not spam or promotions. 3. Ease of Use: Simplicity of use. 4. Cost: Affordability. 5. List Maintenance: Keeping the list clean. 6. Features: Regular features like Broadcast and Sequence. 7. Automation: Better with automation. Slide 8 Top 5 Email Marketing Tools: 1. ConvertKit 2. Get Response 3. Mailchimp 4. Active Campaign 5. Aweber Slide 9 Email Marketing Strategy To get good results, consider: 1. Build your own list. 2. Never buy leads. 3. Respect your customers. 4. Always provide value. 5. Don’t email just to sell. 6. Write heartfelt emails. 7. Stick to a schedule. 8. Use photos and videos. 9. Segment your list. 10. Personalize emails. 11. Ensure mobile-friendliness. 12. Optimize timing. 13. Keep designs clean. 14. Remove cold leads. Slide 10 Uses of Email Marketing: 1. Affiliate Marketing 2. Blogging 3. Customer Relationship Management (CRM) 4. Newsletter Circulation 5. Transaction Notifications 6. Information Dissemination 7. Gathering Feedback 8. Selling Courses 9. Selling Products/Services Read Full Article: https://digitalsamaaj.com/is-email-marketing-effective-in-2024/

Curricuum Map in Grade 7 English aligned with matatag

(𝐓𝐋𝐄 𝟏𝟎𝟎) (𝐋𝐞𝐬𝐬𝐨𝐧 𝟏.𝟎)-𝐅𝐢𝐧𝐚𝐥𝐬 Lesson Outcome: -Students will understand the basics of gardening, including the importance of soil, water, and sunlight for plant growth. They will learn to identify and use essential gardening tools, plant seeds, and seedlings properly, and manage common garden pests using eco-friendly methods.

In Odoo 17, confirmed and uninvoiced sales orders are now factored into a partner's total receivables. As a result, the credit limit warning system now considers this updated calculation, leading to more accurate and effective credit management.

DANH SÁCH THÍ SINH XÉT TUYỂN SỚM ĐỦ ĐIỀU KIỆN TRÚNG TUYỂN ĐẠI HỌC CHÍNH QUY NĂM 2024 KHỐI NGÀNH NGOÀI SƯ PHẠM

Chapter 2 Era of One party Dominance Class 12 Political Science Notes

In Odoo 17, sample data serves as a valuable resource for users seeking to familiarize themselves with the functionalities and capabilities of the software prior to integrating their own information. In this slide we are going to discuss about how to show sample data to a tree view and a kanban view.

As artificial intelligence continues to evolve, understanding the complexities and regulations regarding AI risk management is more crucial than ever. Amongst others, the webinar covers: • ISO/IEC 42001 standard, which provides guidelines for establishing, implementing, maintaining, and continually improving AI management systems within organizations • insights into the European Union's landmark legislative proposal aimed at regulating AI • framework and methodologies prescribed by ISO/IEC 23894 for identifying, assessing, and mitigating risks associated with AI systems Presenters: Miriama Podskubova - Attorney at Law Miriama is a seasoned lawyer with over a decade of experience. She specializes in commercial law, focusing on transactions, venture capital investments, IT, digital law, and cybersecurity, areas she was drawn to through her legal practice. Alongside preparing contract and project documentation, she ensures the correct interpretation and application of European legal regulations in these fields. Beyond client projects, she frequently speaks at conferences on cybersecurity, online privacy protection, and the increasingly pertinent topic of AI regulation. As a registered advocate of Slovak bar, certified data privacy professional in the European Union (CIPP/e) and a member of the international association ELA, she helps both tech-focused startups and entrepreneurs, as well as international chains, to properly set up their business operations. Callum Wright - Founder and Lead Consultant Founder and Lead Consultant Callum Wright is a seasoned cybersecurity, privacy and AI governance expert. With over a decade of experience, he has dedicated his career to protecting digital assets, ensuring data privacy, and establishing ethical AI governance frameworks. His diverse background includes significant roles in security architecture, AI governance, risk consulting, and privacy management across various industries, thorough testing, and successful implementation, he has consistently delivered exceptional results. Throughout his career, he has taken on multifaceted roles, from leading technical project management teams to owning solutions that drive operational excellence. His conscientious and proactive approach is unwavering, whether he is working independently or collaboratively within a team. His ability to connect with colleagues on a personal level underscores his commitment to fostering a harmonious and productive workplace environment. Date: June 26, 2024 Tags: ISO/IEC 42001, Artificial Intelligence, EU AI Act, ISO/IEC 23894 ------------------------------------------------------------------------------- Find out more about ISO training and certification services Training: ISO/IEC 42001 Artificial Intelligence Management System - EN | PECB Webinars: https://pecb.com/webinars Article: https://pecb.com/article -------------------------------------------------------------------------------

 Integrated Marketing Communications (IMC)- Concept, Features, Elements, Role of advertising in IMC  Advertising: Concept, Features, Evolution of Advertising, Active Participants, Benefits of advertising to Business firms and consumers.  Classification of advertising: Geographic, Media, Target audience and Functions.

MATATAG curriculum training

Now we can take look into how to configure time off types in odoo 17 through this slide. Time-off types are used to grant or request different types of leave. Only then the authorities will have a clear view or a clear understanding of what kind of leave the employee is taking.

Configuring Single Sign-On (SSO) via Identity Management | MuleSoft Mysore Meetup #48 Event Link:- https://meetups.mulesoft.com/events/details/mulesoft-mysore-presents-configuring-single-sign-on-sso-via-identity-management/ Agenda ● Single Sign On (SSO) ● SSO Standards ● OpenID Connect vs SAML 2.0 ● OpenID Connect - Architecture ● Configuring SSO Using OIDC (Demo) ● SAML 2.0 - Architecture ● Configuring SSO Using SAML 2.0 (Demo) ● Mapping IDP Groups with Anypoint Team (Demo) ● Q & A For Upcoming Meetups Join Mysore Meetup Group - https://meetups.mulesoft.com/mysore/YouTube:- youtube.com/@mulesoftmysore Mysore WhatsApp group:- https://chat.whatsapp.com/EhqtHtCC75vCAX7gaO842N Speaker:- Vijayaraghavan Venkatadri:- https://www.linkedin.com/in/vijayaraghavan-venkatadri-b2210020/ Organizers:- Shubham Chaurasia - https://www.linkedin.com/in/shubhamchaurasia1/ Giridhar Meka - https://www.linkedin.com/in/giridharmeka Priya Shaw - https://www.linkedin.com/in/priya-shaw