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Serhii R., Microsoft Azure DevOps & SQL Engineer

Kyiv, Ukraine
Last Updated: 29 Mar 2024

- Сertified Azure DevOps Engineer with more than 20 years of experience in software and database development (С# and VB.NET) - 5+ years of experience in managing distributed development teams. I have participated in more than 15 projects, mostly of middle and large size, and have been involved in all stages of the release cycle, including analysis, design, coding, deployment, development and testing. I am versed in supporting new applications and developing new features for existing complex applications. - Skilled in refactoring, migration, and performance optimization, as well as in extending the functionality and maintaining the existing features. - Open-minded and goal-oriented team player with strong interpersonal and communicational skills. - Can learn quickly under tough deadlines. - Constantly looking for opportunities to improve my skills and knowledge in system design and algorithms.Industries: Logistics and transportation, banking and finance, information technology and services, professional services, computer software.

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SQL

SQL

Microsoft SQL Server

Microsoft SQL Server

Microsoft Azure

Microsoft Azure

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Nata L, Data Analyst with BI and Data Engineering skills (Senior Certified Tableau Engineer)

Germany
Last Updated: 23 Apr 2024
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- Oriented Data and Business Intelligence Analysis engineer with Data Engineering skills. - 6+ years of experience with Tableau - Experience in Operations analysis, building charts & dashboards - 20+ years of experience in data mining, data analysis, and data processing. Unifying data from many sources to create interactive, immersive dashboards and reports that provide actionable insights and drive business results. - Adept with different SDLC methodologies - Waterfall, Agile SCRUM - Knowledge of performing data analysis, data modeling, data mapping, batch data processing, and capable of generating reports using reporting tools such as Power BI (advanced), Sisence(Periscope) (expert), Tableau (Advanced), Data Studio (Advanced) - Experience in writing SQL Queries, Big Query, Python, R, DAX to extract data and perform Data Analysis - AWS, Redshift - Combined expertise in data analysis with solid technical qualifications. - Advanced English, Intermediate German - Location: Germany

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SQL

SQL   8 yr.

Python

Python   6 yr.

Microsoft Power BI

Microsoft Power BI

Data Analysis Expressions (DAX)

Data Analysis Expressions (DAX)   4 yr.

Tableau

Tableau   6 yr.

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Ali R., Tableau Engineer

Pakistan
Last Updated: 23 Apr 2024
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Language Verified
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CV Verified

- 7 years of commercial experience with Tableau - 8 years of experience as a BI Consultant, providing data visualization expertise in Tableau, Power BI, Python, SQL - Created visually compelling and interactive Tableau dashboards for clients in the real estate domain in the US - Upper-Intermediate English

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SQL

SQL

Tableau

Tableau   7 yr.

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Ihor K, Big Data & Data Science Engineer with BI & DevOps skills

Ukraine
Last Updated: 5 Mar 2024
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- Data Engineer with a Ph.D. degree in Measurement methods, Master of industrial automation - 16+ years experience with data-driven projects - Strong background in statistics, machine learning, AI, and predictive modeling of big data sets. - AWS Certified Data Analytics. AWS Certified Cloud Practitioner. - Experience in ETL operations and data curation - PostgreSQL, SQL, Microsoft SQL, MySQL, Snowflake - Big Data Fundamentals via PySpark, Google Cloud, AWS. - Python, Scala, C#, C++ - Skills and knowledge to design and build analytics reports, from data preparation to visualization in BI systems.

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SQL

SQL

AWS big data services

AWS big data services

AWS Quicksight

AWS Quicksight

Python

Python

Apache Kafka

Apache Kafka

Data Pipelines (ETL)

Data Pipelines (ETL)

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Henry A., Software Engineer with Python and Data Analytical Skills

Nigeria
Last Updated: 23 Apr 2024
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- 8+ years experience working with Python; - 5 years of experience as a BI and 4 years of experience with Tableau; - 8 years of experience with various data sets (ETL, Data Engineer, Data Quality Engineer); - 3 years of experience with Amazon Web Services (AWS), Google Cloud Platform (GCP); - Data Analytics/Engineering with Cloud Service Providers (AWS, GCP) - Experience working with MySQL, SQL, and PostgreSQL; - Deep abilities working with Kubernetes (K8s); - Hands-on scripting experience with Python; Microsoft Power BI, Tableau, Sisense, CI/CD principles, Data Validation, Data QA, SQL, Pipelines, ETL, and Automated web scraping. - Pet web3 projects (solidity, wallet integration) - Upper-intermediate English

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SQL

SQL

Python

Python   8.5 yr.

Data Analysis

Data Analysis   6 yr.

Google Cloud Platform (GCP)

Google Cloud Platform (GCP)   4 yr.

Tableau

Tableau   4 yr.

Microsoft Power BI

Microsoft Power BI   4 yr.

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Upstaff.com was launched in 2019, addressing software service companies, startups and ISVs, increasingly varying and evolving needs for qualified software engineers

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FAQs about SQL Development

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If you urgently need a verified and qualified SQL developer, and resources for finding the right candidate are lacking, UPSTAFF is exactly the service you need. We approach the selection of SQL developers professionally, tailored precisely to your needs. From placing the call to the completion of your task by a qualified developer, only a few days will pass.

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Undoubtedly, there are dozens, if not hundreds, of specialized services and platforms on the network for finding the right SQL engineer. However, only UPSTAFF offers you the service of selecting real qualified professionals almost in real time. With Upstaff, software development is easier than calling a taxi.

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AI tools and expert human reviewers in the vetting process are combined with a track record and historically collected feedback from clients and teammates. On average, we save over 50 hours for client teams in interviewing SQL candidates for each job position. We are fueled by a passion for technical expertise, drawn from our deep understanding of the industry.

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Our journey starts with a 30-minute discovery call to explore your project challenges, technical needs, and team diversity. Meet Carefully Matched SQL Talents. Within 1-3 days, we’ll share profiles and connect you with the right talents for your project. Schedule a call to meet engineers in person. Validate Your Choice. Bring a new SQL developer on board with a trial period to confirm that you’ve hired the right one. There are no termination fees or hidden costs.

How does Upstaff vet remote SQL engineers? Arrow

Upstaff Managers conduct an introductory round with potential candidates to assess their soft skills. Additionally, the talent’s hard skills are evaluated through testing or verification by a qualified developer during a technical interview. The Upstaff Staffing Platform stores data on past and present SQL candidates. Upstaff managers also assess talent and facilitate rapid work and scalability, offering clients valuable insights into their talent pipeline. Additionally, we have a matching system within the platform that operates in real-time, facilitating efficient pairing of candidates with suitable positions.

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Table of Contents

Let’s consider Difference between Junior, Middle, Senior, Expert/Team Lead developer roles.

Seniority NameYears of experienceResponsibilities and activitiesAverage salary (USD/year)
Junior0-2 yearsAssisting senior developers in implementing features and fixing bugs, writing basic code snippets, performing code reviews under supervision, learning new technologies and frameworks, collaborating with team members.$50,000 – $70,000
Middle2-5 yearsDeveloping and maintaining software components, writing complex code, participating in code reviews, collaborating with cross-functional teams, providing technical guidance to junior developers, contributing to architecture and design decisions.$70,000 – $100,000
Senior5+ yearsLeading and mentoring a team of developers, designing and implementing complex software solutions, participating in architectural discussions, conducting code reviews, optimizing performance and scalability, collaborating with stakeholders, contributing to the overall technical strategy of the organization.$100,000 – $150,000
Expert/Team Lead8+ yearsLeading and managing a team of developers, overseeing project delivery, providing technical expertise and guidance, driving innovation and best practices, participating in strategic planning, fostering collaboration across teams, resolving technical challenges, ensuring high-quality code and adherence to coding standards.$150,000 – $200,000

TOP 10 SQL Related Technologies

  • SQL

    SQL (Structured Query Language) is a standard programming language used for managing and manipulating relational databases. It allows developers to create, query, and modify databases, making it a fundamental technology for SQL software development.

  • Python

    Python is a versatile and powerful programming language widely used for SQL software development. It offers libraries and frameworks like SQLAlchemy and Django that simplify database interactions and enable developers to build robust and scalable applications.

  • Java

    Java is a popular programming language for SQL software development, especially in enterprise environments. It provides frameworks like JDBC (Java Database Connectivity) that facilitate database integration and enable seamless communication with SQL databases.

  • .NET

    The .NET framework, developed by Microsoft, is widely used for SQL software development. It offers technologies like ADO.NET and Entity Framework that provide seamless integration with SQL databases and simplify data access and manipulation.

  • Node.js

    Node.js is a JavaScript runtime built on Chrome’s V8 JavaScript engine. It allows developers to build scalable and high-performance server-side applications, making it a popular choice for SQL software development. Node.js offers libraries like Sequelize that simplify database interactions.

  • React

    React is a JavaScript library for building user interfaces. While not directly related to SQL software development, React is often used in conjunction with backend technologies to create interactive and data-driven web applications that can interact with SQL databases.

  • Ruby

    Ruby is a dynamic and expressive programming language known for its simplicity and readability. It offers frameworks like Ruby on Rails that simplify SQL software development by providing an ORM (Object-Relational Mapping) layer, making database interactions more intuitive.

TOP 15 Facts about SQL

  • SQL stands for Structured Query Language. It is a programming language designed for managing and manipulating relational databases.
  • SQL was first developed by IBM in the 1970s as a part of their System R project.
  • SQL is a standard language for interacting with databases, and it is widely used across different database management systems, including Oracle, MySQL, SQL Server, and PostgreSQL.
  • SQL is a declarative language, meaning that users specify what they want the system to do, rather than how to do it.
  • SQL allows users to retrieve and manipulate data stored in databases using a set of predefined commands, such as SELECT, INSERT, UPDATE, and DELETE.
  • SQL is not case-sensitive, meaning that keywords and identifiers can be written in uppercase or lowercase without affecting the query execution.
  • SQL uses a set-based approach to data manipulation, allowing users to perform operations on multiple rows or sets of rows at once.
  • SQL supports powerful filtering and sorting capabilities, enabling users to extract specific information from a large dataset based on specified criteria.
  • SQL supports various types of joins, which allow users to combine data from multiple tables based on common columns.
  • SQL provides data integrity features, such as primary keys, foreign keys, and constraints, to ensure the accuracy and consistency of data stored in databases.
  • SQL supports the creation and modification of database schema objects, such as tables, views, indexes, and stored procedures.
  • SQL has extensive support for data aggregation and statistical functions, allowing users to perform calculations and generate summary information from large datasets.
  • SQL provides transaction control statements, such as COMMIT and ROLLBACK, to ensure the atomicity, consistency, isolation, and durability (ACID) properties of database operations.
  • SQL has evolved over the years with the introduction of new features and enhancements, such as window functions, common table expressions, and support for JSON data.
  • SQL is an essential skill for data professionals, as it enables them to efficiently work with and analyze large volumes of structured data.

How and where is SQL used?

Case NameCase Description
Data AnalysisSQL development is widely used for data analysis tasks. It allows analysts to retrieve, manipulate, and analyze large volumes of data efficiently. SQL’s powerful querying capabilities enable analysts to extract valuable insights from complex databases, perform aggregations, apply filters, and join multiple tables to gain a comprehensive understanding of the data.
Database ManagementSQL development is essential for managing databases effectively. It enables administrators to create, modify, and optimize database structures, define tables, set up indexes, establish relationships between tables, and enforce data integrity through constraints. SQL also provides mechanisms for backing up and restoring databases, ensuring the reliability and security of critical data.
Web DevelopmentSQL is commonly used in web development to create and manage dynamic websites. It allows developers to store and retrieve user data, such as login credentials, personal information, and preferences. SQL’s ability to handle concurrent access ensures efficient and secure data management in web applications.
Business IntelligenceSQL plays a crucial role in business intelligence (BI) applications. It enables the extraction, transformation, and loading (ETL) of data from various sources into data warehouses or data marts. Analysts can then use SQL to query and analyze the consolidated data, generate reports, create dashboards, and make data-driven decisions to drive business growth.
Data IntegrationSQL development is instrumental in integrating data from disparate sources. By leveraging SQL’s JOIN and UNION operations, developers can combine datasets from different databases or systems, aligning them based on common attributes. This enables organizations to consolidate and centralize their data, facilitating seamless data sharing and fostering a unified view of the business.
Data MigrationSQL is widely used for data migration projects, where organizations need to transfer data from one system or database to another. SQL’s ability to manipulate and transform data allows for seamless data transfer while ensuring data integrity and consistency. It simplifies the process of migrating data between different platforms, enabling smooth transitions and minimizing disruptions.
Data WarehousingSQL is extensively utilized in building and managing data warehouses. It enables the creation of optimized database schemas, the implementation of efficient data loading processes, and the development of complex queries for extracting valuable insights. SQL’s support for indexing, partitioning, and aggregations ensures fast and efficient data retrieval in data warehousing environments.
Report GenerationSQL is commonly used to generate reports from databases. By crafting SQL queries, analysts can extract specific data subsets, apply filters, aggregate data, and format the results according to reporting requirements. SQL’s flexibility and power enable the creation of comprehensive and customized reports that provide meaningful insights to stakeholders.
Data CleansingSQL development is crucial for data cleansing tasks, where data quality issues need to be addressed. SQL offers various functions and operations to identify and rectify inconsistencies, remove duplicates, handle missing values, and enforce data validation rules. By leveraging SQL, organizations can ensure their data is accurate, reliable, and fit for analysis and decision-making.

Soft skills of a SQL Developer

Soft skills are essential for SQL Developers to excel in their roles and collaborate effectively with others. Here are the soft skills required at different levels of expertise:

Junior

  • Communication: Ability to clearly convey information and ideas to team members and stakeholders.
  • Teamwork: Collaboration with colleagues to achieve project goals and resolve challenges.
  • Problem-solving: Analyzing issues and finding solutions to optimize SQL queries and database performance.
  • Attention to detail: Ensuring accuracy and precision in SQL coding and data analysis.
  • Time management: Efficiently organizing tasks and meeting project deadlines.

Middle

  • Leadership: Guiding and mentoring junior team members to enhance their SQL skills and knowledge.
  • Adaptability: Flexibility in adapting to changing project requirements and technologies.
  • Critical thinking: Evaluating complex problems and identifying innovative SQL solutions.
  • Conflict resolution: Resolving conflicts and promoting a positive work environment.
  • Client management: Effectively managing client expectations and delivering quality solutions.
  • Documentation: Documenting SQL processes and procedures for future reference.
  • Continuous learning: Staying updated with the latest SQL trends and technologies.

Senior

  • Strategic thinking: Aligning SQL development with business objectives and driving long-term success.
  • Project management: Overseeing SQL projects from initiation to completion, ensuring quality and timely delivery.
  • Collaboration: Building strong relationships with stakeholders and fostering cross-functional teamwork.
  • Presentation skills: Delivering clear and impactful presentations to key stakeholders.
  • Influence and persuasion: Convincing others of the value and benefits of SQL-related initiatives.
  • Empathy: Understanding and empathizing with the needs and challenges of team members.
  • Negotiation: Negotiating effectively with clients and vendors to achieve favorable outcomes.

Expert/Team Lead

  • Strategic vision: Defining the long-term SQL strategy and roadmap for the team or organization.
  • Mentorship: Coaching and guiding team members to enhance their SQL expertise and professional growth.
  • Decision-making: Making informed decisions based on data analysis and business insights.
  • Innovation: Driving innovative SQL solutions and pushing the boundaries of traditional practices.
  • Change management: Leading and managing teams through SQL-related organizational changes.
  • Relationship building: Establishing strong relationships with key stakeholders and industry experts.
  • Conflict management: Resolving conflicts and mediating disagreements within the team.
  • Business acumen: Understanding the business context and aligning SQL initiatives with organizational goals.
  • Strategic partnerships: Building strategic alliances with external partners to leverage expertise and resources.
  • Resource management: Efficiently allocating and managing SQL development resources for optimal results.
  • Continuous improvement: Identifying opportunities for process optimization and enhancing SQL development practices.

Cases when SQL does not work

  1. Large Datasets: SQL may not be ideal for handling large datasets, especially when dealing with millions or billions of records. The processing and retrieval times can be significantly slower, leading to performance issues. In such cases, alternative solutions like distributed computing frameworks or NoSQL databases may be more suitable.
  2. Unstructured Data: SQL is designed for structured data, where the schema is predefined. However, when dealing with unstructured or semi-structured data, such as documents, images, or social media feeds, SQL may not provide efficient querying capabilities. NoSQL databases, graph databases, or specialized search engines like Elasticsearch can be better options in these scenarios.
  3. Real-time Data Processing: SQL databases are primarily optimized for batch processing or handling transactions. When it comes to real-time data processing, where low latency is crucial, SQL may not be the best choice. Stream processing frameworks like Apache Kafka or Apache Flink are more suitable for continuous data ingestion and real-time analytics.
  4. Complex Data Relationships: SQL databases excel at handling simple relationships like one-to-one, one-to-many, or many-to-many. However, when dealing with highly complex data relationships, such as hierarchical or graph-like structures, SQL queries can become convoluted and difficult to manage. Graph databases like Neo4j are specifically designed to handle such scenarios efficiently.
  5. Data Manipulation and Transformation: SQL is primarily focused on querying and retrieving data from databases. When it comes to complex data manipulation and transformation tasks, such as data cleansing, aggregation, or complex calculations, SQL might not provide the necessary flexibility and expressive power. Data manipulation tools like Apache Spark or Python libraries like Pandas are better suited for such operations.
  6. Scalability and Elasticity: SQL databases often require upfront planning and provisioning of hardware resources. Scaling up and down can be challenging, especially during peak loads or sudden spikes in data volume. Cloud-based NoSQL databases or serverless computing platforms can provide better scalability and elasticity without the need for manual infrastructure management.

What are top SQL instruments and tools?

  • MySQL: MySQL is a popular open-source relational database management system that has been around since 1995. It supports various platforms and is widely used for web-based applications. MySQL is known for its scalability, reliability, and ease of use. It has a large and active community of developers and offers extensive documentation and support.
  • Oracle Database: Oracle Database is a leading enterprise-level database management system that has been in existence since 1979. It is known for its robustness, scalability, and high performance. Oracle Database offers a wide range of features and advanced functionalities, making it suitable for large-scale and mission-critical applications.
  • Microsoft SQL Server: Microsoft SQL Server is a relational database management system developed by Microsoft. It was first released in 1989 and has since become a popular choice for Windows-based applications. SQL Server offers a comprehensive set of tools and features, including data warehousing, business intelligence, and advanced analytics.
  • PostgreSQL: PostgreSQL is a powerful open-source object-relational database management system that was first released in 1996. It is known for its robustness, extensibility, and compliance with SQL standards. PostgreSQL offers a wide range of features, including support for JSON, geospatial data, and full-text search.
  • SQLite: SQLite is a lightweight and self-contained database engine that requires no server setup or configuration. It is widely used in embedded systems, mobile applications, and small-scale projects. SQLite is known for its simplicity, small footprint, and high performance. It is also the most widely deployed database engine in the world.
  • IBM Db2: IBM Db2 (formerly known as IBM DB2) is a family of relational database management systems developed by IBM. It has been in the market since 1983 and has evolved to support various platforms and environments. Db2 offers advanced data management capabilities, including support for hybrid cloud deployments, AI-powered analytics, and data virtualization.
  • Amazon Aurora: Amazon Aurora is a fully-managed relational database service offered by Amazon Web Services (AWS). It is compatible with MySQL and PostgreSQL and is designed to provide high performance, scalability, and availability. Aurora leverages AWS’ cloud infrastructure to deliver fast and reliable database performance.
  • SQLiteStudio: SQLiteStudio is a cross-platform SQLite database manager that provides a user-friendly interface for creating, editing, and managing SQLite databases. It offers a wide range of features, including SQL editor, visual query builder, data export/import, and schema comparison.
  • Navicat: Navicat is a database development and administration tool that supports various database management systems, including MySQL, PostgreSQL, Oracle, and SQL Server. It provides a graphical user interface for designing databases, executing SQL queries, and managing database objects.
  • DBeaver: DBeaver is a free and open-source universal database tool that supports a wide range of databases, including MySQL, PostgreSQL, Oracle, SQL Server, and SQLite. It provides a user-friendly interface for database administration, SQL development, and data migration.
  • SQL Server Management Studio (SSMS): SSMS is the official integrated development environment (IDE) for Microsoft SQL Server. It offers a comprehensive set of tools for database administration, query development, and performance tuning. SSMS is widely used by SQL Server developers and administrators.

Pros & cons of SQL

9 Pros of SQL

  • Efficient Data Retrieval: SQL allows for quick and efficient retrieval of data from databases, enabling faster query processing.
  • Data Integrity: SQL provides built-in mechanisms for enforcing data integrity rules, ensuring the accuracy and consistency of data stored in databases.
  • Scalability: SQL databases are highly scalable, allowing for seamless handling of growing amounts of data without compromising performance.
  • Flexibility: SQL offers a flexible data model, allowing users to define and manipulate data in a way that suits their specific needs.
  • Advanced Querying: SQL supports complex querying capabilities, enabling users to perform advanced operations on data such as filtering, joining, and aggregating.
  • Data Security: SQL provides robust security features, including user authentication, access control, and encryption, to protect sensitive data from unauthorized access.
  • Data Consistency: SQL ensures data consistency by enforcing ACID (Atomicity, Consistency, Isolation, Durability) properties, ensuring that database transactions are executed reliably.
  • Standardized Language: SQL is a standardized language used by various database management systems, making it portable and widely supported.
  • Integration: SQL enables seamless integration with other programming languages and tools, allowing for the development of comprehensive data-driven applications.

9 Cons of SQL

  • Complexity: SQL can be complex to learn and master, especially when dealing with advanced querying and database administration tasks.
  • Vendor Lock-in: Different database management systems may have variations in SQL syntax and functionality, leading to potential vendor lock-in.
  • Performance Limitations: Poorly optimized SQL queries and database designs can result in performance bottlenecks and slow query execution.
  • Relational Limitations: SQL follows a relational model, which may not be suitable for all types of data and use cases, such as unstructured or hierarchical data.
  • Scalability Challenges: While SQL databases are scalable, scaling them horizontally across multiple servers can be more complex compared to other NoSQL databases.
  • Concurrency Issues: SQL databases may face concurrency issues when multiple users try to access and modify the same data simultaneously, requiring careful transaction management.
  • Schema Modifications: Making changes to the database schema in SQL can be challenging, requiring careful planning and potentially impacting existing applications.
  • Learning Curve: Mastering SQL and understanding its nuances may require a significant investment of time and effort, especially for beginners.
  • Less Suitable for Real-time Analytics: SQL databases may not be the best choice for real-time analytics scenarios that require processing large volumes of data in near real-time.

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