#Application integration

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Aaron Kesler, Director of AI Product Management at SnapLogic – Interview Series

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Aaron Kesler, Director of AI Product Management at SnapLogic – Interview Series

Aaron Kesler, Director of AI Product Management at SnapLogic, is a certified product leader with over a decade of experience building scalable frameworks that blend design thinking, jobs to be done, and product discovery. He focuses on developing new AI-driven products and processes while mentoring aspiring PMs through his blog and coaching on strategy, execution, and customer-centric development.

SnapLogic is an AI-powered integration platform that helps enterprises connect applications, data, and APIs quickly and efficiently. With its low-code interface and intelligent automation, SnapLogic enables faster digital transformation across data engineering, IT, and business teams.

You’ve had quite the entrepreneurial journey, starting STAK in college and going on to be acquired by Carvertise. How did those early experiences shape your product mindset?

This was a really interesting time in my life. My roommate and I started STAK because we were bored with our coursework and wanted real-world experience. We never imagined it would lead to us getting acquired by what became Delaware’s poster startup. That experience really shaped my product mindset because I naturally gravitated toward talking to businesses, asking them about their problems, and building solutions. I didn’t even know what a product manager was back then—I was just doing the job.

At Carvertise, I started doing the same thing: working with their customers to understand pain points and develop solutions—again, well before I had the PM title. As an engineer, your job is to solve problems with technology. As a product manager, your job shifts to finding the right problems—the ones that are worth solving because they also drive business value. As an entrepreneur, especially without funding, your mindset becomes: how do I solve someone’s problem in a way that helps me put food on the table? That early scrappiness and hustle taught me to always look through different lenses. Whether you’re at a self-funded startup, a VC-backed company, or a healthcare giant, Maslow’s “basic need” mentality will always be the foundation.

You talk about your passion for coaching aspiring product managers. What advice do you wish you had when you were breaking into product?

The best advice I ever got—and the advice I give to aspiring PMs—is: “If you always argue from the customer’s perspective, you’ll never lose an argument.” That line is deceptively simple but incredibly powerful. It means you need to truly understand your customer—their needs, pain points, behavior, and context—so you’re not just showing up to meetings with opinions, but with insights. Without that, everything becomes HIPPO (highest paid person’s opinion), a battle of who has more power or louder opinions. With it, you become the person people turn to for clarity.

You’ve previously stated that every employee will soon work alongside a dozen AI agents. What does this AI-augmented future look like in a day-to-day workflow?

What may be interesting is that we are already in a reality where people are working with multiple AI agents – we’ve helped our customers like DCU plan, build, test, safeguard, and put dozens of agents to help their workforce. What’s fascinating is companies are building out organization charts of AI coworkers for each employee, based on their needs. For example, employees will have their own AI agents dedicated to certain use cases—such as an agent for drafting epics/user stories, one that assists with coding or prototyping or issues pull requests, and another that analyzes customer feedback – all sanctioned and orchestrated by IT because there’s a lot on the backend determining who has access to which data, which agents need to adhere to governance guidelines, etc. I don’t believe agents will replace humans, yet. There will be a human in the loop for the foreseeable future but they will remove the repetitive, low-value tasks so people can focus on higher-level thinking. In five years, I expect most teams will rely on agents the same way we rely on Slack or Google Docs today.

How do you recommend companies bridge the AI literacy gap between technical and non-technical teams?

Start small, have a clear plan of how this fits in with your data and application integration strategy, keep it hands-on to catch any surprises, and be open to iterating from the original goals and approach. Find problems by getting curious about the mundane tasks in your business. The highest-value problems to solve are often the boring ones that the unsung heroes are solving every day. We learned a lot of these best practices firsthand as we built agents to assist our SnapLogic finance department. The most important approach is to make sure you have secure guardrails on what types of data and applications certain employees or departments have access to.

Then companies should treat it like a college course: explain key terms simply, give people a chance to try tools themselves in controlled environments, and then follow up with deeper dives. We also make it known that it is okay not to know everything. AI is evolving fast, and no one’s an expert in every area. The key is helping teams understand what’s possible and giving them the confidence to ask the right questions.

What are some effective strategies you’ve seen for AI upskilling that go beyond generic training modules?

The best approach I’ve seen is letting people get their hands on it. Training is a great start—you need to show them how AI actually helps with the work they’re already doing. From there, treat this as a sanctioned approach to shadow IT, or shadow agents, as employees are creative to find solutions that may solve super particular problems only they have. We gave our field team and non-technical teams access to AgentCreator, SnapLogic’s agentic AI technology that eliminates the complexity of enterprise AI adoption, and empowered them to try building something and to report back with questions. This exercise led to real learning experiences because it was tied to their day-to-day work.

Do you see a risk in companies adopting AI tools without proper upskilling—what are some of the most common pitfalls?

The biggest risks I’ve seen are substantial governance and/or data security violations, which can lead to costly regulatory fines and the potential of putting customers’ data at risk.  However, some of the most frequent risks I see are companies adopting AI tools without fully understanding what they are and are not capable of. AI isn’t magic. If your data is a mess or your teams don’t know how to use the tools, you’re not going to see value. Another issue is when organizations push adoption from the top down and don’t take into consideration the people actually executing the work. You can’t just roll something out and expect it to stick. You need champions to educate and guide folks, teams need a strong data strategy, time, and context to put up guardrails, and space to learn.

At SnapLogic, you’re working on new product development. How does AI factor into your product strategy today?

AI and customer feedback are at the heart of our product innovation strategy. It’s not just about adding AI features, it’s about rethinking how we can continually deliver more efficient and easy-to-use solutions for our customers that simplify how they interact with integrations and automation. We’re building products with both power users and non-technical users in mind—and AI helps bridge that gap.

How does SnapLogic’s AgentCreator tool help businesses build their own AI agents? Can you share a use case where this had a big impact?

AgentCreator is designed to help teams build real, enterprise-grade AI agents without writing a single line of code. It eliminates the need for experienced Python developers to build LLM-based applications from scratch and empowers teams across finance, HR, marketing, and IT to create AI-powered agents in just hours using natural language prompts. These agents are tightly integrated with enterprise data, so they can do more than just respond. Integrated agents automate complex workflows, reason through decisions, and act in real time, all within the business context.

AgentCreator has been a game-changer for our customers like Independent Bank, which used AgentCreator to launch voice and chat assistants to reduce the IT help desk ticket backlog and free up IT resources to focus on new GenAI initiatives. In addition, benefits administration provider Aptia used AgentCreator to automate one of its most manual and resource-intensive processes: benefits elections. What used to take hours of backend data entry now takes minutes, thanks to AI agents that streamline data translation and validation across systems.

SnapGPT allows integration via natural language. How has this democratized access for non-technical users?

SnapGPT, our integration copilot, is a great example of how GenAI is breaking down barriers in enterprise software. With it, users ranging from non-technical to technical can describe the outcome they want using simple natural language prompts—like asking to connect two systems or triggering a workflow—and the integration is built for them. SnapGPT goes beyond building integration pipelines—users can describe pipelines, create documentation, generate SQL queries and expressions, and transform data from one format to another with a simple prompt. It turns out, what was once a developer-heavy process into something accessible to employees across the business. It’s not just about saving time—it’s about shifting who gets to build. When more people across the business can contribute, you unlock faster iteration and more innovation.

What makes SnapLogic’s AI tools—like AutoSuggest and SnapGPT—different from other integration platforms on the market?

SnapLogic is the first generative integration platform that continuously unlocks the value of data across the modern enterprise at unprecedented speed and scale. With the ability to build cutting-edge GenAI applications in just hours — without writing code — along with SnapGPT, the first and most advanced GenAI-powered integration copilot, organizations can vastly accelerate business value. Other competitors’ GenAI capabilities are lacking or nonexistent. Unlike much of the competition, SnapLogic was born in the cloud and is purpose-built to manage the complexities of cloud, on-premises, and hybrid environments.

SnapLogic offers iterative development features, including automated validation and schema-on-read, which empower teams to finish projects faster. These features enable more integrators of varying skill levels to get up and running quickly, unlike competitors that mostly require highly skilled developers, which can slow down implementation significantly. SnapLogic is a highly performant platform that processes over four trillion documents monthly and can efficiently move data to data lakes and warehouses, while some competitors lack support for real-time integration and cannot support hybrid environments.

 What excites you most about the future of product management in an AI-driven world?

What excites me most about the future of product management is the rise of one of the latest buzzwords to grace the AI space “vibe coding”—the ability to build working prototypes using natural language. I envision a world where everyone in the product trio—design, product management, and engineering—is hands-on with tools that translate ideas into real, functional solutions in real time. Instead of relying solely on engineers and designers to bring ideas to life, everyone will be able to create and iterate quickly.

Imagine being on a customer call and, in the moment, prototyping a live solution using their actual data. Instead of just listening to their proposed solutions, we could co-create with them and uncover better ways to solve their problems. This shift will make the product development process dramatically more collaborative, creative, and aligned. And that excites me because my favorite part of the job is building alongside others to solve meaningful problems.

Thank you for the great interview, readers who wish to learn more should visit SnapLogic. 

[lisakeller22]

How App Integration Improves Business Performance?

App integration helps businesses automate tasks, unify data, and boost collaboration. Read the blog to know how it can power up your digital transformation.

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Mastering SwaggerHub Integrations for Seamless API Collaboration

Efficient API management requires tools that integrate design, testing, and documentation seamlessly. SwaggerHub is a central hub for collaborative API development, offering robust integrations with popular tools and platforms. These integrations extend its capabilities, enabling streamlined workflows and improving productivity across the API lifecycle.

This blog delves into the various integrations offered by SwaggerHub and how they enhance API design, development, testing, and deployment.

Understanding SwaggerHub’s Role in API Development

SwaggerHub simplifies the API lifecycle by providing a centralized platform for designing, documenting, and collaborating on APIs. With its support for Open-API specifications, teams can work together to ensure consistency, quality, and compliance.

However, the true strength of SwaggerHub lies in its integrations, which allow it to connect with external tools, enabling automation and efficient workflow management. These integrations cater to developers, testers, and DevOps teams, ensuring a unified experience.

Key SwaggerHub Integrations to Elevate API Workflows

Integrations are the backbone of modern API ecosystems, connecting diverse tools to create seamless workflows. SwaggerHub’s suite of integrations amplifies productivity by automating processes, fostering collaboration, and simplifying deployment. Here’s how these integrations enhance every stage of the API lifecycle.

Source Control and Versioning with Git Integrations

SwaggerHub integrates seamlessly with Git platforms like GitHub, GitLab, and Bit-bucket. This integration enables teams to manage API definitions directly within their source control systems.

The benefits of integrating SwaggerHub with Git platforms include:

Automate version control for API specifications.

Enable collaboration by syncing API changes across teams.

Ensure traceability with commit histories.

For instance, pushing API updates from SwaggerHub to a Git repository ensures all team members work on the latest version, minimizing conflicts and redundancy.

CI/CD Automation with Jenkins and Azure DevOps

Continuous integration and delivery pipelines are crucial for deploying APIs efficiently. SwaggerHub’s integrations with Jenkins and Azure DevOps allow organizations to automate API validation and deployment.

Use cases for integrating SwaggerHub with Jenkins and Azure DevOps include:

Validate Open-API definitions as part of the CI pipeline.

Deploy API gateways after successful validations.

Generate client SDKs and server stubs during builds.

Automating these tasks eliminates manual errors and accelerates the delivery process.

API Gateway Integrations for Simplified Deployment

SwaggerHub supports direct integration with popular API gateways like AWS API Gateway, Azure API Management, and Apigee. These integrations enable teams to publish APIs to their preferred gateway platforms effortlessly.

Below are the advantages of API Gateway Integrations:

Simplify API deployment to cloud-native environments.

Maintain consistent API documentation across platforms.

Reduce setup time for production readiness.

Publishing APIs from SwaggerHub to a gateway ensures consistent deployment and better scalability.

Collaboration with Project Management Tools

SwaggerHub integrates with tools like Jira and Confluence, bridging the gap between API developers and project managers. This integration ensures API documentation and development tasks are accessible within project management workflows.

Key Features of SwaggerHub’s integration with Jira and Confluence include:

Automatically link API updates to Jira issues.

Embed API definitions in Confluence pages for visibility.

Enhance communication between technical and non-technical teams.

These integrations foster transparency and help align development goals with business objectives.

Testing and Quality Assurance with Postman

SwaggerHub’s Postman integration transforms API testing by allowing developers to export API definitions directly into Postman collections. This process simplifies test case generation and execution.

Why it matters:

Automate test case creation for APIs.

Validate API performance using predefined collections.

Reduce the learning curve for testers unfamiliar with Open-API.

Efficient API testing ensures the reliability and robustness of API endpoints before deployment.

Code Generation and SDK Integration

Generating SDKs and server stubs directly from SwaggerHub speeds up application development. Integrations with tools like Swagger Code-gen enable developers to produce code in various programming languages.

The supported Languages for code and SDK generation are mentioned below:

Java, Python, Ruby, JavaScript, and more.

Client-side SDKs and server-side frameworks.

These integrations save development time by providing ready-to-use code templates.

Optimizing API Lifecycle with SwaggerHub Integrations

Integrating SwaggerHub with external platforms transforms it into a versatile API lifecycle management tool. Here’s how organizations can leverage these integrations:

Centralized Collaboration: SwaggerHub’s ability to link with multiple platforms ensures that all stakeholders—developers, testers, and project managers—can collaborate effectively.

Enhanced API Quality: By connecting SwaggerHub to testing tools, teams can ensure their APIs meet performance and reliability benchmarks.

Reduced Time-to-Market: Automation through CI/CD tools and code generators streamlines workflows, enabling faster delivery of high-quality APIs.

Scalability: API gateway integrations simplify the deployment process, making it easier to scale applications as demand grows.

Best Practices for SwaggerHub Integrations

Maximizing the potential of SwaggerHub integrations requires a strategic approach. By implementing thoughtful workflows, staying updated, and leveraging automation, teams can unlock greater efficiency and collaboration. These practices ensure consistent, scalable API development.

Define Clear Workflows: Establish workflows that utilize SwaggerHub integrations effectively. For instance, API changes can be synced to Git repositories, or APIs can be validated in CI pipelines.

Monitor and Update Integrations: Ensure all integrated tools are updated to their latest versions to avoid compatibility issues.

Train Teams on Integrations: Provide adequate training to developers and testers to use SwaggerHub integrations optimally.

Leverage Automation: Automate repetitive tasks like API testing and code generation to save time and minimize errors.

Conclusion

SwaggerHub integrations serve as a cornerstone for efficient API lifecycle management, offering teams the flexibility to connect with diverse tools for enhanced collaboration, automation, and scalability. By integrating with source control systems, CI/CD tools, testing platforms, API gateways, and project management tools, SwaggerHub transforms API workflows into streamlined, collaborative processes.

Organizations that leverage these integrations can improve their API quality, reduce time-to-market, and foster better stakeholder communication. Adopting best practices such as defining workflows, updating tools, and utilizing automation further maximizes these benefits.

Incorporating SwaggerHub into an API strategy ensures operational efficiency and a robust foundation for future scalability. With its diverse integrations, SwaggerHub paves the way for delivering APIs that meet high reliability, performance, and alignment with business goals.

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Oracle Integration Cloud Training - Simplify Integration

Enhance your skills with IQ Stream Tech's Oracle Integration Cloud training. Learn to seamlessly integrate applications, automate processes, and connect enterprise systems. This hands-on course provides in-depth knowledge of integration techniques, best practices, and tools to streamline operations and boost efficiency. Perfect for IT professionals aiming to master Oracle Integration Cloud solutions.

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Cloud integration is essential for businesses looking to enhance operational efficiency and scalability. By integrating cloud and on-premises systems through APIs and iPaaS, organizations can ensure data consistency, automate processes, and streamline workflows, enabling a more seamless operation.

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Discover how Prolifics excels in integrating and applying cutting-edge technologies to optimize business processes. Explore their expertise in seamlessly connecting diverse systems and applications, enhancing operational efficiency, and driving innovation across industries.

[techspianblog]

Understanding Application Integration: Mechanisms and Operations

In today’s rapidly evolving and interconnected business landscape, companies heavily depend on a multitude of applications to optimize operations, boost productivity, and fuel growth. As organizations embrace a diverse array of applications, ensuring seamless communication and interaction between them becomes essential. This is where application integration takes center stage.

Application integration facilitates the efficient collaboration of different software applications, systems, and services, offering businesses a comprehensive and unified perspective on their data and processes. This integration eliminates data silos, streamlines workflows, and enhances decision-making.

This article delves into a thorough exploration of application integration, covering its significance, components, as well as various techniques and patterns. While providing a comprehensive overview of application integration, special emphasis will be given to mobile applications, given their indispensable role in modern businesses. Continue reading to explore the realm of application integration and its profound impact on mobile apps.

What is Application Integration?

Application integration is the intricate process of enabling disparate software applications, systems, or services to communicate and collaborate, resulting in a unified and synchronized system. This process facilitates the smooth exchange of data and functionality between diverse applications, empowering businesses to streamline processes, eradicate data silos, and enhance overall efficiency.

By establishing connections between disparate systems and ensuring a consistent flow of data, application integration empowers organizations to attain a comprehensive view of their operations. This, in turn, contributes to improved decision-making and heightened productivity.

In the contemporary business environment, organizations leverage a diverse array of applications to oversee various facets of their operations, including customer relationship management (CRM), enterprise resource planning (ERP), human resource management (HRM), and more. Due to the distinct origins and data structures of these applications, they cannot inherently communicate with each other. Application integration serves as the bridge, ensuring that these systems can harmonize and share information seamlessly without the need for manual intervention.

As businesses continually embrace new applications and technologies, the necessity for robust application integration strategies becomes increasingly pronounced. In the context of the modern business landscape, characterized by the growing significance of mobile applications, integration solutions must also address the unique requirements of mobile apps. This includes aspects such as real-time data access, support for multiple platforms, and scalability.

Objectives and Advantages of Application Integration

The fundamental goals of application integration encompass the streamlining of business processes, enhancement of data sharing and collaboration, improvement of decision-making, cost reduction, and increased efficiency. A detailed exploration of each objective reveals the associated benefits.

Streamlining Business Processes:

Integration of diverse applications allows businesses to automate workflows, eliminating redundant and manual tasks. This not only saves time significantly but also minimizes the risk of errors, enabling employees to concentrate on more critical business tasks.

Application integration optimizes processes by automating activities such as data entry, scheduling, and reporting, resulting in heightened efficiency and productivity.

Enhancing Data Sharing and Collaboration:

Application integration addresses the imperative need for accurate and timely information in today’s data-driven landscape. By ensuring data consistency across all systems and eliminating data silos, integration facilitates easier access to and sharing of information.

Improved collaboration is achieved through a unified view of data and processes, fostering cross-functional communication, transparency, and collaboration between departments. This equips organizations to navigate swiftly through fast-changing environments.

Improving Decision-making:

Application integration plays a pivotal role in improving decision-making by providing a comprehensive and unified view of data and processes. Integrating various applications enables businesses to gain insights into their operations and make informed, data-driven decisions.

Consolidation of data from multiple sources into a single dashboard enables organizations to identify trends, patterns, and opportunities more effectively, enhancing their decision-making capabilities through the utilization of artificial intelligence and machine learning.

Reducing Costs and Increasing Efficiency:

Automation of workflows and elimination of manual tasks through application integration contribute to significant time and cost savings, allowing businesses to prioritize critical tasks.

Integration mitigates data duplication and inconsistencies, leading to improved data accuracy and reduced operational costs.

A flexible and scalable infrastructure provided by integration assists businesses in scaling their operations efficiently, thereby reducing IT costs and ensuring quick adaptation to changing business needs.

Types of Application Integration

Application integration can generally be categorized into three main types: data integration, process integration, and presentation integration.

Each integration type serves a distinct purpose, offering specific benefits to businesses. By selecting the appropriate integration strategy, organizations can optimize processes, foster collaboration, and enhance decision-making.

Let’s delve into each type of application integration in greater detail below.

Data Integration

Data integration is the process of combining data from diverse sources into a unified view, facilitating easier access and analysis. This type of integration is crucial for businesses utilizing different applications, such as CRM, ERP, and HRM systems, to manage data.

Various techniques, including Extract, Transform, and Load (ETL), data replication, and data virtualization, can achieve data integration. ETL entails extracting data from diverse sources, transforming it into a unified format, and loading it into a target system.

Data replication copies data from one system to another, while data virtualization creates a virtual layer, allowing users to access data from multiple sources as if it were a single database. A unified view of data enables businesses to gain insights into their operations, identify trends, and make informed decisions.

Process Integration

Process integration connects different applications to automate business processes, a critical need for businesses managing diverse operational facets. Techniques such as Application Programming Interfaces (APIs), Service-Oriented Architecture (SOA), and Business Process Management (BPM) can achieve process integration.

APIs enable communication between applications, while SOA provides a framework for creating services usable across different applications. BPM involves modeling, automating, and optimizing business processes.

Process automation leads to improved productivity, reduced errors, and enhanced scalability. By automating business processes, organizations reduce manual tasks, improve efficiency, and respond swiftly to market changes.

Presentation Integration

Presentation integration merges various user interfaces into a unified user experience, aiding businesses using applications with different interfaces. Techniques such as web portals, Single Sign-On (SSO), and web services achieve presentation integration.

Web portals offer a unified interface for accessing multiple applications, while SSO allows users to access various applications with a single set of credentials. Web services enable different applications to share data and functionality through a standard interface.

By providing a unified interface, businesses simplify the use of multiple applications, enabling users to concentrate on their tasks. Presentation integration enhances the user experience, lowers training costs, and boosts productivity.

Components of Application Integration

To achieve integration goals effectively, various components are employed. Let’s delve into the key components of application integration in greater detail below.

Application Programming Interfaces (APIs)

APIs encompass a set of protocols, routines, and tools for constructing software applications. They facilitate communication and interaction among different applications, allowing businesses to integrate multiple systems seamlessly. APIs establish a standard interface for accessing data and functionality across applications, simplifying data sharing and workflow automation.

Businesses leverage APIs to connect diverse applications, such as CRM, ERP, and HRM systems, fostering a unified operational view. Overall, APIs play a crucial role in application integration by offering a secure and scalable means of linking diverse systems.

Connectors and Adaptors

Connectors and adaptors are software components that facilitate communication between different applications. Connectors provide a framework for integrating diverse applications, while adaptors enable connectivity to various data sources. These components offer standardized methods for connecting different systems.

Connectors establish a framework for integrating applications, streamlining data sharing and workflow automation. Adaptors empower applications to link to diverse data sources, ensuring accessibility and sharing of data across systems.

Data Transformation Tools

Data transformation tools are software components that enable businesses to convert data from one format to another. They ensure seamless data sharing between applications, even if they employ different data formats.

Organizations rely on data transformation tools to standardize data formats, promoting consistency across diverse systems. By transforming data between formats, businesses can seamlessly share data and automate workflows, reducing manual tasks and enhancing efficiency.

Integration Middleware

Integration middleware software serves as a platform for integrating diverse applications, systems, and services. It introduces a layer between applications, facilitating communication and interaction.

Integration middleware establishes a framework for connecting applications, ensuring shared data and automated processes. This centralized platform manages various integration components, including APIs, connectors, adaptors, and data transformation tools.

Utilizing integration middleware, businesses can establish a unified and coordinated system, leading to improved decision-making, enhanced productivity, and cost reduction.

Application Integration Techniques and Patterns

Various techniques and patterns are employed for application integration, each offering a distinct approach to connecting diverse applications and systems.

Some widely utilized techniques and patterns include point-to-point integration, hub-and-spoke integration, federated integration, service-oriented architecture (SOA), and event-driven architecture.

Point-to-Point Integration:

This technique directly links two applications by developing custom interfaces between them, facilitating communication and data sharing. While effective for integrating pairs of applications, it can become intricate and challenging to maintain as the number of applications increases.

Hub-and-Spoke Integration:

Involving the connection of multiple applications to a central hub or middleware, the hub-and-spoke technique employs connectors and adaptors. This scalable and highly flexible approach enables applications to communicate and share data, allowing businesses to effortlessly add or remove applications as needed.

Federated Integration:

Federated integration connects multiple applications without a central hub or middleware, utilizing APIs to enable data and functionality sharing. This technique is prevalent among businesses with a substantial number of applications that require connection and management.

Service-Oriented Architecture (SOA):

SOA is an architectural pattern that creates reusable services for deployment across different applications. This involves breaking down applications into modular services and facilitating the reuse of functionality across diverse applications.

Event-Driven Architecture:

Event-driven architecture sends and receives events between different applications, leveraging message brokers for real-time communication. Ideal for businesses requiring immediate data access and processing, this approach enables applications to share information in real-time.

The selection of application integration techniques and patterns is pivotal in enabling businesses to connect various applications and systems. By employing the appropriate integration method, organizations can establish a unified and coordinated system efficiently.

Conclusion-

Application integration plays a critical role in today’s interconnected world, empowering businesses to streamline processes, foster collaboration, enhance decision-making, and minimize costs. Through the adoption of a resilient integration strategy, businesses can harness the advantages of integration to stay competitive and flourish in the dynamic landscape of contemporary business.

Read More-https://www.techspian.com/mobile-app-development/understanding-application-integration-mechanisms-and-operations/

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Discover the power of application integration with Quickwork. Seamlessly connect and automate your favorite apps to enhance productivity and streamline workflows. Experience efficiency like never before. More at https://bit.ly/3PHKKGY

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Integrating Custom Retail Software with Other Existing Legacy Systems

Business organizations rely on technology to manage several operations efficiently in today's fast-paced retail industry. Custom retail software has become popular to meet all retailers' unique needs and challenges.

The software helps manage inventories, analyze data, streamline operations, and automate processes, enabling retailers to stay competitive and deliver an enhanced customer experience.

However, most retailers have existing legacy systems, such as Customer Relationship Management (CRM), Enterprise Resource Planning (ERP), and other systems crucial for their respective operations. These legacy systems consist of valuable data and business processes.

This article will discuss why retailers must integrate custom retail software with these legal systems to leverage the technological potential and achieve seamless operations.

Legacy Systems: Understanding the Basics

Legacy systems refer to outdated software/applications that many organizations still use in the present context. These systems were developed using older technology and can become difficult to maintain while posing risks to the business over time. However, they may also perform some critical functions necessary for organizational operations.

Some of the common legacy systems are:

ERP systems that manage supply chain, inventory, and financials

CRM systems that handle customer data and interaction

Systems for point of sale (POS), payroll, human resources, etc.

Here is a breakdown of the challenges with integrating legacy systems.

●      Compatibility

Custom retail software may not be compatible with traditional legacy systems, which may have limited integration capabilities or use outdated technology.

●      Data Inconsistency

Legacy systems may have inconsistent or duplicate data. So, the process may complicate data integration and synchronization functionalities.

●      Integration Complexity

Legacy systems may have complex integration requirements such as multiple formats, data sources, and integration points. So, it can be challenging to integrate with custom retail software.

●      Business Process Misalignment

Legacy systems may have different workflows and business processes than custom retail software. It may result in misalignment and duplication of efforts.

Integration Techniques

Organizations can integrate custom retail software with legal systems through various techniques depending on specific requirements. Here is a breakdown of a few of the most common integration techniques.

●      Data Integration

The process involves exchanging data between systems to ensure accuracy. It involves several methods, such as real-time data exchange, batch processing, and synchronization.

●      Application Integration

It involves integrating the functionality of different applications to create a unified system. The process happens through APIs (Application Programming Interfaces) and other web services.

●      Process Integration

This process involves integrating different systems' business processes and workflows to ensure smooth operations. It happens through workflow automation, process mapping, and process orchestration.

●      Middleware Integration

It involves using middleware, a layer of software that acts as a bridge between different systems. Middleware can help with data transformation, data routing, and protocol conversion.

Benefits of Integration

As mentioned below, organizations can benefit from integrating custom retail software with legal systems.

●      Streamlined Business Processes

Integration can streamline business processes by eliminating manual data entry, automating workflows, and reducing errors. The process can help retailers achieve operational efficiency and keep customers satisfied.

●      Improved Data Accuracy and Consistency

Integration ensures that data is updated regularly and synchronized across different systems. The process helps reduce data inconsistencies and duplications.

●      Enhanced Customer Experience

Integrated systems allow retailers to access and analyze customer data from different sources in real-time. It enables personalized and relevant interactions with customers.

●      Increased Efficiency and Productivity

Integration automates manual processes, reduces data entry errors, and eliminates redundant tasks, increasing efficiency and productivity. It allows retailers to save time and resources.

●      Reduced Operational Costs

Integration can streamline operations, eliminate redundant tasks, and optimize workflows, saving costs.

Best Practices for Successful Integration

Retailers must be careful when ensuring integrations between custom retail software and legacy systems. The lack of integration may cause system failures, delayed developments, and increased costs. So, here are some best practices for successful integration that retailers can follow to avoid negative consequences.

●      Set Goals and Objectives

Defining the goals and objectives of integration projects, such as enhancing customer experience, achieving cost savings, and improving operational efficiency, is important to align the plan with the overall business strategies of an organization.

●      Establish a Comprehensive Plan

Retailers must devise a plan that involves the scope, timeline, and resources required for the integration project. It will help them, including the key stakeholders, identify potential risks and challenges and develop contingency plans to mitigate them.

●      Security and Data Privacy

Retailers can try implementing encryption, authentication, and authorization mechanisms to protect sensitive data. They must comply with industry regulations and standards, such as PCI-DSS, GDPR, and HIPAA to ensure data security and privacy.

●      Select the Right Integration Approach

Retailers must select the correct integration approach based on the organization's specific requirements and the related legacy systems. They can consider factors such as data volume, complexity, and real-time requirements to select the framework that suits them the best.

●      Testing and Validation

Retailers must test the integration thoroughly to ensure it works as expected and does not cause any disruptions to the existing systems. They must also validate the data accuracy and consistency across different systems.

●      Train Employees on the New System

Provide comprehensive training to employees who will be using the integrated system. Train them on how to use the system effectively, understand the new processes and workflows, and leverage the integrated data and functionality to their advantage. Provide ongoing support to address any questions or issues arising after the integration.

Case Studies

Here are some examples of successful integration projects in the retail industry:

●      Multimedia Lifestyle Company is a renowned fashion retailer that has integrated its custom retail software with its legacy ERP system to streamline its inventory management and supply chain operations. The integration allowed them to automate updating inventory levels, tracking orders, and managing stock replenishment. The process improved inventory accuracy, reduced stockouts, and increased customer satisfaction.

●      A confidential client is a consumer electronics retailer that integrated its custom retail software with its legacy CRM system to enhance customer experience. The integration enabled them to consolidate customer data from various touchpoints, such as online and offline channels, into a single view. The process further allowed them to provide personalized recommendations, targeted promotions, and seamless customer service. It resulted in positive customer loyalty and repeat purchases.

Conclusion

You must integrate custom retail software with legacy systems like CRM and ERP to achieve operational efficiency, improve customer experience, and drive business growth. The process allows retailers to streamline business processes, improve data accuracy, reduce operational costs, and increase productivity and efficiency.

So, retailers can ensure efficient integration of custom retail software with legacy systems by following the best practices and establishing a comprehensive plan for further growth.

[jcmarchi]

Aaron Kesler, Sr. Product Manager, AI/ML at SnapLogic – Interview Series

New Post has been published on https://thedigitalinsider.com/aaron-kesler-sr-product-manager-ai-ml-at-snaplogic-interview-series/

Aaron Kesler, Sr. Product Manager, AI/ML at SnapLogic – Interview Series

Aaron Kesler, Sr. Product Manager, AI/ML at SnapLogic, is a certified product leader with over a decade of experience building scalable frameworks that blend design thinking, jobs to be done, and product discovery. He focuses on developing new AI-driven products and processes while mentoring aspiring PMs through his blog and coaching on strategy, execution, and customer-centric development.

SnapLogic is an AI-powered integration platform that helps enterprises connect applications, data, and APIs quickly and efficiently. With its low-code interface and intelligent automation, SnapLogic enables faster digital transformation across data engineering, IT, and business teams.

You’ve had quite the entrepreneurial journey, starting STAK in college and going on to be acquired by Carvertise. How did those early experiences shape your product mindset?

This was a really interesting time in my life. My roommate and I started STAK because we were bored with our coursework and wanted real-world experience. We never imagined it would lead to us getting acquired by what became Delaware’s poster startup. That experience really shaped my product mindset because I naturally gravitated toward talking to businesses, asking them about their problems, and building solutions. I didn’t even know what a product manager was back then—I was just doing the job.

At Carvertise, I started doing the same thing: working with their customers to understand pain points and develop solutions—again, well before I had the PM title. As an engineer, your job is to solve problems with technology. As a product manager, your job shifts to finding the right problems—the ones that are worth solving because they also drive business value. As an entrepreneur, especially without funding, your mindset becomes: how do I solve someone’s problem in a way that helps me put food on the table? That early scrappiness and hustle taught me to always look through different lenses. Whether you’re at a self-funded startup, a VC-backed company, or a healthcare giant, Maslow’s “basic need” mentality will always be the foundation.

You talk about your passion for coaching aspiring product managers. What advice do you wish you had when you were breaking into product?

The best advice I ever got—and the advice I give to aspiring PMs—is: “If you always argue from the customer’s perspective, you’ll never lose an argument.” That line is deceptively simple but incredibly powerful. It means you need to truly understand your customer—their needs, pain points, behavior, and context—so you’re not just showing up to meetings with opinions, but with insights. Without that, everything becomes HIPPO (highest paid person’s opinion), a battle of who has more power or louder opinions. With it, you become the person people turn to for clarity.

You’ve previously stated that every employee will soon work alongside a dozen AI agents. What does this AI-augmented future look like in a day-to-day workflow?

What may be interesting is that we are already in a reality where people are working with multiple AI agents – we’ve helped our customers like DCU plan, build, test, safeguard, and put dozens of agents to help their workforce. What’s fascinating is companies are building out organization charts of AI coworkers for each employee, based on their needs. For example, employees will have their own AI agents dedicated to certain use cases—such as an agent for drafting epics/user stories, one that assists with coding or prototyping or issues pull requests, and another that analyzes customer feedback – all sanctioned and orchestrated by IT because there’s a lot on the backend determining who has access to which data, which agents need to adhere to governance guidelines, etc. I don’t believe agents will replace humans, yet. There will be a human in the loop for the foreseeable future but they will remove the repetitive, low-value tasks so people can focus on higher-level thinking. In five years, I expect most teams will rely on agents the same way we rely on Slack or Google Docs today.

How do you recommend companies bridge the AI literacy gap between technical and non-technical teams?

Start small, have a clear plan of how this fits in with your data and application integration strategy, keep it hands-on to catch any surprises, and be open to iterating from the original goals and approach. Find problems by getting curious about the mundane tasks in your business. The highest-value problems to solve are often the boring ones that the unsung heroes are solving every day. We learned a lot of these best practices firsthand as we built agents to assist our SnapLogic finance department. The most important approach is to make sure you have secure guardrails on what types of data and applications certain employees or departments have access to.

Then companies should treat it like a college course: explain key terms simply, give people a chance to try tools themselves in controlled environments, and then follow up with deeper dives. We also make it known that it is okay not to know everything. AI is evolving fast, and no one’s an expert in every area. The key is helping teams understand what’s possible and giving them the confidence to ask the right questions.

What are some effective strategies you’ve seen for AI upskilling that go beyond generic training modules?

The best approach I’ve seen is letting people get their hands on it. Training is a great start—you need to show them how AI actually helps with the work they’re already doing. From there, treat this as a sanctioned approach to shadow IT, or shadow agents, as employees are creative to find solutions that may solve super particular problems only they have. We gave our field team and non-technical teams access to AgentCreator, SnapLogic’s agentic AI technology that eliminates the complexity of enterprise AI adoption, and empowered them to try building something and to report back with questions. This exercise led to real learning experiences because it was tied to their day-to-day work.

Do you see a risk in companies adopting AI tools without proper upskilling—what are some of the most common pitfalls?

The biggest risks I’ve seen are substantial governance and/or data security violations, which can lead to costly regulatory fines and the potential of putting customers’ data at risk.  However, some of the most frequent risks I see are companies adopting AI tools without fully understanding what they are and are not capable of. AI isn’t magic. If your data is a mess or your teams don’t know how to use the tools, you’re not going to see value. Another issue is when organizations push adoption from the top down and don’t take into consideration the people actually executing the work. You can’t just roll something out and expect it to stick. You need champions to educate and guide folks, teams need a strong data strategy, time, and context to put up guardrails, and space to learn.

At SnapLogic, you’re working on new product development. How does AI factor into your product strategy today?

AI and customer feedback are at the heart of our product innovation strategy. It’s not just about adding AI features, it’s about rethinking how we can continually deliver more efficient and easy-to-use solutions for our customers that simplify how they interact with integrations and automation. We’re building products with both power users and non-technical users in mind—and AI helps bridge that gap.

How does SnapLogic’s AgentCreator tool help businesses build their own AI agents? Can you share a use case where this had a big impact?

AgentCreator is designed to help teams build real, enterprise-grade AI agents without writing a single line of code. It eliminates the need for experienced Python developers to build LLM-based applications from scratch and empowers teams across finance, HR, marketing, and IT to create AI-powered agents in just hours using natural language prompts. These agents are tightly integrated with enterprise data, so they can do more than just respond. Integrated agents automate complex workflows, reason through decisions, and act in real time, all within the business context.

AgentCreator has been a game-changer for our customers like Independent Bank, which used AgentCreator to launch voice and chat assistants to reduce the IT help desk ticket backlog and free up IT resources to focus on new GenAI initiatives. In addition, benefits administration provider Aptia used AgentCreator to automate one of its most manual and resource-intensive processes: benefits elections. What used to take hours of backend data entry now takes minutes, thanks to AI agents that streamline data translation and validation across systems.

SnapGPT allows integration via natural language. How has this democratized access for non-technical users?

SnapGPT, our integration copilot, is a great example of how GenAI is breaking down barriers in enterprise software. With it, users ranging from non-technical to technical can describe the outcome they want using simple natural language prompts—like asking to connect two systems or triggering a workflow—and the integration is built for them. SnapGPT goes beyond building integration pipelines—users can describe pipelines, create documentation, generate SQL queries and expressions, and transform data from one format to another with a simple prompt. It turns out, what was once a developer-heavy process into something accessible to employees across the business. It’s not just about saving time—it’s about shifting who gets to build. When more people across the business can contribute, you unlock faster iteration and more innovation.

What makes SnapLogic’s AI tools—like AutoSuggest and SnapGPT—different from other integration platforms on the market?

SnapLogic is the first generative integration platform that continuously unlocks the value of data across the modern enterprise at unprecedented speed and scale. With the ability to build cutting-edge GenAI applications in just hours — without writing code — along with SnapGPT, the first and most advanced GenAI-powered integration copilot, organizations can vastly accelerate business value. Other competitors’ GenAI capabilities are lacking or nonexistent. Unlike much of the competition, SnapLogic was born in the cloud and is purpose-built to manage the complexities of cloud, on-premises, and hybrid environments.

SnapLogic offers iterative development features, including automated validation and schema-on-read, which empower teams to finish projects faster. These features enable more integrators of varying skill levels to get up and running quickly, unlike competitors that mostly require highly skilled developers, which can slow down implementation significantly. SnapLogic is a highly performant platform that processes over four trillion documents monthly and can efficiently move data to data lakes and warehouses, while some competitors lack support for real-time integration and cannot support hybrid environments.

 What excites you most about the future of product management in an AI-driven world?

What excites me most about the future of product management is the rise of one of the latest buzzwords to grace the AI space “vibe coding”—the ability to build working prototypes using natural language. I envision a world where everyone in the product trio—design, product management, and engineering—is hands-on with tools that translate ideas into real, functional solutions in real time. Instead of relying solely on engineers and designers to bring ideas to life, everyone will be able to create and iterate quickly.

Imagine being on a customer call and, in the moment, prototyping a live solution using their actual data. Instead of just listening to their proposed solutions, we could co-create with them and uncover better ways to solve their problems. This shift will make the product development process dramatically more collaborative, creative, and aligned. And that excites me because my favorite part of the job is building alongside others to solve meaningful problems.

Thank you for the great interview, readers who wish to learn more should visit SnapLogic. 

[kibibarel]

i need to complain and you're the only N liker i trust... whys every N rper have such a boring interpretation of him.... like at LEAST make him obsessed with math 😭😭😭

N is a fan favorite, which means you get way more people than usual attempting to write him, which means he tends to get subjected to more fanon...that's my theory

because he's a fan favorite, i think he's also the type of character that people like to pick up and project themselves onto, even if it means removing a lot of the nuance in his canon character. back when i was still RPing him on tumblr myself (which, granted, was almost a decade ago now...geez) it was also very in vogue to put him through so many layers of AU that he was basically just an OC lmao...tumblr Gladions are also like this in my experience. so many wildly out-of-character boys out there

anyway my advice to N writers is you don't even really need to know math to write N's math stuff true to canon...just have him throw out the word "formula" or "theorem" every now and then. that's what i did LMAO......this math shit is easy

[lisakeller22]

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We offer application integration services that connect your apps and systems, enabling seamless communication and improving overall business efficiency.

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How to Choose The Right HubSpot Partner? - A compressive Guide

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[aeide-thea]

truly just SUCH a typical tumblr experience but like.

Familiar Tumblr Name makes a post that's like: 'you know how fast fashion perpetuates itself by selling us clothing that gets dingy and grody really fast, so we have to replace it yearly?'

me: uh, no, actually—historically i've found that the few fast fashion pieces i acquired long outstayed their welcome, and were perfectly wearable long after i was heartily sick of them! but go on, i guess

FTN: 'let me tell you about this traditional domestic wisdom (implied: that's been lost because of, uh, capitalism) that will fix this problem (that you, too, definitely have) for you!'

me, googling: okay so this residue that FTN said was somehow a Fast Fashion thing is apparently generally caused by like. fabric softener and/or hard water. using discount detergents that skimp on active ingredients. using too much detergent so it doesn't wash out. letting your bedding go too long between washes. letting your washer go too long between cleans. etc. anyway. lots of specific factors here, many of which may in fact not apply to you in particular!

but like. why get specific when instead we could assert You Know This Problem, Right? This Lost Traditional Wisdom Will Definitely Help You Personally!!