Artificial intelligence (AI) apps are becoming increasingly crucial for individual customers and businesses alike. These apps bring many benefits, such as task automation, efficient analysis of large data sets, and data-informed decision-making, making AI-powered applications highly valuable. As a result, DevOps teams working on AI apps can’t afford poor performance.

Implementing a PIM or PXM* solution will bring numerous benefits to your organization, in terms of improving efficiency, increasing sales and conversions, reducing returns, and promoting customer loyalty through more accurate, more complete, and more engaging product content. Here we explore these benefits in more detail.

The quick and dirty definition of data mapping is the process of connecting different types of data from various data sources. Data mapping is essential for integration, migration, and transformation of different data sets; it allows you to improve your data quality by preventing duplications and redundancies in your data fields. Data mapping is a crucial step in data modeling and can help organizations achieve their business goals by enabling data integration, migration, transformation, and quality.

What determines the success of an API? A significant part lies in mastering the API lifecycle—from planning to retiring, every step impacts your API’s performance and adoption. The API lifecycle involves several critical stages—planning, designing, developing, deploying, consuming, monitoring, and retiring. Each stage dictates the successful implementation of APIs, including governance models, transparency, and security being crucial throughout.

With more emerging players entering the insurance market and insurance companies recognizing the importance of the digital experience, consumer demands for a connected insurance experience have grown to new heights. For insurance customers, the claims process is a critical moment of truth, making it essential that insurers deliver a hassle-free, seamless experience with faster claims processing and excellent customer service.

Streaming analytics is an invaluable capability for organizations seeking to extract real-time insights from the log data they continuously generate through applications and cloud services. To help our community get started with streaming analytics on AWS, we published a piece last year called An Overview of Streaming Analytics in AWS for Logging Applications, where we covered all the basics.

You've probably heard the expression "data is the new oil." Well, data today is fueling an increasing number of businesses. Personalized customer experiences, automated marketing messaging, and science-driven insights all depend on the quality and volume of your information. Companies are eager to gather data, and understandably so. Legislators, on the other hand, are keen to protect the privacy and safety of individuals.

Actionable marketing dashboards are a key to any marketing campaign. To get the most out of your campaign, it’s important to choose the marketing dashboard that will best fit your business goals. Read on to learn more about actionable marketing dashboards, what makes a good marketing dashboard, and discover 20 examples of marketing dashboards filled with valuable insights.

Experts predict the big data market will be worth $474 billion by 2030, proving data is incredibly valuable for businesses of all types. However, a company's ability to gather the right data, interpret it, and act on those insights will determine the success of data projects. The amount of data accessible to companies is increasing, as are the different types of data available. Business data comes in a wide variety of formats, from strictly formed relational databases to social media posts.

Jitterbit is an all-in-one integration platform that serves a variety of use cases – including API Gateway, API manager, iPaaS (Integration Platform as a Service), ETL (Extract, Transform, and Load), and more. Integrate.io is a cloud-native unified data stack that has four major components: ETL/Reverse ETL, ELT (Extract, Load, and Transform) and CDC (Change Data Capture), API Generation, Data Observability Monitoring and Alerts.