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10 Fintech App Security Solutions [Complete Guide]

Design, speed, and simplicity are the winning flavors for any mobile banking app. By possessing these characteristics, the fintech app can entice any smartphone enthusiast, the number of whom is steadily increasing. The industry’s major players recognize that the pervasiveness of mobile phones in our lives must be used as a tool to win loyal users for FinTech businesses.

A new dawn for Business: CRM Marketing Automation

Imagine having a powerful tool that revolutionizes how you communicate and do business with your customers. That’s precisely what Customer Relationship Management, or CRM, offers. It’s a category of software solutions combining data-driven technology to enhance customer interactions and improve business performance.

A Developer's Guide to Continuous Performance Testing

Today’s fast-paced development environments require new approaches to testing. Enter continuous performance testing. Unlike traditional performance testing, automated continuous performance testing is part of every build, monitoring the application continuously under increased load. With continuous performance tests, organizations with lots of users can expect to improve the customer experience, prevent major outages, and find and resolve issues faster.

Leading multi-brand multi-national hotel chain

As travelers increasingly expect personalized experiences, brands in the travel and hospitality industry must find innovative ways to leverage data in their marketing and product experiences. That said, managing vast, complex data sets across multiple brands, loyalty programs and guest touchpoints presents unique challenges for companies in this industry. Enter the Composable CDP on the Snowflake AI Data Cloud for Travel and Hospitality.

Java String Methods: A Guide With Examples

Strings are important concepts in programming and are data types that allow storage of character sequences. String methods are built-in functions that are called on a string to either get information or manipulate data. In Java, strings are treated as immutable data, therefore their values cannot be changed. To work with strings and perform operations on them, you need to understand string methods in Java and how they work.

Connect with Confluent Q4 Update: New Program Entrants and SAP Datasphere Hydration

The Connect with Confluent (CwC) Technology Partner Program consistently expands the reach of Confluent’s data streaming platform across an ever-growing landscape of enterprise data systems. In this blog, you’ll meet the latest program entrants who have built fully managed integrations with Confluent and discover new ways to leverage real-time data across your business.

Load testing tools: comparison of Loadero and LoadNinja

"Load, load testing, load test this, load test that, Loadero, LoadNinja, load, load, load... ugh, what should I choose?!'' - we can only imagine what the experience of choosing a load testing tool is like. The Loadero team has decided to ease the burden of choosing between testing tools by writing a comparison review about Loadero and LoadNinja. By the way, if you’re considering testRTC as an option too, we have published a similar article before, where we compared Loadero and testRTC.

Top 3 Data and Analytics Trends to Prepare for in 2025

2025 is poised to be another year of significant advancements in business intelligence (BI) and analytics. Building on the momentum of 2024, which saw a surge in self-service BI adoption, our attention turns to newer, sophisticated artificial intelligence (AI) solutions. As the data landscape evolves, it’s important to keep agile and adapt to emerging technologies to stay competitive and maximize the value of your analytics investments.

Elevating Productivity: Cloudera Data Engineering Brings External IDE Connectivity to Apache Spark

As advanced analytics and AI continue to drive enterprise strategy, leaders are tasked with building flexible, resilient data pipelines that accelerate trusted insights. AI pioneer Andrew Ng recently underscored that robust data engineering is foundational to the success of data-centric AI—a strategy that prioritizes data quality over model complexity.