Systems | Development | Analytics | API | Testing

Businesses handle massive amounts of data daily. To make informed decisions, this data must be optimized for accuracy and consistency, which requires effective data management. However, for best results, data management must be coupled with data governance, which provides essential frameworks to manage data quality and security. Data stewardship takes it a step further.

Cloud operations were once the logical next step for streamlining business processes, but now they have become the go-to solution for maximizing operational efficiency. With the advent of ‘cloud-first’ architectures and strategies, cloud computing is the rule, not the exception.

Big data storage tools like BigQuery, Hadoop, and Cassandra are used to manage large volumes of structured and unstructured data generated by modern applications. Unlike traditional databases, these tools provide scalable and distributed infrastructure that efficiently stores, processes, and analyzes petabytes of data across clusters.

The fifth edition of the Global Fintech Fest has officially begun at the well-known Bandra Kurla Complex in Mumbai. This three-day event is celebrated as one of the largest fintech festivals in the world, attracting leaders, experts, and enthusiasts from every corner of the globe. The festival is packed with sessions on the latest trends in financial technology, exciting product launches, and the announcement of new partnerships that could play a significant role in shaping the future of the industry.

Exploratory testing, a dynamic and versatile approach to software testing, has gained significant traction in recent years. In previous blog posts we explained what's Exploratory Testing and why it's so helpful. Also, we have discussed How to develop a Structured Exploratory testing strategy and we introduced why it is the real asset to exceptional functionality and superb UX if you want your QA to go above and beyond basic expectations.

Twelve years ago, a Wakefield Research survey revealed that 1 in 3 Americans thought cloud computing was somehow related to the weather. Fast forward to today, 67% of enterprise infrastructure in the US is cloud-based. Given that 92% of enterprises already have a multi-cloud strategy in place or in the works, it’s evident that embracing cloud migration is no longer just an option but a strategic necessity.

Since generative AI exploded onto the global market, organizations have flocked to adopt it. SAP is no exception–late last year, the ERP launched its embedded AI copilot, Joule. In addition, SAP has invested in other AI companies, hired a chief artificial intelligence officer, and added generative AI features to its products. In order to spur cloud adoption, many of SAP’s premium AI features will only be available to RISE with SAP and GROW with SAP customers.

In the continuous quest to raise the bar on software quality, product teams often find it difficult to avoid trade-offs between release speed and test coverage. One of the more significant sources of trade-off tension is associated with test automation runtimes. Achieving the necessary device coverage during testing often requires teams to seek out multiple device cloud providers with different strengths across security, geolocation, device types, and support for alternative test automation frameworks.