Gartner predicts that by 2023, organizations that promote data sharing will outperform their peers on most business value metrics. According to Debra Logan, Gartner’s Research Vice President, “Data sharing is the way to optimize higher quality data and more robust data and analytics to solve business challenges and goals.” Given these numbers, it is clear that businesses will need to embrace application software integration as a core business strategy.

MongoDB vs DynamoDB: How do you choose between them? Whether you are a two-man team bootstrapping a proof of concept or an established one battling with high throughput and heavy load; this post can serve as a guidepost in your decision process. Before going into the details, a brief history lesson on how these technologies emerged is pertinent; you must understand the optimal conditions for running these systems and how they operate in the wild before making an informed choice.

According to Gartner, leading organizations in every industry are wielding data and analytics as competitive weapons. Companies that leverage data as a competitive differentiator will stand the best chance of acting faster on opportunities and responding to threats in a competitive marketplace. The problem is that most companies aren’t aware of the value of their data. As a result, they aren’t leveraging the full potential of their data to make informed decisions.

Shared Data Experience (SDX) on Cloudera Data Platform (CDP) enables centralized data access control and audit for workloads in the Enterprise Data Cloud. The public cloud (CDP-PC) editions default to using cloud storage (S3 for AWS, ADLS-gen2 for Azure). This introduces new challenges around managing data access across teams and individual users. To solve these challenges for S3 and ADLS-gen2, Cloudera has introduced a new service — the Ranger Authorization Service (RAZ).

Across the federal government, agencies are struggling to identify, organize, analyze, and act on troves of data. It’s a problem that leaders are working actively to tackle, but they’re in a race against immeasurable volumes of data that is continuously being generated in perpetuity in stores known and unknown. At the Internal Revenue Service, decades’ worth of data exceeds even the most cutting-edge processing capabilities.

Learn how off-the-shelf, open-source dbt packages make data modeling frictionless.

From cost estimates and project ROI to schedule variance and task completion rates, project managers share the top KPIs they are monitoring.

Cloud testing, in simple terms, means testing software applications using the resources provided by the cloud. Resources can be any element i.e., hardware, software, or infrastructure which are necessary to carry out tests. Cloud testing helps an organization gain competitiveness by reducing the cost of testing. By using cloud computing services for testing, organizations or businesses can shorten the provisioning time.

As more and more companies move to a multi-cloud strategy and increase usage of a cloud native infrastructure, API providers are under a lot of pressure to deliver APIs at scale in multi-cloud environments. At the same time, APIs should follow each company’s security requirements and best practices, no matter the cloud platform. These reasons explain why many providers have such complex API authorization requirements.

In 2019, my team at Kong introduced a new open source project called Kuma. Now a sandbox project of the CNCF, Kuma is a modern, universal control plane for service mesh based on Envoy. As we celebrate Kuma’s achievements, I want to thank the Kuma community for your support and contributions!