Yellowfin 9 is defined by the belief that design matters. The ability to create a cohesive design look and feel across analytics dashboards and reports is particularly crucial for independent software vendors (ISVs) that embed analytics into their applications. Interestingly, when you take a look at the wider analytics market, few vendors are providing the toolkit that designers and developers need to build the analytical experiences they want.

ETL tools help companies to streamline and enhance their data operations. They automate the repetitive tasks involved in extracting raw data from sources, transforming data into a consumable format and loading into data warehouses, where it is ready to be analyzed. With so many offerings available to you, all of which do the heavy lifting ‘out of the box’, it is hard to discern which ETL tool is best suited to your needs.

“Alone we can do so little; together we can do so much.” – a famous quote by Hellen Keller is very much valid even in current times, especially in the context of teamwork. The relationship between any two people is considered good when communication between them is healthy. And on the same lines, a team is able to work ‘together’ better when their communication is strong.

We built Kong to handle any API at any level of scale, but running APIs at scale means storing and managing data at scale. That’s why we’ve always recommended Apache Cassandra for the biggest Kong deployments. Cassandra is powerful and proven, but it does require some skill to install and operate – which is why we’re excited to hear that Datastax is making Cassandra easy to use at any level of scale with DataStax Astra, a Database-as-a-Service built on Apache Cassandra.

“When you’re working from home you should try and do it systematically and methodologically”, says John Bennett a veteran work-at-homer. “It’s a lot like running a business from home, which is what I do”. John night know a thing or two about it, since he’s been working from home in upstate New Hampshire for the last 20 years.

Working with Rookout customers, I have noticed a significant pattern in how they describe engineering routines in the days before our software became a part of their daily workflow. It shows up in various engineering tasks such as developing new features, reproducing and fixing bugs, or even just documenting the existing system and how to best utilize it. It is also consistent across industries and tech stack.

Laravel development services have been growing in popularity, with the Laravel framework often being compared to CakePHP. This article will show how to choose the best framework to meet specific business or solution requirements in the most effective way. Laravel and CakePHP are both very popular PHP frameworks. PHP is often used for creating dynamic websites or building high-end apps. PHP frameworks make it possible to create affordable websites with impressive UI/UX.

With increasingly draconian measures worldwide aimed at keeping people at home to quell the spread of COVID-19, companies of all shapes and sizes and across the majority of industries are finding themselves in the same situation – how to equip and empower their workforce for mobile working. More than 5 million companies around the world will experience an impact at a cost to the global economy exceeding US$1 trillion.

This blog post is part of a series on Cloudera’s Operational Database (OpDB) in CDP. Each post goes into more details about new features and capabilities. Start from the beginning of the series with, Operational Database in CDP. This blog post gives you an overview of the OpDB management tools and features in the Cloudera Data Platform. The tools discussed in this article will help you understand the various options available to manage the operations of your OpDB cluster.

There are many reasons to run a big data distribution, such as Cloudera Data Hub (CDH) and Hortonworks Data Platform (HDP), in the cloud with Infrastructure-as-a-Service (IaaS). The main reason is agility. When the business needs to onboard a new use case, a data admin can bring on additional virtual infrastructure to their clusters in the cloud in minutes or hours. With an on-prem cluster, it may take weeks or months to add the infrastructure capacity for the new use cases.