Systems | Development | Analytics | API | Testing

With the rapidly changing pace of innovative technology, companies must be able to pivot quickly or perish. The ability to adapt to change is critical to a company’s success. A key factor in the ability to pivot is access to real-time information to facilitate data-driven decisions. Traditionally, that data has existed across multiple systems with no simple method for bringing it all together meaningfully.

When we announced the GA of Cloudera Data Engineering back in September of last year, a key vision we had was to simplify the automation of data transformation pipelines at scale. By leveraging Spark on Kubernetes as the foundation along with a first class job management API many of our customers have been able to quickly deploy, monitor and manage the life cycle of their spark jobs with ease. In addition, we allowed users to automate their jobs based on a time-based schedule.

At Airflow Summit 2021, Unravel’s co-founder and CTO, Shivnath Babu, led a talk titled Data Pipeline HealthCheck for Correctness, Performance & Cost Efficiency. This story, along with the slides and videos included in it, come from the presentation.

For more than 20 years, OpenTable has connected foodies and novice diners with the restaurants they love. But how does its technology work on the back end? To make a long story short: data. Beyond the app and website, OpenTable provides restaurants with software that manages their floor plans, phone reservations, walk-ins, shift scheduling, turn times, and more.

CRM (customer relationship management) software is the lifeblood of any modern B2C company. By monitoring and storing all of your interactions with prospects and customers—from their first visit to your website to their most recent purchase—CRM software makes it dramatically easier to segment your customer base, identify hidden trends in the data, make smarter predictions, and forecasts, and much more.

Are you ready to turbo-charge your data flows on the cloud for maximum speed and efficiency? We are excited to announce the general availability of Cloudera DataFlow for the Public Cloud (CDF-PC) – a brand new experience on the Cloudera Data Platform (CDP) to address some of the key operational and monitoring challenges of standard Apache NiFi clusters that are overloaded with high-performant flows.

We just announced Cloudera DataFlow for the Public Cloud (CDF-PC), the first cloud-native runtime for Apache NiFi data flows. CDF-PC enables Apache NiFi users to run their existing data flows on a managed, auto-scaling platform with a streamlined way to deploy NiFi data flows and a central monitoring dashboard making it easier than ever before to operate NiFi data flows at scale in the public cloud.

Visualize a variety of SaaS metrics, including MRR, ARR, LTV over CAC, NRR, ARPC, and the growth of revenues compared to goals.

Thanks to its user-friendliness and popularity in the field of data science, Python is one of the best programming languages for ETL. Still, coding an ETL pipeline from scratch isn’t for the faint of heart — you’ll need to handle concerns such as database connections, parallelism, job scheduling, and logging yourself. The good news is that Python makes it easier to deal with these issues by offering dozens of ETL tools and packages.