In digital transformation projects, it’s easy to imagine the benefits of cloud, hybrid, artificial intelligence (AI), and machine learning (ML) models. The hard part is to turn aspiration into reality by creating an organization that is truly data-driven.
The manufacturing industry, like any other industry, is not immune to data challenges. Sourcing data, wrangling it and ensuring it’s being used in a governed, standardized way are not uncommon problems. Particularly in manufacturing, issues surface with inventory management, within the supply chain and with logistics.
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.
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.
Migros is the largest retailer in Turkey, with more than 2500 outlets selling fresh produce and groceries to millions of people. To maintain high-quality operations, the company depends on fresh, accurate data. And to ensure high data quality, Migros depends on Talend. The sheer volume of data managed by Migros is astonishing. The company’s data warehouse currently holds more than 200 terabytes, and Migros is running more than 7,000 ETL (extract, transform, load) jobs every day.
Every enterprise is trying to collect and analyze data to get better insights into their business. Whether it is consuming log files, sensor metrics, and other unstructured data, most enterprises manage and deliver data to the data lake and leverage various applications like ETL tools, search engines, and databases for analysis. This whole architecture made a lot of sense when there was a consistent and predictable flow of data to process.
In my previous blog post, I shared examples of how data provides the foundation for a modern organization to understand and exceed customers’ expectations. However, the important role data occupies extends beyond customer experience and revenue, as it becomes increasingly central in optimizing internal processes for the long-term growth of an organization.
