BigQuery, Google Cloud’s petabyte-scale data warehouse, lets you ingest and analyze data quickly and with high availability, so you can find new insights, trends, and predictions to efficiently run your business. Our engineering team is continually making improvements to BigQuery so you can get even more out of it. Recently added BigQuery features include new materialized views, column-level security, and BigQuery ML additions.
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 provides an overview of the OpDB data integrity capabilities that help you achieve ACID transactions and data consistency. OpDB guarantees certain properties to ensure atomicity, durability, consistency, and visibility.
Being data-driven is the holy grail of modern business. It allows you to grow 8x faster than your competition, boosts your company’s net earnings by 30% and will have VCs throwing money at you if your organization relies on AI. So, what strategy does one use to become data-driven? Well, it’s actually quite simple: If you follow this recipe to the T, you can have your data cake and eat it.
The year was 1993. The place, a little town in Sweden. A serial killer was on the loose. He randomly shot at people standing at bus stops or sitting in their cars, killing one and wounding many others. The residents of Malmö lived in fear. Window blinds were shut, playgrounds were deserted. The police didn’t know where to start.
In 2019, organizations invested $28.5 billion into machine learning application development (Statistica). Yet, only 35% of organizations report having analytical models fully deployed in production (IDC). When you connect those two statistics, it’s clear that there are a breadth of challenges that must be overcome to get your models deployed and running.
Apache Hadoop Ozone is a distributed key-value store that can manage both small and large files alike. Ozone was designed to address the scale limitations of HDFS with respect to small files. HDFS is designed to store large files and the recommended number of files on HDFS is 300 million for a Namenode, and doesn’t scale well beyond this limit.