As virtual selling and digital buying continues to grow, data, insights and timely action are becoming more valuable than ever.
Are you looking to migrate a large amount of Hive ACID tables to BigQuery? ACID enabled Hive tables support transactions that accept updates and delete DML operations. In this blog, we will explore migrating Hive ACID tables to BigQuery. The approach explored in this blog works for both compacted (major / minor) and non-compacted Hive tables. Let’s first understand the term ACID and how it works in Hive. ACID stands for four traits of database transactions.
As the strategic role of finance teams continues to evolve, the Office of the CFO faces many new responsibilities. Resource allocation, however, does not always grow in tandem with those responsibilities, leading to scalability challenges for finance teams tasked with doing more with fewer resources.
We’ve come a long way since 1778 when George Washington’s spies gathered and shared military intelligence on the British Army’s tactical operations in occupied New York. But information broadly, and the management of data specifically, is still “the” critical factor for situational awareness, streamlined operations, and a host of other use cases across today’s tech-driven battlefields.
Cloudera has a strong track record of providing a comprehensive solution for stream processing. Cloudera Stream Processing (CSP), powered by Apache Flink and Apache Kafka, provides a complete stream management and stateful processing solution. In CSP, Kafka serves as the storage streaming substrate, and Flink as the core in-stream processing engine that supports SQL and REST interfaces.
Data is the fuel for today’s modern economy – it drives everything from large-scale manufacturing, financial services, energy and transportation to healthcare, media and entertainment and everything in between. This new philosophy of data-centricity has evolved the way organizations think about their IT environments, infrastructure, applications, solutions and even cloud providers.
With all of the buzz around cloud computing, many companies have overlooked the importance of hybrid data. Many large enterprises went all-in on cloud without considering the costs and potential risks associated with a cloud-only approach. The truth is, the future of data architecture is all about hybrid.
The previous decade has seen explosive growth in the integration of data and data-driven insight into a company’s ability to operate effectively, yielding an ever-growing competitive advantage to those that do it well. Our customers have become accustomed to the speed of decision making that comes from that insight. Data is integral for both long-term strategy and day-to-day, or even minute-to-minute operation.
As uncertainty and volatility become the order of the day, buyer behavior and preferences continue to evolve. The continuing global supply chain crisis has resulted in lost sales and market disruptions that have in some cases widely thrown off forecasts.
