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Cloud

How to migrate an on-premises data warehouse to BigQuery on Google Cloud

Data teams across companies have continuous challenges of consolidating data, processing it and making it useful. They deal with challenges such as a mixture of multiple ETL jobs, long ETL windows capacity-bound on-premise data warehouses and ever-increasing demands from users. They also need to make sure that the downstream requirements of ML, reporting and analytics are met with the data processing.

What is Amazon Redshift Spectrum?

Amazon S3 (Simple Storage Service) has been around since 2006. Most use this scalable, cloud-based service for archiving and backing up data. Within 10 years of its birth, S3 stored over 2 trillion objects, each up to 5 terabytes in size. Enterprises value their data as something worth preserving. But much of this data lies inert, in “cold” data lakes, unavailable for analysis. Also called “dark data”, it can hold key insights for enterprises.

Redshift Join: How to use Redshift's Join Clause

Redshift’s JOIN clause is perhaps the second most important clause after SELECT clause, and it is used even more ubiquitously, considering how interconnected a typical application database’s tables are. Due to that connectivity between datasets, data developers require many joins to collect and process all the data points involved in most use cases. Unfortunately, as the number of tables you’re joining in grows, so does the sloth of your query.

PostgreSQL to Amazon Redshift: 4 Ways to Replicate Your Data

PostgreSQL is the preferred platform of millions of developers around the world. The open-source tool is one of the most powerful databases on the planet, with the ability to handle sophisticated analytical workloads and high levels of concurrency. That makes PostgreSQL (also called Postgres) a popular DB for scientific research and AI/ML projects. It’s also a popular production database for data-driven companies in every industry. But no database is perfect.

Top 3 CloudOps Priorities for 2022, from Hitachi Vantara & AWS

As an estimated 92% of enterprises have adopted hybrid and multicloud strategies, according to the 2021 State of the Cloud Report from Flexera, cloud operations (CloudOps) teams face increasing pressure to simultaneously manage costs while improving business outcomes. What levers can CloudOps teams pull to achieve operational objectives such as reducing hybrid and distributed cloud complexity, enhancing security, and automating processes?

Will cloud ecosystems finally make insight to action a reality?

For decades, the technologies and systems that deliver analytics have undergone massive change. What hasn’t changed, however, is the goal: using data-driven insights to drive actions. Insight to action has been a consistent vision for the industry. Everyone from data practitioners to technology developers have sought this elusive goal, but as Chief Data Strategy Officer Cindi Howson points out, it has remained unfulfilled — until now.

Channel global decoupling for region discovery

Ably is a platform for pub/sub messaging. Publishes are done on named channels, and clients subscribed to a given channel have all messages on that channel delivered to them. The Ably pub/sub backend is multi-region: we run the production cluster in 7 AWS regions, and channel pub/sub operates seamlessly between them.

CDP on Azure: Harnessing the Power of Data Flow and Event Processing

Data is being created at an ever increasing rate and generating insights through event streams has become a critical function for businesses. How can we process this data flowing in the enterprise, evaluate, enrich and transform it, all in real time to enable fast analytics to support intelligent decision making? Join us for this session where we will look at how we can use the elastic nature of Azure to scale Data Flows and perform SQL operations in realtime on streaming data from a variety of sources.