Cloud migration, also called “move to cloud,” is the process of moving existing data processing tasks to a cloud platform, such as Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform. Private clouds and hybrid cloud solutions can also serve as destinations.
In cloud migration, also known as “move to cloud,” you move existing data processing tasks to a cloud platform, such as Amazon Webservices (AWS), Microsoft Azure, or Google Cloud Platform, to private clouds, and-or to hybrid cloud solutions. See our blog post, What is Cloud Migration, for an introduction. Figure 1: Steps in cloud migration.
Users today are asking ever more from their data warehouse. This is resulting in advancements of what is provided by the technology, and a resulting shift in the art of the possible. As an example of this, in this post we look at Real Time Data Warehousing (RTDW), which is a category of use cases customers are building on Cloudera and which is becoming more and more common amongst our customers.
How Hitachi Vantara’s global IT team is enabling the “new normal” and delivering at speeds previously thought impossible.
One of the really big trends that we're seeing in the analytics space, is the move towards talking about the analytics experience. Analytics experience is about supporting or triggering decisions and transactions. This is a shift from what I would describe as the passive use of analytics, where people were expected to use dashboards and reports that didn't add a lot of value to their transactions or decision making. The difference sounds subtle, but it's really quite profound.
The Fourth Industrial Revolution has not halted despite the global pandemic. If anything, COVID-19 has only accelerated the adoption of Industry 4.0, leading businesses across industries to use Internet of Things (IoT) technology and Big Data in a more sophisticated manner.
As we covered in part 1 of this blog series, Snowflake’s platform is architecturally different from almost every traditional database system and cloud data warehouse. Snowflake has completely separate compute and storage, and both tiers of the platform are near instantly elastic. The need to do advanced resource planning, agonize over workload schedules, and prevent new workloads on the system due to the fear of disk and CPU limitations just go away with Snowflake.
With the massive explosion of data across the enterprise — both structured and unstructured from existing sources and new innovations such as streaming and IoT — businesses have needed to find creative ways of managing their increasingly complex data lifecycle to speed time to insight.
As a product feature for your app, embedded analytics is undoubtedly a valuable tool. But historically, many product managers and software developers have approached it as a standalone capability. This has led to dashboards and reporting modules added as an afterthought, rather than as a founding strategic component of the core application.
Cloudera services logs offer a breadth of information to assist in cluster maintenance; from assisting in security checks, auditing tasks, and validation for performance tuning and testing tasks – to name a few. However, log records generated by these services do not hold the same value for every organisation.
