infogix
During this interview-style webcast Infogix’s Emily Washington, SVP of Product Management looked ahead in 2018 and predicted what trends will come to fruition, what new concepts will graze the horizon, and what may fail to launch.
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Arcadiadata
Brand new research published from Dresner Advisory Services digs deeply into the trends in 2018 around big data analytics. Where are organizations heading in 2019? How are analytic and data warehouse architectures evolving to enable faster and deeper self-service analytics and BI for organizations looking to create a competitive edge? How is public, private and hybrid clouds factoring into deployment decisions? What are the hottest open source projects from Apache Spark to Kudu, Kafka, Hadoop, and beyond?
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Veeam
The benefits of turning to the cloud are numerous; scalability, control, flexibility, and power to name a few. While transitioning to the cloud has many strong points, there are still the challenges of data and application protection. In this webinar, you’ll learn:
- How to leverage multi-cloud as an addition to your traditional data center
- What applications and services require the most protection in hybrid mode and how to protect them
- The importance of portability and how to avoid lock-in
- How to get better compliance and data protection by moving data between on-prem and the cloud.
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Modern-day systems are transforming into complex, open-source, cloud-native services running on various environments and being developed/deployed at lightning speed by distributed teams. When working on these systems, identifying a broken link in the chain can be near impossible. Everything fails at one point or another, whether due to code bugs, infrastructure overload, or changes in end-user behavior or market driven factors or errors in data collection. This has led to the rise of DataOps with a focus on changing the organizational speed and trust in delivering data pipelines and the related artifacts by co-creating “decision quality” data with the consumers. This development has led to the idea of observability that includes monitoring, tracking, and triaging incidents to prevent downtime of the systems and around several factors such as freshness, distribution, volume, schema, lineage.
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