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In agile software development, the focus is on adapting to changing conditions or requirements and optimizing the process continuously. Adaptations and optimizations are driven by the development team itself. To be able to judge the course of an iteration reasonably, metrics are generally used. The main objective of this talk it to propose metrics and appropriate visualizations to answer questions of agile development teams. The metrics provide team members with better access to the metadata of their own work. This is intended to enable the team to better understand their own work and to adapt their processes meaningfully based on the information obtained.
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DataStax Enterprise Advanced Replication supports one-way distributed data replication from remote database clusters that might experience periods of network or internet downtime. Benefiting use cases that require a 'hub and spoke' architecture. Learn more at http://www.datastax.com/2016/07/stay-100-connected-with-dse-advanced-replication Advanced Replication docs – https://docs.datastax.com/en/latest-dse/datastax_enterprise/advRep/advRepTOC.html
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DataStax Enterprise (DSE) Graph is a built to manage, analyze, and search highly connected data. DSE Graph, built on NoSQL Apache Cassandra delivers continuous uptime along with predictable performance and scales for modern systems dealing with complex and constantly changing data. Download DataStax Enterprise: Academy.DataStax.com/Download Start free training for DataStax Enterprise Graph: Academy.DataStax.com/courses/ds332-datastax-enterprise-graph
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Data Modeling is the one of the first things to sink your teeth into when trying out a new database. That's why we are going to cover this foundational topic in enough detail for you to get dangerous. Data Modeling for relational databases is more than a touch different than the way it's approached with Cassandra. We will address the quintessential query-driven methodology through a couple of different use cases, including working with time series data for IoT. We will also demo a new tool to get you bootstrapped quickly with MovieLens sample data. This talk should give you the basics you need to get serious with Apache Cassandra.
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In agile software development, the focus is on adapting to changing conditions or requirements and optimizing the process continuously. Adaptations and optimizations are driven by the development team itself. To be able to judge the course of an iteration reasonably, metrics are generally used. The main objective of this talk it to propose metrics and appropriate visualizations to answer questions of agile development teams. The metrics provide team members with better access to the metadata of their own work. This is intended to enable the team to better understand their own work and to adapt their processes meaningfully based on the information obtained.
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DataStax Enterprise Advanced Replication supports one-way distributed data replication from remote database clusters that might experience periods of network or internet downtime. Benefiting use cases that require a 'hub and spoke' architecture. Learn more at http://www.datastax.com/2016/07/stay-100-connected-with-dse-advanced-replication Advanced Replication docs – https://docs.datastax.com/en/latest-dse/datastax_enterprise/advRep/advRepTOC.html
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DataStax Enterprise (DSE) Graph is a built to manage, analyze, and search highly connected data. DSE Graph, built on NoSQL Apache Cassandra delivers continuous uptime along with predictable performance and scales for modern systems dealing with complex and constantly changing data. Download DataStax Enterprise: Academy.DataStax.com/Download Start free training for DataStax Enterprise Graph: Academy.DataStax.com/courses/ds332-datastax-enterprise-graph
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Data Modeling is the one of the first things to sink your teeth into when trying out a new database. That's why we are going to cover this foundational topic in enough detail for you to get dangerous. Data Modeling for relational databases is more than a touch different than the way it's approached with Cassandra. We will address the quintessential query-driven methodology through a couple of different use cases, including working with time series data for IoT. We will also demo a new tool to get you bootstrapped quickly with MovieLens sample data. This talk should give you the basics you need to get serious with Apache Cassandra.
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Apache Cassandra is a leading open-source distributed database capable of amazing feats of scale, but its data model requires a bit of planning for it to perform well. Of course, the nature of ad-hoc data exploration and analysis requires that we be able to ask questions we hadn’t planned on asking—and get an answer fast. Enter Apache Spark. Spark is a distributed computation framework optimized to work in-memory, and heavily influenced by concepts from functional programming languages. It’s exactly what a Cassandra cluster needs to deliver real-time, ad-hoc querying of operational data at scale. In this talk, we’ll explore Spark and see how it works together with Cassandra to deliver a powerful open-source big data analytic solution.
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Apache Cassandra is a leading open-source distributed database capable of amazing feats of scale, but its data model requires a bit of planning for it to perform well. Of course, the nature of ad-hoc data exploration and analysis requires that we be able to ask questions we hadn’t planned on asking—and get an answer fast. Enter Apache Spark. Spark is a distributed computation framework optimized to work in-memory, and heavily influenced by concepts from functional programming languages. It’s exactly what a Cassandra cluster needs to deliver real-time, ad-hoc querying of operational data at scale. In this talk, we’ll explore Spark and see how it works together with Cassandra to deliver a powerful open-source big data analytic solution.
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One is the loneliest number Much, much worse than two Many of PagerDuty’s mission-critical services are based on Cassandra, and as a result we have built up a lot of operational experience over the past few years. Unfortunately, some of our best learnings have come from sizeable failures in production. One of those failures stemmed from having multiple services share the same Cassandra cluster, which was a major factor in PagerDuty’s largest outage of 2014. This talk will relive that outage, sort through the wreckage, and explain why isolating your Cassandra clusters is a best practice you should adopt
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Apidays New York 2024 - Scaling API-first by Ian Reasor and Radu Cotescu, Adobe
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HTML Injection Attacks: Impact and Mitigation Strategies
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Strategies for Landing an Oracle DBA Job as a Fresher
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A Domino Admins Adventures (Engage 2024)
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What Are The Drone Anti-jamming Systems Technology?
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Axa Assurance Maroc - Insurer Innovation Award 2024
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[2024]Digital Global Overview Report 2024 Meltwater.pdf
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Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
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Finology Group – Insurtech Innovation Award 2024
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AWS Community Day CPH - Three problems of Terraform
Handwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed texts
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Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024
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TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
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Automating Google Workspace (GWS) & more with Apps Script
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