Anmol is an experienced software developer with focus on Cloud Monitoring and Reliability. As a Senior Software Engineer in Splunk Enterprise Cloud, he oversees the monitoring and alerting pipelines across all Splunk Cloud stacks. Besides software development, he is actively involved with product management and data science. Before joining Splunk, he led the development and maintenance of several tools for performance engineering, data science, and predictive analytics at Salesforce. He holds a MS in CS from UC Irvine.
AI influencing Politics, insights from Chatbots, Enterprise Data Cloud, handling Video Big Data, and more takeaways from Strata Data Conference 2019, San Francisco.
Highlights and key takeaways include Domain Specific Architectures – the next big thing, Emerging China – evolving from copying ideas to true innovation, and Addressing Risks in AI – Security, Privacy, and Ethics.
Highlights and key takeaways from KDD 2018, 24th ACM SIGKDD conference on Data Science and Data Mining: including what is a deconfounder, how Pinterest approaches Machine Learning, Knowledge Graph for Products, and Differential Privacy.
Highlights and key takeaways from day 2 of AI Conference San Francisco 2017, including current state review, future trends, and top recommendations for AI initiatives.
Highlights and key takeaways from day 1 of AI Conference San Francisco 2017, including current state review, future trends, and top recommendations for AI initiatives.
Let's have a look at common quality issues facing Big Data in terms of the key characteristics of Big Data – Volume, Velocity, Variety, Veracity, and Value.
Efficient implementation is key to achieving the benefits of parallelization, even though parallelism is a good idea when the task can be divided into sub-tasks that can be executed independent of each other without communication or shared resources.
Anmol is an experienced software developer with focus on Cloud Monitoring and Reliability. As a Senior Software Engineer in Splunk Enterprise Cloud, he oversees the monitoring and alerting pipelines across all Splunk Cloud stacks. Besides software development, he is actively involved with product management and data science. Before joining Splunk, he led the development and maintenance of several tools for performance engineering, data science, and predictive analytics at Salesforce. He holds a MS in CS from UC Irvine.
Must-Know: What are common data quality issues for Big Data and how to handle them?
