How can we become Elastic Certified Engineers?
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(Weekly Roundup) Top AI, Data Science, Analytics Appointments In India
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How Azure Cloud is shaping the future of cloud services
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How to Manage Secrets in Kubernetes
Learn how Kubernetes Secrets work, how they differ from ConfigMaps, and how to create and manage secrets safely — including cloud-native secret management options.
DataOps and Beyond: How DevOps Methodology Is Transforming Data Science
DataOps applies DevOps principles—automation, CI/CD, Agile culture, and continuous feedback—to data pipelines and data science workflows. Learn what DataOps is, how it differs from DevOps, and what benefits organizations can expect.
Google Cloud Machine Images: Simplifying Data Science VM Deployments
Google Cloud’s Machine Images feature lets system administrators and data scientists capture, clone, and restore full virtual machine environments — including multi-disk configurations and instance metadata — without manual reconfiguration.
dotData Achieves AWS Machine Learning Competency Status
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Acxiom Joins AWS Data Exchange as a Launch Partner, Bringing Global Marketing Data to the Cloud
Acxiom announced its participation as a Launch Partner for AWS Data Exchange, giving AWS customers direct cloud access to aggregated marketing analytics data spanning EMEA, APAC, and the Americas.
10 Leading Cloud Computing Courses and Training Programmes in India
A guide to ten notable cloud computing courses and training programmes available in India, covering curriculum, cost, duration, and key differentiators for IT professionals looking to upskill.
Google Cloud at RSNA 2019: Healthcare AI, DICOM Services, and Medical Imaging Competitions
Google Cloud showcased healthcare-focused cloud solutions at RSNA 2019, including managed DICOM services, HIPAA-supported deployments, and AI-powered medical imaging competitions in partnership with Kaggle.
Michael Berthold on End-to-End Data Science Using KNIME Analytics Platform
KNIME CEO Michael Berthold outlined a four-phase end-to-end data science cycle at the KNIME Fall Summit 2019, covering data gathering, modelling, deployment, and optimisation—along with three generations of ML automation.
How Microsoft’s Azure Synapse Analytics Helps Developers and Businesses
Announced at Microsoft Ignite 2019, Azure Synapse Analytics unifies data warehouses and data lakes into a single analytics platform — integrating Power BI, Azure Machine Learning, and a rewritten SQL engine designed for cloud-scale workloads.
Digital Turbine, Inc. (NASDAQ: APPS) Stock Analysis: Technical Indicators, Analyst Ratings, and Price Targets
A technical and fundamental snapshot of Digital Turbine, Inc. (NASDAQ: APPS) stock, covering RSI, MACD, analyst price targets, valuation multiples, and revenue forecasts as of late October 2019.
Going Serverless with AWS: AWS Lambda Explained for DevOps Engineers
Serverless doesn’t mean no servers—it means you stop managing them. Learn the history of serverless computing, how AWS Lambda works, and the key limitations you need to plan around.
DevOps now most sought-after skill, and with good reason
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Splunk .conf19: Turning Data Into Doing with the Data-to-Everything Platform
Splunk’s .conf19 conference drew more than 11,000 attendees to Las Vegas, where executives unveiled Splunk Enterprise 8.0, Mission Control, FedRAMP authorization for Splunk Cloud, and a vision centered on moving from data collection to data-driven action.
Four Big Factors Shaping the Future of Data Science
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The Power of Kubernetes Done the Right Way: Lessons from HPC and AI Workloads
How data science teams at the Dell EMC HPC and AI Innovation Lab use Kubernetes container orchestration to streamline deep learning model development, training, and deployment at scale across supercomputing clusters.
LazyDocker: A Terminal UI That Makes Docker Commands Easier to Manage
LazyDocker is an open-source terminal UI for Docker and Docker Compose, built in Go with the gocui library. It consolidates container management, logs, metrics, and common commands into a single keyboard-driven interface.
CI/CD for Data Science and Machine Learning: A Practical Introduction
Continuous integration and continuous deployment aren’t just for application developers. Learn how CI/CD practices apply to data science and machine learning workflows, reduce technical debt, and help teams ship models with confidence.