Tag: Patterns

Feed: Featured Blog Posts - Data Science Central. Author: Partha Pritam Deka. Author: Partha Deka and Rohit Mittal 1. Introduction Automation in Industrial manufacturing: Today’s increased level of automation in manufacturing also demands automation of material quality inspection with little human intervention. The trend is to reach human level accuracy or more in quality inspection with automation. To stay competitive, modern Industrial firms strive to achieve both quantity and quality with automation without compromising one over the other. Deep Learning for Quality inspection: To meet industry standards quality inspectors in manufacturing firms inspect product quality usually after the product is manufactured, it’s ... Read More

Feed: AWS Partner Network (APN) Blog. Author: Shashi Raina. By Shashi Raina, Partner Solution Architect at AWSBy Veda Shankar, Senior Developer Advocate at OmniSciWe generate quintillions of bytes of data every day, but on the face of it the data is not necessarily useful. To make data useful, it should be processed into information. In this post, we’ll talk about how OmniSci, an AWS Partner Network (APN) Standard Technology Partner, provides a platform to make this process of changing data into information faster, cheaper, and interactive. With the rapid growth of data comes the challenge of getting meaningful information from ... Read More

Feed: AWS Compute Blog. Author: Chris Munns. Serverless application architectures enable you to break large projects into smaller, more manageable services that are highly reusable and independently scalable, secured, and evolved over time. As serverless architectures grow, we have seen common patterns that get reimplemented across companies, teams, and projects, hurting development velocity and leading to wasted effort. We have made it easier to develop new serverless architectures that meet organizational best practices by supporting nested applications in AWS SAM and the AWS Serverless Application Repository.How it works Nested applications build off a concept in AWS CloudFormation called nested stacks ... Read More

Feed: AWS Big Data Blog. Whatever your industry, data is central to how organizations function. When we discuss data strategy with customers, it’s often in the context of how do they ingest, store, process, analyze, distribute, and ultimately secure data.Amazon EMR is a managed Hadoop framework that you use to process vast amounts of data. One of the reasons that customers choose Amazon EMR is its security features. For example, customers like FINRA in regulated industries such as financial services, and in healthcare, choose Amazon EMR as part of their data strategy. They do so to adhere to strict regulatory ... Read More

Feed: Big Data Made Simple. Author: Baiju NT. The global energy market is undergoing a massive shift with the emergence of decarbonization, decentralization, and new technologies. Utilities, independent power producers (IPPs), and other energy companies are exploring effective ways to manage the imbalance in demand and supply caused by the growing use of unpredictable renewable energy source (RES) in power generation.Therefore, utilities, energy companies, and grid operators are exploring ways to employ AI technologies to improve the accessibility and efficiency of renewable energy technologies. Despite its nascence, AI possesses tremendous potential to transform the energy & utilities sector.“In combination with ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Bill Schmarzo. The opportunity to watch and coach the University of San Francisco (USF) students during our annual Hackathon with our friends at Good Dataprobably taught me as much as it taught the students. The lessons learned I’ll share here will not only benefit future classes, but my customers.  It also gives me an opportunity to make special mention of one Hackathon team that really delivered the goods! This year’s Hackathon focused on analyzing air traffic delays (a subject area with which I unfortunately consider myself an expert).  We used data ... Read More

Feed: SAS Blogs. Author: John Maynard. Photo by Pixabay via CC2.0 The Data Revolution is causing disruption everywhere. Even governments are feeling the effects. While the public sector may be less prepared for the impending changes, government has good reasons to embrace the Data Revolution. First, governments have been collecting data for years. They have lots of data. This supports programs, policy assessment, and often compliance requirements for program grants. The difficulty is pooling, accessing, and using this data effectively. This is key to unlocking the power of advanced data analytics. The Rise of the Government Chief Data Officer According ... Read More

Feed: AWS Government, Education, & Nonprofits Blog. Author: publicsector. The climate data factory is a French startup working on making future climate information easily accessible. The team believes that easy access to actionable data of future climate conditions is essential to fight climate change.Read on for the Q&A with Dr. Harilaos Loukos of the climate data factory on how we can best make use of data. What is future climate information and what do you mean by “ready to use”? Future climate information is created by climate models that simulate the Earth’s future climate, while considering scenarios of future atmospheric ... Read More

Feed: Neo4j Graph Database Platform. Author: Bryce Merkl Sasaki. By Emil Eifrem, CEO & Co-Founder, Neo4j, Inc. | December 13, 2018Reading time: 8 minutes Just yesterday, I got to announce the addition of Denise Persson – CMO at Snowflake – to the Neo4j Board of Directors.Today, I get to announce another incredibly important executive appointment: Mike Asher has joined Neo4j as our inaugural chief financial officer (CFO).Since Mike works from our global headquarters in San Mateo, California, he and I recently got to sit down for an interview. Here’s how it went.For readers who don’t know you, could you tell ... Read More

Feed: AWS Big Data Blog. Understanding Windows system and service health on a global scale is challenging. You capture server log data, and then analyze and manipulate the data in real time to create actionable telemetry insights. Amazon Kinesis Agent for Microsoft Windows makes it efficient to ingest Windows server log data into your AWS ecosystem for analysis. This blog post discusses using Kinesis Agent for Windows to capture and aggregate Windows Dynamic Host Configuration Protocol (DHCP) server logs. Then turning that data into service health graphs in Amazon CloudWatch.How do you quantify network access metrics of a team across ... Read More