3 Things to Learn About:
*The IoT ecosystem and data management considerations for IoT
*Top IoT use cases and data architecture strategies for managing the sheer volume and variety of IoT data
*Real-life case studies on how our customers are using Cloudera Enterprise to drive insights and analytics from all of their IoT data
The document discusses the Internet of Things (IoT). It defines IoT as connecting "things" or objects to the Internet. It traces the origins and development of IoT from 1999 when the term was coined to its growth in recent years. The document also outlines IoT architecture including devices, gateways, protocols and cloud platforms. It examines applications of IoT in various sectors like home automation, transportation, healthcare, agriculture, smart grids and smart cities. Finally, it analyzes challenges to IoT adoption like sensing environments, connectivity standards, power consumption and security/privacy issues.
This document outlines the syllabus for an Internet of Things Technology course taught by Dr. Syed Mustafa at HKBK College of Engineering in Bengaluru. It covers key topics like smart objects, sensors, actuators, and micro-electro-mechanical systems. The evaluation process includes three internal assessments weighted at 30%, 40%, and 30% respectively, covering different portions of the syllabus. Students must also submit assignments and have a class participation rate of at least 85%.
A talk presented at IEEE ComSoc workshop on Evolution of Data-centers in the context of 5G.
Discuss about what is edge computing and management issues in Edge Computing
The slides defines IoT and show the differnce between M2M and IoT vision. It then describes the different layers that depicts the functional architecture of IoT, standard organizations and bodies and other IoT technology alliances, low power IoT protocols, IoT Platform components, and finally gives a short description to one of IoT low power application protocols (MQTT).
The document discusses Internet of Things (IoT) and provides an overview in three main points:
1. IoT involves connecting physical objects/things to the internet so they can communicate and transfer data without human interaction. This allows the objects to collect and share information.
2. Current trends show efforts to connect 26 billion objects by 2020, with healthcare, transportation and manufacturing leading the way. Common communication methods for connecting objects include WiFi, Bluetooth, and Zigbee.
3. IoT provides benefits like real-time analytics and control, but also faces challenges regarding security, adoption rates, compatibility and power constraints. Main application areas include home automation, smart cities, manufacturing and automotive.
The IoT is here to stay. As with any other trend in the history of computer software, it’s starting to produce a new generation of cloud platforms. This tech talk will identify and explain what to look for when evaluating an IoT cloud platform to ensure a successful deployment of IoT strategies.
The document discusses cloud computing from the perspectives of application developers, quality assurance teams, and enterprises. It provides rationales for why cloud computing can reduce capital expenditures and operational expenditures compared to maintaining their own on-premise hardware and software. The document also summarizes the NIST definition of cloud computing and describes its essential characteristics, service models, and deployment models.
IoT Architectures for a Digital Twin with Apache Kafka, IoT Platforms and Mac...Kai Wähner
A digital twin is a digital replica of a living or non-living physical entity. This session discusses the benefits and IoT architectures of a Digital Twin in Industrial IoT (IIoT) and its relation to Apache Kafka, IoT frameworks and Machine Learning. Kafka is often used as central event streaming platform to build a scalable and reliable digital twin for real time streaming sensor data. A live demo shows a scalable digital twin infrastructure for condition monitoring and predictive maintenance in real time for a connected car infrastructure leveraging Kafka, MQTT and TensorFlow.
Key Take-Aways:
• Learn about use cases and characteristics of a digital twin in various industries
• Understand how to build a digital twin for every single (of tens of thousands) IoT device or machine
• See different IoT architectures with Kafka and other IoT technologies and products, including edge, hybrid and global deployments
• Understand the relation to Machine Learning and bring added value to your IoT infrastructure by enabling use cases like predictive maintenance
• Understand how the Apache Kafka enables scalable and flexible end-to-end integration processing from IIoT data to various backend applications
• Watch a live demo of an end-to-end integration, real time processing and analytics of thousands of IoT devices
More details:
https://www.kai-waehner.de/blog/2019/11/28/apache-kafka-industrial-iot-iiot-build-an-open-scalable-reliable-digital-twin/
https://www.kai-waehner.de/blog/2020/03/25/architectures-digital-twin-digital-thread-apache-kafka-iot-platforms-machine-learning/
https://youtu.be/Q3eKPEVwNVY
Application development for the internet of thingsPankesh Patel
1. The document discusses application development challenges for the Internet of Things (IoT), including heterogeneity of devices, large scale, lack of separation of concerns, and life-cycle issues.
2. It proposes a conceptual model that classifies IoT concepts and relates development concerns to promote reusability.
3. A multi-stage model-driven approach is presented using a set of modeling languages to abstract heterogeneity, scale, and support automation across development stages.
Independent of the source of data, the integration of event streams into an Enterprise Architecture gets more and more important in the world of sensors, social media streams and Internet of Things. Events have to be accepted quickly and reliably, they have to be distributed and analysed, often with many consumers or systems interested in all or part of the events. Dependent on the size and quantity of such events, this can quickly be in the range of Big Data. How can we efficiently collect and transmit these events? How can we make sure that we can always report over historical events? How can these new events be integrated into traditional infrastructure and application landscape?
Starting with a product and technology neutral reference architecture, we will then present different solutions using Open Source frameworks and the Oracle Stack both for on premises as well as the cloud.
This document discusses the integration of IoT and cloud computing. It provides overviews of cloud computing, including characteristics, stakeholders, and service delivery models. It discusses the motivation for integrating IoT and cloud, including leveraging cloud benefits and addressing conflicting properties. Integration models are described including adapting cloud models (IaaS, PaaS, SaaS) to IoT. Challenges of integration like data quality and lack of interoperability are covered along with solutions like abstraction layers and adapting existing cloud models. Edge/fog computing is introduced as an approach to address limitations of full cloud integration. Popular public IoT cloud platforms and their architectures are analyzed.
Students will be able to comprehend the ideas of the Internet of Things and will be able to develop basic IoT applications
Explain about the Internet of Things (IoT) and its need and
also how it functions.
2. Identify the reasons that contributed to the development of IoT technology.
3. Use Real IoT protocols for communication.
4. Challenges in IoT
5. Different areas of IoT applications
6. Develop basic IoT Applications
Industry 4.0 (IIoT) is changing the face of manufacturing like never before. Global situation of tariff war and re-shoring are catalysts driving this change in addition to technology adaption.
Check out this Comparative Analysis between Industry 4.0 (IIoT) and SCADA systems to understand the basic differences between the two.
The document discusses the key features and architecture of the Internet of Things (IoT). It describes IoT as connecting physical devices through sensors and software to collect and exchange data over networks. The key features discussed are artificial intelligence, interconnectivity, distributed processing, heterogeneity, interoperability, scalability, security, and dynamic changes. The basic IoT architecture includes sensor networks, gateways, and communication technologies to connect devices. Sensor networks gather data from various sensors, while gateways act as an interface between sensor networks and cloud/application services. Common wireless technologies enabling IoT device connectivity include RFID, WLAN, and short-range wireless protocols.
This document provides an introduction to the Internet of Things (IOT). It defines IOT as the collection of physical devices connected over the internet that can exchange data with less human involvement. The history and key technologies that enabled IOT are discussed, including wireless sensor networks, RFID, and cloud computing. The document also outlines the typical architecture of an IOT system including sensing, network, service, and application layers. Common IOT standards, protocols, and applications are summarized along with research areas and challenges in IOT development.
Through this presentation, you will get to know about Edge computing and explore the fields where it is needed.
You can start exploring the technical knowledge by seeing what industries are working on now-days
The document discusses the future of the Internet of Things (IoT). It covers key topics such as future applications and challenges of IoT, trends in IoT, future job roles, and vision for the future of IoT. Some of the main points discussed include how IoT will transform industries like healthcare and automotive through applications like remote health monitoring and connected vehicles. However, security is a major challenge as more devices are connected. Other trends discussed are growth of smart cities and use of data and artificial intelligence. The future of IoT is seen as limitless with potential in new areas like manufacturing and opportunities for new types of jobs and business models.
Powering the Internet of Things with Apache HadoopCloudera, Inc.
Without the right data management strategy, investments in Internet of Things (IoT) can yield limited results. Apache Hadoop has emerged as a key architectural component that can help make sense of IoT data, enabling never before seen data products and solutions.
How to Build Continuous Ingestion for the Internet of ThingsCloudera, Inc.
The Internet of Things is moving into the mainstream and this new world of data-driven products is transforming a vast number of industry sectors and technologies.
However, IoT creates a new challenge: how to build and operationalize continual data ingestion from such a wide and ever-changing array of endpoints so that the data arrives consumption-ready and can drive analysis and action within the business.
In this webinar, Sean Anderson from Cloudera and Kirit Busu, Director of Product Management at StreamSets, will discuss Hadoop's ecosystem and IoT capabilities and provide advice about common patterns and best practices. Using specific examples, they will demonstrate how to build and run end-to-end IOT data flows using StreamSets and Cloudera infrastructure.
The document discusses how Cloudera provides a data management platform for IoT data. It handles massive volumes of data from diverse sources in real-time and batch. The platform includes capabilities for data storage, processing, machine learning, analytics and management. Example use cases show how customers use the platform for predictive maintenance, smart cities, connected vehicles and other IoT applications.
Simplifying Real-Time Architectures for IoT with Apache KuduCloudera, Inc.
3 Things to Learn About:
*Building scalable real time architectures for managing data from IoT
*Processing data in real time with components such as Kudu & Spark
*Customer case studies highlighting real-time IoT use cases
In this presentation I do a review of the architecture of an AI application for IoT environments.
Since specific modeling and training aspects also have an impact on the final implementation of an enterprise ready solution, such solutions become very complex pretty soon.
The complexity of AI system for IoT is a big challenge – thus, I want to break this complexity down into particular views, which emphasize the individual but still interconnected aspects more clearly.
IoT is reshaping the manufacturing and industrial processes, effectively changing the paradigm from one of repair and replace to more of predict and prevent. Using data streaming from connected equipment and machinery, organizations can now monitor the health of their assets and effectively predict when and how an asset might fail. However, without the right data management strategy and tools, investments in IoT can yield limited results. Join Cloudera and Tata Consultancy Services (TCS) for a joint webinar to learn more about how organizations are using advanced analytics and machine learning to drive IoT enabled predictive maintenance.
Manufacturers have an abundance of data, whether from connected sensors, plant systems, manufacturing systems, claims systems and external data from industry and government. Manufacturers face increased challenges from continually improving product quality, reducing warranty and recall costs to efficiently leveraging their supply chain. For example, giving the manufacturer a complete view of the product and customer information integrating manufacturing and plant floor data, with as built product configurations with sensor data from customer use to efficiently analyze warranty claim information to reduce detection to correction time, detect fraud and even become proactive around issues requires a capable enterprise data hub that integrates large volumes of both structured and unstructured information. Learn how an enterprise data hub built on Hadoop provides the tools to support analysis at every level in the manufacturing organization.
Explore IoT in Big Data while brewing beer. All verticals are instrumenting devices to learn more about their process to help cut costs or improve efficiency.
Managing Microsoft Applications with VistaraVistara
Vistara provides a unified cloud platform for managing IT operations across physical, virtual, and cloud environments. The platform enables customers to manage Microsoft applications and infrastructure from a single pane of glass, eliminating the need to use multiple point tools. Vistara has over 1000 customers including IT departments, managed service providers, and partners. The platform provides comprehensive capabilities for defining, delivering, monitoring, and managing IT services throughout their lifecycle.
Cloudera Altus: Big Data in the Cloud Made EasyCloudera, Inc.
Cloudera Altus makes it easier for data engineers, ETL developers, and anyone who regularly works with raw data to process that data in the cloud efficiently and cost effectively. In this webinar we introduce our new platform-as-a-service offering and explore challenges associated with data processing in the cloud today, how Altus abstracts cluster overhead to deliver easy, efficient data processing, and unique features and benefits of Cloudera Altus.
This document discusses using Cloudera Enterprise to analyze data from connected cars. It begins with an overview of the connected car market and use cases such as predictive maintenance, usage-based insurance, and mobility management. Examples are given of how major automakers and insurance companies are using connected car data and analytics. The rest of the document focuses on Cloudera Enterprise's capabilities for ingesting, storing, processing, and analyzing large volumes of diverse connected car data in real-time and batch modes. A demo is outlined to showcase predictive maintenance, usage-based insurance, and public services use cases.
CL2015 - Datacenter and Cloud Strategy and PlanningCisco
This document discusses strategies for data center and cloud transformation over the next 5 years. It outlines key digital business trends like data growth, cloud adoption, and security threats that are driving organizations' IT initiatives. These include managing increased data and applications, optimizing cloud strategies, addressing disruptive business models, and securing distributed data and applications. The document advocates adopting flexible consumption models, automation, and supporting edge/IoT applications. It positions Cisco as uniquely able to enable digital transformations through its portfolio of networking, compute, storage, automation, analytics, and security solutions.
Dell NVIDIA AI Roadshow - South Western OntarioBill Wong
- Artificial intelligence (AI) is mimicking human intelligence through machine algorithms like those used for chess and facial recognition. Machine learning (ML) is a subset of AI that uses algorithms to parse data, learn from data, and make predictions. Deep learning (DL) uses artificial neural networks to develop relationships in data and is used for applications like driverless cars and cybersecurity.
- AI technologies are enabling digital transformation and require infrastructure like edge computing, GPUs, FPGAs, deep learning accelerators, and specialized hardware to power applications of AI, ML, and DL. Dell Technologies provides platforms and solutions to accelerate AI workloads and support digital transformation.
Simplify IT Operations by Unifying Element Management with VistaraVistara
IT administrators can simplify IT operations by unifying element management with Vistara. Using a single tool for enterprise monitoring and management reduces the amount of time IT administrators spend context switching, increasing their productivity. Vistara also makes it possible to use a single tool to monitor and manage services that are deployed on both the private cloud and the public cloud in a hybrid cloud configuration.
The Future of Data Management: The Enterprise Data HubCloudera, Inc.
The document discusses the enterprise data hub (EDH) as a new approach for data management. The EDH allows organizations to bring applications to data rather than copying data to applications. It provides a full-fidelity active compliance archive, accelerates time to insights through scale, unlocks agility and innovation, consolidates data silos for a 360-degree view, and enables converged analytics. The EDH is implemented using open source, scalable, and cost-effective tools from Cloudera including Hadoop, Impala, and Cloudera Manager.
Turning Data into Business Value with a Modern Data PlatformCloudera, Inc.
The document discusses how data has become a strategic asset for businesses and how a modern data platform can help organizations drive customer insights, improve products and services, lower business risks, and modernize IT. It provides examples of companies using analytics to personalize customer solutions, detect sepsis early to save lives, and protect the global finance system. The document also outlines the evolution of Hadoop platforms and how Cloudera Enterprise provides a common workload pattern to store, process, and analyze data across different workloads and databases in a fast, easy, and secure manner.
What are the standards for IoT? What are the requirements for different parts of your business for IoT? For your infrastructure? For your employees? For your customers? For your partners? Examples of Successful Enterprise IOT architecture patterns and use cases. What are problems like security for IoT?
Travis Cox from Inductive Automation and Arlen Nipper from Cirrus Link Solutions discusses the various ways that tag data can be leveraged through cloud services provided by Amazon Web Services and Microsoft Azure. These experts will also show you different ways to get data up to the cloud in a simple, efficient, and secure manner.
Learn more about cloud services such as:
- Machine learning
- Analytics
- Business intelligence
- Data lakes
- Cloud databases
- And more
The document discusses using Cloudera DataFlow to address challenges with collecting, processing, and analyzing log data across many systems and devices. It provides an example use case of logging modernization to reduce costs and enable security solutions by filtering noise from logs. The presentation shows how DataFlow can extract relevant events from large volumes of raw log data and normalize the data to make security threats and anomalies easier to detect across many machines.
Cloudera Data Impact Awards 2021 - Finalists Cloudera, Inc.
The document outlines the 2021 finalists for the annual Data Impact Awards program, which recognizes organizations using Cloudera's platform and the impactful applications they have developed. It provides details on the challenges, solutions, and outcomes for each finalist project in the categories of Data Lifecycle Connection, Cloud Innovation, Data for Enterprise AI, Security & Governance Leadership, Industry Transformation, People First, and Data for Good. There are multiple finalists highlighted in each category demonstrating innovative uses of data and analytics.
2020 Cloudera Data Impact Awards FinalistsCloudera, Inc.
Cloudera is proud to present the 2020 Data Impact Awards Finalists. This annual program recognizes organizations running the Cloudera platform for the applications they've built and the impact their data projects have on their organizations, their industries, and the world. Nominations were evaluated by a panel of independent thought-leaders and expert industry analysts, who then selected the finalists and winners. Winners exemplify the most-cutting edge data projects and represent innovation and leadership in their respective industries.
The document outlines the agenda for Cloudera's Enterprise Data Cloud event in Vienna. It includes welcome remarks, keynotes on Cloudera's vision and customer success stories. There will be presentations on the new Cloudera Data Platform and customer case studies, followed by closing remarks. The schedule includes sessions on Cloudera's approach to data warehousing, machine learning, streaming and multi-cloud capabilities.
Machine Learning with Limited Labeled Data 4/3/19Cloudera, Inc.
Cloudera Fast Forward Labs’ latest research report and prototype explore learning with limited labeled data. This capability relaxes the stringent labeled data requirement in supervised machine learning and opens up new product possibilities. It is industry invariant, addresses the labeling pain point and enables applications to be built faster and more efficiently.
Data Driven With the Cloudera Modern Data Warehouse 3.19.19Cloudera, Inc.
In this session, we will cover how to move beyond structured, curated reports based on known questions on known data, to an ad-hoc exploration of all data to optimize business processes and into the unknown questions on unknown data, where machine learning and statistically motivated predictive analytics are shaping business strategy.
Introducing Cloudera DataFlow (CDF) 2.13.19Cloudera, Inc.
Watch this webinar to understand how Hortonworks DataFlow (HDF) has evolved into the new Cloudera DataFlow (CDF). Learn about key capabilities that CDF delivers such as -
-Powerful data ingestion powered by Apache NiFi
-Edge data collection by Apache MiNiFi
-IoT-scale streaming data processing with Apache Kafka
-Enterprise services to offer unified security and governance from edge-to-enterprise
Introducing Cloudera Data Science Workbench for HDP 2.12.19Cloudera, Inc.
Cloudera’s Data Science Workbench (CDSW) is available for Hortonworks Data Platform (HDP) clusters for secure, collaborative data science at scale. During this webinar, we provide an introductory tour of CDSW and a demonstration of a machine learning workflow using CDSW on HDP.
Shortening the Sales Cycle with a Modern Data Warehouse 1.30.19Cloudera, Inc.
Join Cloudera as we outline how we use Cloudera technology to strengthen sales engagement, minimize marketing waste, and empower line of business leaders to drive successful outcomes.
Leveraging the cloud for analytics and machine learning 1.29.19Cloudera, Inc.
Learn how organizations are deriving unique customer insights, improving product and services efficiency, and reducing business risk with a modern big data architecture powered by Cloudera on Azure. In this webinar, you see how fast and easy it is to deploy a modern data management platform—in your cloud, on your terms.
Modernizing the Legacy Data Warehouse – What, Why, and How 1.23.19Cloudera, Inc.
Join us to learn about the challenges of legacy data warehousing, the goals of modern data warehousing, and the design patterns and frameworks that help to accelerate modernization efforts.
Leveraging the Cloud for Big Data Analytics 12.11.18Cloudera, Inc.
Learn how organizations are deriving unique customer insights, improving product and services efficiency, and reducing business risk with a modern big data architecture powered by Cloudera on AWS. In this webinar, you see how fast and easy it is to deploy a modern data management platform—in your cloud, on your terms.
Explore new trends and use cases in data warehousing including exploration and discovery, self-service ad-hoc analysis, predictive analytics and more ways to get deeper business insight. Modern Data Warehousing Fundamentals will show how to modernize your data warehouse architecture and infrastructure for benefits to both traditional analytics practitioners and data scientists and engineers.
Explore new trends and use cases in data warehousing including exploration and discovery, self-service ad-hoc analysis, predictive analytics and more ways to get deeper business insight. Modern Data Warehousing Fundamentals will show how to modernize your data warehouse architecture and infrastructure for benefits to both traditional analytics practitioners and data scientists and engineers.
The document discusses the benefits and trends of modernizing a data warehouse. It outlines how a modern data warehouse can provide deeper business insights at extreme speed and scale while controlling resources and costs. Examples are provided of companies that have improved fraud detection, customer retention, and machine performance by implementing a modern data warehouse that can handle large volumes and varieties of data from many sources.
Extending Cloudera SDX beyond the PlatformCloudera, Inc.
Cloudera SDX is by no means no restricted to just the platform; it extends well beyond. In this webinar, we show you how Bardess Group’s Zero2Hero solution leverages the shared data experience to coordinate Cloudera, Trifacta, and Qlik to deliver complete customer insight.
Federated Learning: ML with Privacy on the Edge 11.15.18Cloudera, Inc.
Join Cloudera Fast Forward Labs Research Engineer, Mike Lee Williams, to hear about their latest research report and prototype on Federated Learning. Learn more about what it is, when it’s applicable, how it works, and the current landscape of tools and libraries.
Analyst Webinar: Doing a 180 on Customer 360Cloudera, Inc.
451 Research Analyst Sheryl Kingstone, and Cloudera’s Steve Totman recently discussed how a growing number of organizations are replacing legacy Customer 360 systems with Customer Insights Platforms.
Build a modern platform for anti-money laundering 9.19.18Cloudera, Inc.
In this webinar, you will learn how Cloudera and BAH riskCanvas can help you build a modern AML platform that reduces false positive rates, investigation costs, technology sprawl, and regulatory risk.
Introducing the data science sandbox as a service 8.30.18Cloudera, Inc.
How can companies integrate data science into their businesses more effectively? Watch this recorded webinar and demonstration to hear more about operationalizing data science with Cloudera Data Science Workbench on Cazena’s fully-managed cloud platform.
The code is written and the tests pass. I just have to commit this last round of changes to my branch. Wait, why does that say committed to main? Did I commit all those changes to main? Arghh! I can’t redo all of this!
Committing changes to the wrong branch, forgetting files, misspelling the commit message, and needing to undo commits are some of the “advanced” features of Git that we normal people run into way too often and need help with. The fixes are often easy – once you know what they are. But in the heat of the moment, with the deadline (or Friday afternoon) approaching, it isn’t always easy to figure out what magic spell to cast to get Git to do what you need.
We’ll spend some time looking at typical Git situations people get themselves into, and then we’ll demonstrate how to get out of them. This isn’t about Git internals or a Git master’s class – this real-world Git when things aren’t going right. And there will be plenty of time for questions, so bring your “best” Git nightmare scenarios so we can figure out how to recover.
BDRSuite - #1 Cost effective Data Backup and Recovery Solutionpraveene26
BDRSuite and BDRCloud by Vembu are comprehensive and cost-effective backup and disaster recovery solutions designed to meet the diverse data protection requirements of Businesses and Service Providers.
With BDRSuite & BDRCloud, you can backup diverse IT workloads from any location, including VMs (VMware, Hyper-V, KVM, Proxmox VE, oVirt), Servers & Endpoints (Windows, Linux, Mac), SaaS Applications (Microsoft 365, Google Workspace), Cloud VMs (AWS, Azure), NAS/File Shares and Databases & Applications (Microsoft Exchange Server, SQL Server, SharePoint Server, PostgreSQL, MySQL).
You can store backup anywhere like On-Premise/Remote storage, Private/Public Cloud, and BDRCloud.
You can centrally manage the entire backup infrastructure with BDRSuite’s self-hosted centralized management console (or) BDRCloud-hosted centralized management console.
You can quickly recover from data loss or ransomware attacks—all at an affordable price.
To know more visit our website -
https://www.bdrsuite.com/
https://www.bdrcloud.com/
How Generative AI is Shaping the Future of Software Application DevelopmentMohammedIrfan308637
Generative AI is revolutionizing software development. Find out how it enhances innovation and productivity. https://www.qisacademy.com/blog-detail/the-power-of-generative-ai-in-software-application-development
In today's dynamic business landscape, ERP software systems are essential tools for businesses worldwide, including those in the UAE. These systems cater to the unique needs of the UAE's rapidly changing economy and expanding industries.
This blog examines the top 10 ERP companies in the UAE, highlighting their innovative products, exceptional customer support, and significant impact on the regional business community. These companies excel in providing ERP solutions that enhance efficiency and growth for businesses throughout the UAE.
1. **Odoo**
- Odoo ERP is a comprehensive business management solution with features like accounting, HR, sales, inventory control, and CRM. Its user-friendly interface simplifies processes and boosts productivity. Banibro IT Solutions leverages Odoo to transform business operations.
- **Details:**
- Suitable for: Small, Medium, Large Businesses
- Open Source: Yes
- Cloud-based: Yes (Cloud and On-premises)
- Support: Phone, Chat, Email
- Payment: Yearly, Monthly
- Multi-Language: Yes
- OS Support: Windows, Mac, iOS, Android
- API: Available
2. **Microsoft Dynamics 365**
- Dynamics 365 offers a centralized platform for small and medium-sized businesses, integrating with Microsoft apps and cloud services for scalability. It simplifies data processing with user-friendly interfaces and customizable reporting.
- **Details:**
- Suitable for: Small, Medium, Large Businesses
- Support: Phone, Chat, Email, Knowledge Base
- Payment: One-Time, Yearly, Monthly
- Multi-Language: No
- OS Support: Web App, Windows, iOS, Android
- API: Not specified
3. **FirstBIT ERP**
- Known for serving small and medium-sized businesses, FirstBIT ERP offers comprehensive solutions and exceptional customer service, enhancing productivity and efficiency.
- **Details:**
- Suitable for: Medium, Large Businesses
- Open Source: Yes/No
- Cloud-based: Yes (Cloud and On-premises)
- Support: Phone, Email, Video Tutorials
- Payment: Yearly, Monthly
- Multi-Language: Yes
- OS Support: Web App, Windows, Mac, iOS, Android
- API: Available
4. **Ezware Technologies**
- Ezware Technologies provides top-notch ERP solutions for various industries with user-friendly modules that streamline complex business processes.
- **Details:**
- Suitable for: Small, Medium, Large Businesses
- Support: Phone, Chat, Email, Knowledge Base
- Payment: One-Time, Yearly, Monthly
- Multi-Language: No
- OS Support: Web App, Windows, Mac, iOS, Android
- API: Not specified
5. **RealSoft**
- RealSoft by Coral is popular in Dubai, offering modules for contracting, real estate, job costing, manufacturing, trading, and finance. It's VAT-enabled and affordable for medium-sized businesses.
- **Details:**
- Suitable for: Small, Medium, Large Businesses
- Open Source: No
- Cloud-based: On-premises
-
Empowering Businesses with Intelligent Software Solutions - GrawlixAarisha Shaikh
Explore Grawlix's comprehensive suite of intelligent software solutions designed to drive transformative growth and scalability for businesses. This presentation covers our expertise in bespoke software development, digital marketing, web design, cloud solutions, cybersecurity, AI/ML, and IT consulting. Discover how Grawlix's customized solutions enhance productivity, streamline processes, and enable data-driven decision-making. Learn about our key projects, technologies, and the dedicated team who ensures exceptional client satisfaction through innovation and excellence.
BitLocker Data Recovery | BLR Tools Data Recovery SolutionsAlina Tait
BLR Tools provides an advanced BitLocker Data Recovery Tool specifically engineered to recover lost or inaccessible data from BitLocker-encrypted drives. Whether you're dealing with accidental deletion, encryption key problems, or system crashes, our cutting-edge software guarantees a secure and efficient recovery process. Rely on BLR Tools for dependable BitLocker data recovery and effortlessly restore access to your essential files.
Fix Production Bugs Quickly - The Power of Structured Logging in Ruby on Rail...John Gallagher
Rails apps can be a black box. Have you ever tried to fix a bug where you just can’t understand what’s going on? This talk will give you practical steps to improve the observability of your Rails app, taking the time to understand and fix defects from hours or days to minutes. Rails 8 will bring an exciting new feature: built-in structured logging. This talk will delve into the transformative impact of structured logging on fixing bugs and saving engineers time. Structured logging, as a cornerstone of observability, offers a powerful way to handle logs compared to traditional text-based logs. This session will guide you through the nuances of structured logging in Rails, demonstrating how it can be used to gain better insights into your application’s behavior. This talk will be a practical, technical deep dive into how to make structured logging work with an existing Rails app.
I talk about the Steps to Observable Software - a practical five step process for improving the observability of your Rails app.
Understanding Automated Testing Tools for Web Applications.pdfkalichargn70th171
Automated testing tools for web applications are revolutionizing how we ensure quality and performance in software development. These tools help save time, reduce human error, and increase the efficiency of web application testing processes. This guide delves into automated testing, discusses the available tools, and highlights how to choose the right tool for your needs.
AI is revolutionizing DevOps by advancing algorithmic optimizations in pipelines, elevating efficiency levels, and introducing predictive functionalities. This article examines how AI is reshaping continuous integration, deployment strategies, monitoring practices, and incident management within DevOps ecosystems, ultimately amplifying efficiency and dependability.
Alluxio Webinar | What’s new in Alluxio Enterprise AI 3.2: Leverage GPU Anywh...Alluxio, Inc.
Alluxio Webinar
July.23, 2024
For more Alluxio Events: https://www.alluxio.io/events/
Speaker:
- Shouwei Chen (core maintainer and product manager, Alluxio)
In today's AI-driven world, organizations face unprecedented demands for powerful AI infrastructure to fuel their model training and serving workloads. Performance bottlenecks, cost inefficiencies, and management complexities pose significant challenges for AI platform teams supporting large-scale model training and serving. On July 9, 2024, we introduced Alluxio Enterprise AI 3.2, a groundbreaking solution designed to address these critical issues in the ever-evolving AI landscape.
In this webinar, Shouwei Chen will introduce exciting new features of Alluxio Enterprise AI 3.2:
- Leveraging GPU resources anywhere accessing remote data with the same local performance
- Enhanced I/O performance with 97%+ GPU utilization for popular language model training benchmarks
- Achieving the same performance as HPC storage on existing data lake without additional HPC storage infrastructure
- New Python FileSystem API to seamlessly integrate with Python applications like Ray
- Other new features, include advanced cache management, rolling upgrades, and CSI failover
Literals - A Machine Independent Feature21h16charis
Introduction to Literals, A machine independent feature. The presentation is based on the prescribed textbook for System Software and Compiler Design, Computer Science and Engineering - System Software by Leland. L. Beck,
D Manjula.
Old Tools, New Tricks: Unleashing the Power of Time-Tested Testing ToolsBenjamin Bischoff
In the rapidly evolving landscape of software development and testing, it is tempting to chase the latest tools and technologies. However, some of the most effective solutions have been in existence for decades. In this talk, we’ll delve into the enduring value of these timeless testing tools.
We’ll explore how established tools like Selenium, GNU Make, Maven, and Bash remain vital in today’s software development and testing toolkit even though they have been around for a long time (some were even invented before I was born). I’ll share examples of how these tools have addressed our testing and automation challenges, showcasing their adaptability, versatility, and reliability in various scenarios. I aim to demonstrate that sometimes, the “old” ways can indeed be the best ways.
Crowd Strike\Windows Update Issue: Overview and Current Statusramaganesan0504
Crowd Strike\Windows Update Issue: Overview and Current Status
Discover the latest on the CrowdStrike Windows update issue, including an overview, current status, and support steps for affected customers. Learn about the identified defect, its impact on Windows hosts, and CrowdStrike's committed actions to ensure ongoing security and stability.
What is CrowdStrike?
CrowdStrike is a prominent cybersecurity technology company that specializes in providing advanced threat intelligence and endpoint protection solutions. Founded in 2011 by George Kurtz, Dmitri Alperovitch, and Gregg Marston, CrowdStrike has quickly established itself as a leader in the cybersecurity industry. Here are some key aspects of