How Big Data is Changing the Way We Listen to Music

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Technology and music are best friends now – though record company execs smoking fat cigars have been replaced by coffee-sipping tech whiz kids. And Big Data and analytics have played a big part in this reinvigorated friendship. From recommendation engines designed to choose the perfect individual playlist, to Internet of Things enabled pop concerts, data is redefining the dynamics of the music industry, as well as the relationship between listeners and music, in ever more creative ways. In the past, the record industry had relatively little way of understanding who was buying their LPs, cassettes or CDs. Downloading allowed them to begin tracking listening habits and making recommendations. With the current streaming model, however, the floodgates are open, with detailed information about when, how and where we are listening all up for grabs. This SlideShare explores the usage of Big Data in the music industry.

How Big Data is Changing the Way We Listen to Music

How Big Data is Changing the Way We Listen to Music

How Big Data is Changing the Way We Listen to Music

How Big Data is Changing the Way We Listen to Music

How Big Data is Changing the Way We Listen to Music

How Big Data is Changing the Way We Listen to Music

How Big Data is Changing the Way We Listen to Music

How Big Data is Changing the Way We Listen to Music

How Big Data is Changing the Way We Listen to Music

How Big Data is Changing the Way We Listen to Music

How Big Data is Changing the Way We Listen to Music

How Big Data is Changing the Way We Listen to Music

How Big Data is Changing the Way We Listen to Music

How Big Data is Changing the Way We Listen to Music

How Big Data is Changing the Way We Listen to Music

How Big Data is Changing the Way We Listen to Music

How Big Data is Changing the Way We Listen to Music

How Big Data is Changing the Way We Listen to Music

How Big Data is Changing the Way We Listen to Music

How Big Data is Changing the Way We Listen to Music

How Big Data is Changing the Way We Listen to Music

How Big Data is Changing the Way We Listen to Music

How Big Data is Changing the Way We Listen to Music

How Big Data is Changing the Way We Listen to Music

How Big Data is Changing the Way We Listen to Music

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Sakha Global has been transforming ideas into solutions through technology consulting & software development since 2005. With presence in USA & India and a team of 400+ resources, we are a recognized solution specialist in product development with 150+ products delivered worldwide in the areas of Mobile (Android & iOS), Big Data, Machine Learning, Blockchain, AR / VR, IoT & Pega BPM. We have offices across USA, with a development center in Bangalore, India. We are ISO 9001:2015 certified.

Sakha - Corporate Profile

A large part of the IT budget in many companies is used for maintaining and managing the legacy application portfolio. Containers and container orchestration tools, such as Kubernetes, are emerging trends well under way to become game changers in the software engineering and IT industry. The way that the containers concept provides an abstraction layer to infrastructure is unprecedented for software developers. For cloud-native scenarios, containerization is the process of packaging compiled software code, libraries, configuration, and compute, network, and storage definitions into a set of containers and container management (Kubernetes) definitions. These containers are deployed on a runtime engine, such as Docker Engine or CRI-O. Scalability, high availability, and cluster management are arranged by the container orchestration tool. As with all migration approaches, choosing the right legacy containerization technique is a matter of striking the right balance between investment, business outcome, cost-effectiveness gain, technical feasibility, and risk appetite. This SlideShare explores the concept of migration of containerized legacy application to the cloud in brief.

Migration of Containerized Legacy Application to the Cloud

Migration of Containerized Legacy Application to the Cloud

Migration of Containerized Legacy Application to the Cloud

Infrastructure as Code, also referred to as IaC, is an IT practice that codifies and manages underlying IT infrastructure as software. The purpose of Infrastructure as Code is to enable developers or operations teams to automatically manage, monitor and provision resources, rather than manually configure discrete hardware devices and operating systems. Infrastructure as Code is sometimes referred to as programmable or software-defined infrastructure. The concept of Infrastructure as Code is similar to programming scripts, which are used to automate IT processes. However, scripts are primarily used to automate a series of static steps that are repeated numerous times across multiple servers. Infrastructure as Code uses higher-level or descriptive language to code more versatile and adaptive provisioning and deployment processes. This SlideShare explores the concept of Infrastructure as Code in brief.

Infrastructure as Code

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OpenTelemetry is a collection of tools, APIs and SDKs, used to instrument, generate, collect, and export telemetry data (metrics, logs and traces) to help analyze a software’s performance and behavior. OpenTelemetry (also referred to as OTel) aims to address the full range of observability signals across traces, metrics and logs. Loosely defined, observability is the ability to understand what’s happening inside a system from the knowledge of the external data it produces, which are usually logs, metrics, and traces. Having a common format for how observability data is collected and sent is where OpenTelemetry comes into play. As a Cloud Native Computing Foundation (CNCF) incubating project, OTel aims to provide unified sets of vendor-agnostic libraries and APIs — mainly for collecting data and transferring it somewhere. This SlideShare explores OpenTelemetry in brief.

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OpenTelemetry - The Open Source Vision for Unified Observability

It can be difficult for enterprise application development or IT operations professionals to get their arms around multi-cloud DevOps. That's because a single multi-cloud deployment might depend on hundreds of remote application and infrastructure components. These, in turn, might use myriad interfaces and orchestrations, and execute in dozens of clouds with varying degrees of federated interoperability. Multi-clouds have already arrived in enterprises. According to a recent survey , around 85% of companies are already operating multiple clouds. However, only 39% of respondents have implemented DevOps processes and tool chains across these deployments. To ensure the CI/CD of applications and infrastructure across increasingly heterogeneous clouds, enterprises will need DevOps tools that integrate with those platforms. This SlideShare explores the concept of Automating Software Delivery on Multiple Clouds in brief.

Automating Software Delivery on Multiple Clouds

Automating Software Delivery on Multiple Clouds

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Code quality is important, as it impacts the overall software quality. And quality impacts how safe, secure, and reliable a codebase is. High quality is critical for many development teams today. And it's especially important for those developing safety-critical systems. Just one line of poorly written code can drive an enterprise into the ground, meaning that development projects can also come to an end because of them. That’s why improving code quality is necessary. This SlideShare explores ways to improve code quality in brief.

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The internet has a carbon footprint. Behind the rhetoric of digital solutions making our lives lighter, there is a very big problem. The internet, and our usage of it, is not so light at all. The internet as a whole currently accounts for 2% of global emissions. That’s the same as all global aviation. And this figure is increasing rapidly. The more data we consume, the more energy we use, and data consumption shows no signs of slowing as people worldwide grasp for better and faster internet speeds. By 2025, Cisco predicts that the internet will account for 3.5% of global carbon emissions. The internet is not slowing down. As it matures and plays more of an integral part in our lives, we expect more from the internet. As each year passes, people are developing more complex, visually elaborate websites. These websites may look and work well – but behind the scenes they are bloated, using huge amounts of energy each time they are loaded. To put this in perspective: loading the average website uses up the equivalent amount of energy as boiling a kettle for a cup of tea. Environmental guilt has started to creep into everyday life for most people. There is always a sense that we should be doing better. Thankfully, there are many things we can do to reduce our internet carbon footprint. One of the means is using the most efficient file format for graphics (such as SVG) to lessen the power needed to load the site. This SlideShare explores the concept of SVG format in brief.

How the SVG Format is Reducing Carbon Footprint

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Millennials have seen multiple breakthroughs in wireless technology. GSM networks brought us the cell phone age in the 90s. 3G networks gave us the smartphone age a decade later. 4G and LTE brought us our paradoxical world of complaining if things take more than a few seconds to load. 4G networks are still being built, 3G phones are still being sold, but there’s a new technology on the horizon. A new and improved technology, 5G (5th generation) mobile networks will bring many changes. The next generation of wireless connectivity, 5G, is becoming a ubiquitous topic but is still the subject of many myths and misconceptions. Although various use cases are emerging, only a few are compelling enough to generate strong demand in the short term. This SlideShare explores the concept of 5G-based product development in brief.

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Engaged consumers have a significant impact on the bottom line. Brands that successfully engage their customers realize lower customer attrition and higher share of wallet. Gamification is a recent mechanism to increase customer engagement, born our of the user-centered approach. The user-centered approach, which strives for creating products highly responding to the user’s needs, has become the major philosophy behind many projects. Following this method, designers constantly search for the new techniques improving user experience which depends on various aspects including emotions. The thing is that users expect a product to be simple and enjoyable in use, so the idea to add a “fun” element to the UX came as it is. But how to make the product fun and enjoyable in use? The technique called gamification was created to solve the problem. This SlideShare explores what’s the method of gamification in design and how it can improve UX and engagement.

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Ivy is Angular's new rendering pipeline and view engine. Smaller bundles, faster compilations, better debugging, dynamic loading of module & components, and advanced concepts like higher order components are promised by this 8.0 version of Angular. Angular already being a popular platform for building mobile and desktop web applications, the current version 8.0 aka Ivy has backward compatibility and by using it we can get smaller bundles, easier to debug API, faster compilation and dynamic loading of modules and components. This SlideShare explores the concept of Angular Ivy in brief.

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Houdini is a collection of APIs that expose the CSS engine's internals to developers. CSS does an amazing amount of work when it comes to UI / UX. You change a single attribute and suddenly your entire website appears in a different layout. Houdini CSS is a new collection of browser APIs which allow you to gain more access to your browser’s CSS engine. The APIs are accessible through JavaScript, making them web developer friendly. Houdini is a W3C task force with the overriding goal of trying to make browser support issues a thing of the past. Houdini also attempts to resolve some of the more difficult things around CSS development, which is, at times, extremely delicate by nature. This SlideShare explores the concept of CSS Houdini in brief.

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The success of the Internet of Things (IoT) depends heavily on the extent of achieved interoperability, as well as on addressing the many security and privacy challenges. Due to the multitude of types of devices, systems, and protocols, and their scale of deployment and limited resources, some of these systems will be extremely challenging to interconnect and secure. The underlying edge network or edge-computing infrastructure, supporting the IoT, will also need to provide security and privacy guarantees. Given that IoT devices and edge networks are deployed by a multitude of players, decentralization has become a key enabling design goal of the system. For example, recent advances in Distributed Ledger Technology (DLT) and Blockchains can be incorporated to support decentralized security. In turn, decentralized security through distributed trust can help overcome privacy concerns and scalability bottlenecks, both of which are becoming increasingly serious in large-scale deployments, such as smart cities or Industry 4.0. A decentralized approach to IoT interconnection brings forth many opportunities, but also important challenges, e.g., in state synchronization, trust management, and the difficulties of operating with constrained devices and networking modes. This SlideShare explores the concept of Decentralized Computing in IoT in brief.

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Lazy loading images means loading artifacts such as images on websites asynchronously — that is, after the above-the-fold content is fully loaded, or even conditionally, only when they appear in the browser’s viewport. This means that if users don’t scroll all the way down, images placed at the bottom of the page won’t even be loaded. A number of websites use this approach, but it’s especially noticeable on image-heavy sites. By postponing the loading of images that are not immediately required – or, in some cases, not loading them at all – the browser saves resources (bandwidth as well as CPU). The page loads faster and the user experience is improved as saved resources can be affected to more critical content. There are also server-side gains. The CPU and bandwidth required to delivered the resources are subjected to less stress, reducing the hosting and/or CDN costs. This SlideShare explores the concept of Lazy Loading in brief.

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Foundation models are machine learning models which are easily capable of performing variable tasks on large and huge datasets. FMs have managed to get a lot of attention due to this feature of handling large datasets. It can do text generation, video editing to protein folding and robotics. In case we believe that FMs can help the hospitals and patients in any way, we need to perform some important evaluations, tests to test these assumptions. In this review, we take a walk through Fms and their evaluation regimes assumed clinical value. To clarify on this topic, we reviewed no less than 80 clinical FMs built from the EMR data. We added all the models trained on structured and unstructured data. We are referring to this combination of structured and unstructured EMR data or clinical data.

Reassessing the Bedrock of Clinical Function Models: An Examination of Large ...

Reassessing the Bedrock of Clinical Function Models: An Examination of Large ...

Reassessing the Bedrock of Clinical Function Models: An Examination of Large ...

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