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best javascript frameworks for 2021
Best JavaScript Frameworks for 2021


According to Stackoverflow’s 2021 Developer Survey, JavaScript is the most used language for the eighth consecutive year, with 67.7% of people choosing it. The main reason for this popularity is that JavaScript is versatile and can use for front-end and back-end development and testing websites or web applications.

If you google “JavaScript framework,” you will find many JavaScript frameworks, each with its advantages and uses. Because there are so many choices of JavaScript frameworks for front-end, back-end development, or even testing, it can be challenging to choose the right one to suit your needs.

It can be tough to find the proper framework for your needs. In this article on the best JavaScript frameworks for 2021, I’ve used StateOfJS 2019, Stackoverflow’s Developer Survey 2021, and NPM trends to compile a list of the best JavaScript frameworks for front-end, back-end, and testing that can help you with this.

Front-end JavaScript frameworks

JavaScript has been widely using for the front-end development for almost two decades. Famous structures such as React, Vue, and Angular have gained a vast legion of followers, while recently, some new competitors have found success in challenging the big 3. Here are the six best front-end frameworks in 2021 -.

1|  React.js

The first place in our ranking of the best JavaScript frameworks for 2021 in the front-end category is React.js. React.js is an open-source front-end JavaScript library (not a full-fledged framework) created in 2011 by a team of Facebook developers led by Jordan Walke and became open-source in June 2013. The prototype was called “FaxJS” and was the first test in the Facebook News Feed. React can be regarded as one of the biggest disruptors in the web development industry, and it was a real breakthrough in shaping the web applications we see today.

React introduced a component-driven, functional and declarative programming style for creating interactive user interfaces for mainly single-page web applications. React offers ultra-fast rendering using a “virtual DOM” that renders only the parts that have changed, rather than causing the entire page. Another essential feature of React is the use of a simpler JSX syntax instead of JavaScript.

Although learning React is a bit more complicated than the other best front-end JavaScript frameworks on this list, React supports by a vast developer community, rich learning resources, and massive adoption in every corner of the world.

React consistently tops the popularity charts for front-end JavaScript frameworks, whether it’s the Stack Overflow Developer Survey or the State OF JS Survey. React has always won the crown as the favorite front-end JavaScript framework. The world’s biggest companies and brands like Airbnb, Facebook, Instagram, Netflix, Twitter, WhatsApp, and many more built with React. It would not be wrong to assume that React.js is arguably the best JavaScript framework.

2 | Vue.js

Vue.js is a lightweight, open-source JavaScript framework used to build creative user interfaces and high-performance single-page web applications with minimal effort.

Vue was first announced in 2014 by Evan Yu, a Google developer who took inspiration from Angular to provide a simple, lightweight, and efficient alternative in the form of Vue.js. Vue takes much of its functionality from React and Angular but has significantly improved those features to provide a better, easier to use, and more secure framework. The best example of this approach is Vue’s provision of bi-directional data binding, as seen in Angular, and ‘Virtual DOM,’ as seen in React.

Similarly, Vue is very flexible, allowing it to function as a complete end-to-end framework, like Angular, as well as a stateful view layer, like React. Thus Vue’s main advantage is its progressive nature, which is simpler, more accessible, and less restrictive to adapt to developers’ needs. In the last two years, Vue has exploded in popularity, displacing the angular and complex dominance of React as the best JavaScript framework. Some of the world’s biggest companies, such as Adobe, Apple, BMW, Louis Vuitton, and Nintendo, have adopted Vue.

3 | Angular

In third place in the Best JavaScript Frameworks of 2021 category is Angular.js, Google’s open-source, script-based framework used to create the client-side of a single-page web application. Angular was created in 2010 by Google engineers Misko Hevery and Adam Abrons as AngularJS (or Angular 1). AngularJS was widely known and at the height of its popularity, but the advent of React exposed its serious flaws, and it has been relegated to oblivion. As a result, AngularJS was rewritten entirely from scratch and Angular 2 (or simply Angular) in 2016.

AngularJS (Angular 1) took inspiration from React. They made significant changes, the most important of which was moving from an M-V-W (Model-View-Whatever) architecture to a component-oriented architecture like React to a component-based architecture like React. Today Angular is an example of the most secure JavaScript frameworks for building enterprise applications; over a million websites use Angular, including Google, Forbes, IBM, and Microsoft.

4|  Emberjs

Fourth place in the front-end category of the Best JavaScript Frameworks 2021 list goes to Ember.js. It is an open-source JavaScript framework. Unlike the other frameworks we have reviewed, Ember uses the Model-View-ViewModel (MVVW) architectural.

Ember was originally a SproutCore 2.0 framework that was renamed Ember.js by Yehuda Katz, a veteran developer who is considered one of the leading creators of jQuery. Ember’s most popular and essential features are the Ember command-line interface, which is itself very powerful. Ember’s most popular and essential features are the Ember command-line interface, a powerful productivity tool.

Ember is one of the older JavaScript frameworks compared to React, Vue, and Svelte, but it still has a large user base at big companies like Microsoft, LinkedIn, Netflix, and Twitch. It has many users in its customer base. Old friends like Backbone and Polymer have disappeared, but Amber has somehow managed to hang on to Fort through a passionate community.

5| Preact.js

At number five in the front-end category of our list of the best JavaScript frameworks for 2021 is Preact.js. Preact.js is a lightweight, fast and powerful alternative to React (it’s not a complete framework). Jason Miller created preact, Senior Developer Programs Engineer at Google, and used several developers as a subset of React. Jason Miller made preact, Senior Developer Programs Engineer at Google, and is used by several developers as a subset of React, with some features stripped out.

Preact.js  base on the same basic principles as React, a component-based approach using Virtual Dom while fully compatible with React

You can also use React packages without compromising on speed, performance, and lean size. Unless you need the full potential of React, most developers will use Preact during development and even switch to Preact in production. There are many large companies use Preact, including Tencent, Uber, and Lyft. 

Conclusion

These are not even remotely all of the frameworks available for Javascript front-end development, but they do make up the bulk of such frameworks currently in use. As Javascript capabilities continue to evolve (through the ECMAscript process), so too will the likely migration of framework capabilities into the core.

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optimize your website with these five everyday seo tasks
Optimize your Website with these Five everyday SEO Tasks

Time is money. What if you lack both? 

Small business owners deal with a lot of work and don’t have the resources to hire someone to do these tasks. Secondly, they are usually on a very tight budget. Therefore, hiring someone only for SEO purposes or spending much time on SEO is practically impossible. Yet it is naive to ignore SEO. No business can be successful without SEO. So how can you deal with the situation effectively? The answer is simple.
You have to take baby steps but on a regular basis. Here we will discuss some small yet highly effective things you can do to keep the SEO of your business up to the mark.

Long-Term SEO Strategy

Before we dig deep into our topic, let’s shed some light on the importance of a long-term SEO strategy. Although it sounds good to have a plan based on daily tasks, nothing can replace the value and impact of a well-placed long-term plan. Whether you use the services of a digital marketing agency or create a plan on your own. What matters is that you have a well-thought-out plan for your business. Through a long-term SEO strategy, you set goals, define keywords, optimize content, and build links. This helps you keep track of your website and measure the extent of success you are achieving.
Now let’s deep dive into the daily tasks that can improve the SEO of your website.

Keep Your Website Content Fresh

Content is king. We all have heard this time and again. Yet we cannot deny the value and impact of content on the performance of your website. Content is important to rank, will simply be an understatement. That’s why you must regularly add new content to your website or keep the existing content updated. Writing and publishing new content on a regular basis should be part of your strategy. It is not necessary to publish new content every day. You can do it according to your goals and objectives. The important point is to have a posting schedule that suits your business. It can be daily, weekly, or monthly. For example, when you publish new content every Friday, your audience will be looking forward to it each Friday. 

Another aspect is to update comments and reviews. When you reply to comments the content of your website stays fresh. Moreover, if you don’t reply to comments, your visitors will feel ignored. This will impact negatively your website.

Create a Proper Internal Linking structure

No one likes to get confused or get sidetracked. A good internal linking structure plays the role of the red carpet for Google and your visitors. At the start, internal linking may not seem important but as your website grows it is imperative to have a well-defined internal linking structure. 

One of the most important factors to look out for is orphaned content. Orphaned content is the content that doesn’t get any links from other posts or pages from the same website. These links can really impact the rankings of your website. Having pages or content that don’t link to any other useful information can actually affect you negatively rather than having a positive effect on your website.

Improve your Technical SEO

We understand that technical SEO requires expertise and time. You need a professional SEO for this purpose. Having said that, there are few technical tasks that need to be handled on an everyday basis and don’t require an expert.

The first one is to optimize your images. Having high-quality images on your website is a necessity, but you don’t want these images to hinder the performance of your website. The goal is to keep the size of your images as small as possible without compromising on quality. 

Another task is to look for duplicate content. Google doesn’t appreciate duplicate content of any kind. It is possible that there is some duplicate content on your website that you may be unaware of. You don’t need to look for duplicate content on daily basis, but keep it on our list of tasks.

Keep Track of your Site Maintenance

Anything working needs proper maintenance. The same goes for your website. If not daily, you must analyze your website on a weekly basis. Most of us will agree that it is better to clean daily rather than waiting for the house to become a total mess. The same principle applies to your website. Managing a bunch of pages will be much harder than managing a few ones. Some of the tasks that you need to carry out regularly are:

  • Make sure that all the pages are loading without any errors. If not then look for reasons behind and take steps to eradicate them.
  • Look out for the cannibalization of your content. When you have too many pages and upload content on regular basis it is possible that you have content that will compete against each other. 
  • Find pages that are irrelevant or unnecessary. Analyze all the pages and determine if there are any pages that are not useful anymore.
  • Check the speed of your website and make sure that it is above the optimum range. Compress images, reduce redirects, and reduce response time.

Stay Active on Social Media

No one can deny the importance of social media platforms today. A decade ago it may seem like a waste of time and money but not anymore. When you have a website it is almost mandatory that you have some presence on social media. Through social media, you can stay engaged with your audience. Being on social media doesn’t require much time or money. It is easy, fast, and effective. You can post blog posts, share images, news about events, and so on. This also allows you to interact with your audience at a personal level. You can deduce what they prefer, what they want, and what are the issues they face. You can leave comments on their profiles or reply to their questions. You can choose the platform that suits you the best. You have a lot of options like Facebook, Instagram, Snapchat, Twitter, LinkedIn, and Reddit. Whatever platform you choose, the important part is to utilize it to your advantage and use this information to improve the SEO of your website.

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7 Tips For Posting To Data Science Central

Posting to any kind of online site should be seamless, but seldom is. Like most community sites, Data Science Central has been optimized for certain types of articles, and posting to the site can always be a bit nerve-wracking, especially if you’re trying to do something beyond simple articles. The following post contains a few tips, techniques and recommendations to ensure both the greatest fidelity to what you produce and the greatest likelihood that your article will be featured.

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dsc weekly digest 19 april 2021
DSC Weekly Digest 19 April 2021
An old fashioned editor's desk with DSC logos

Become A Data Science Leader

Becoming A Data Society

Data has always been an integral part of computing, but it has only been in the last decade or so that we have reached a point of data ubiquity. What that means in practice comes down to a fundamental notion about what exactly data is.

Data isn’t really a “thing” per se. Rather, you can think of data as being the digitized artifact that a process produces as it changes state. It is not just a signal, but a signal with some attached semantics that describes what a thing has become. Human civilization has produced such signals for a long, long time, but in most cases, only the crudest of these signals were interpretable, usually at a significant cost.

Increasingly, however, everything around us has begun emitting state signals that can be encoded and transmitted clear across the planet. If the temperature in my house falls below 65 degrees, the thermostat not only acts by turning up the heat, but it also informs me that the house is too cold. Amazon informs me when a particular book I’ve been wanting to read comes out, but it also now tells me when the cost of that book falls below a certain threshold … and can even purchase the book on my behalf without me even being in the loop.

This is having a profound impact upon our society in ways we’re only just beginning to realize. One effect is that it provides a natural deflationary pressure on financial transactions even in the midst of the supply chain disruptions from the pandemic that would ordinarily be strongly inflationary. It is even mitigating those disruptions by providing a better idea about where alternatives can be found in real-time, a process that normally would be prohibitively complex.

We’re beginning to discover that data societies are mediated societies, where the mediation is less through human interaction and more through algorithms and gradient modeling (machine learning). The next decade will see refinements of this mediation, as the theoretical work being done today becomes embedded in self-modifying code that is able to reduce the friction of human interactions. This is what data scientists do, ultimately, and while there are advantages to this, there are also deep ethical and technical questions that need to be worked out as we draw the line about how much automated mediation is too much.

This is why we run Data Science Central, and why we are expanding its focus to consider the width and breadth of digital transformation in our society. Data Science Central is your community. It is a chance to learn from other practitioners, and a chance to communicate what you know to the data science community overall. I encourage you to submit original articles and to make your name known to the people that are going to be hiring in the coming year. As always let us know what you think.

In media res,
Kurt Cagle
Community Editor,
Data Science Central


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when it comes to kubernetes data mobility is the game changer
When it comes to Kubernetes, data mobility is the game changer

To repeat a commonly used adagetoday every company is a technology company. Regardless of whether you are making computer chips or paper pulp, you are using technology, software and IT infrastructure to bring your products to market. Essentially, your company’s digital systems have become a weapon of business to deliver differentiated products and services, making digital transformation an imperative in order to stay competitive.  

The transition from traditional IT to cloud IT plays a significant role in these digital transformation efforts as it enables efficient use of resources and reduces costs and complexity. But the reality is that for all the potential benefits that cloud adoption brings, for many companies it hasn’always delivered on its promise. Although the cloud has become the backbone of an organizations applications and systems, many organizations are discovering the shortcomings of a one-size-fits-all mindset toward cloud adoption. 

 

An enterprise centric approach to cloud 

The cloud has taken hold quickly. Only a decade ago, most enterprises were just beginning to scratch the surface of cloud adoption with sole focus on moving their applications to the public cloud. Many companies became single sourced on their cloud infrastructure and services.  

As requirements have become more complex, organizations are beginning to realize that a onesizefitsall and single provider approach is no longer sufficientEnterprises need the flexibility to leverage resources from the public clouds, private clouds, and edge data centers to make IT more effective, reduce costs, increase agility, navigate regulatory requirements and deliver better service to their customersThe increasing adoption of multicloud and hybrid cloud architectures for IT infrastructure is a recognition of this need. 

However, for an enterprise, the cloud continues to be defined in terms of the provider of the public cloud or the technology adopted by the enterprise for their private or hybrid cloud. What is needed is an enterprisecentric vision for the cloud, as the distributed elastic pool of IT resources across public cloud providers, private clouds, and edge data centers that the enterprise has access to, within which they have the freedom to run applications wherever and whenever they want. 

 

Kubernetes everywhere and the Enterprise Cloud 

Containerization and Kubernetes are key to realizing this vision of the cloud. Kubernetes allows enterprises to define and build a consistent softwaredefined IT environment tailored for their specific needs, one that can run across multiple infrastructure silos and providers in private cloud, public cloud, and edge data centers. 

Applications can run anywhere the Kubernetesbased IT environment is instantiated and applications no longer need to be tailored to run on a given infrastructure or cloud.  Given this transformative capability, it’s no surprise that Kubernetes has quickly gained traction in the industry, with adoption increasing from 28 to 48% between 2018 and 2020 in enterprises, according to a survey by VMware.  

 

IT agility requires data mobility 

To realize the full potential of the cloud and have IT agility, application instances need to be mobile. Kubernetes and containers have made it easy to move application code between clouds and Kubernetes. But it has been much harder to make the underlying data mobile. A new approach is required – one that makes persistent volumes as mobile as application containers so that enterprises can fully benefit from their cloud investment.  

Container native storage solutions enable consistent data and storage management across infrastructure silos and cloud providers. This by itself isn’t sufficient to provide data mobility. Data migration and data replication technologies that are used today to copy or move persistent volumes between clouds and Kubernetes clusters are operationally complex and time-consuming. They require upfront planning and often require significant downtime. 

Whatneeded is a new capability that allows persistent volumes to be moved as quickly as application containers – instant data mobility. Since moving all application data within a short period of time is not feasible and since moving data sets between clouds can be expensive, data mobility must allow the application to start working immediately, prioritize hot data over cold data, and implement strategies to minimize the amount of data thats moved.    

The events of last year accelerated digital transformation and cloud adoption. The shift to Kubernetes and container-native storage simplifies IT. New capabilities in container storage solutions related to data mobility will allow enterprises to optimize their IT investments while maximizing effectiveness. This opens the door for innovation and creates a competitive advantage. It’s a whole new future.  

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risk management plan what is it and how to write
Risk Management Plan: What Is It and How To Write?

Planning is a path to success in business. Companies create a risk management strategy each time they begin a project because risks are an unavoidable part of any project. This document also aids in the identification of the gaps that may contribute to risk occurrence. Do you have a risk management plan for an upcoming project?

Risk is determined as a possible event that could cause damage. Risk management is a complex of measures, which enable the possibility to achieve successful results with consideration of all potential threats that may appear during the lifecycle of the project.

Before the project is implemented, it is necessary to create a team and develop a risk management plan. This document makes it possible to see the details, make timely adjustments, and revisions at different project implementation stages.

What Is A Risk Management Plan?

A risk management plan is a document describing approaches and principles of project risk management.

The risk management procedure of the project includes:

  • Risks identification;
  • Risks analysis and prioritization;
  • Development of measures for eliminating or minimizing the risk effects;
  • Risk monitoring and control.

If you want your piece of writing to look good, try using the services of Writing Judge.

How To Write A Risk Management Plan?

Even if you expect your project to go smoothly, it does not mean that everything will go the right way. It is up to humans and technique to make mistakes and fail. Hence, none of the businesses can avoid risks. Nonetheless, you can mitigate and anticipate them through an established risk management plan. Here are the steps you should take to write it:

Step 1. Risk identification and analysis

It involves the identification and analysis of the risks of your project. While some risks may be regarded as “known,” others might require a study to be discovered. To get well-researched information on a specific issue, you can visit Online Writers Rating to get high-quality, plagiarism-free products crafted by degreed professional writers.

Here are the main categories the risks fall to:

  • External;
  • Management;
  • Organizational;
  • Technical;
  • Logistics-related.

One should consider all of them to prepare a set of appropriate measures to respond to them.

Step 2. Assessment of the risk, its consequences, and effect

To prioritize project risks, one asks three questions:

  • What will happen if this situation takes place?
  • How likely is it that this will happen?
  • How bad will the resulting impact be on the project?

This helps to see the risks likelihood and their quantitative impact. For deeper research on a specific type of risk, you can contact Best Writers Online, which has specialists to do investigations you do not have time to do.

Step 3. Risk response planning

Risk response planning entails removing a risk, reducing its impact on the project, and preventing its occurrence. Begin with the danger that has the highest priority. Examine it with your team and see whether you can solve it or format it so that it no longer poses a risk to the project.

Step 4. Assign the roles in a team to monitor risks

Once you have determined a range of risks for your project, you will need to allocate each team member a particular risk category. Each of them will be in charge of devising strategies for dealing with the risk as it arises. This way, you will be able to manage all of the threats you will face along the way at the same time.

Step 5. Triggers

Risks do not emerge without triggers, i.e. mechanisms that activate them. This step involves consideration of situations that may launch risks typical to your project.

Why Write A Risks Management Plan?

There are many advantages of writing a risk management plan:

  • Improved results. This allows the team to stick to the budget and achieve its objectives. Your projects become vulnerable and exposed to problems if you do not have well-defined risk management plans in place.
  • Timely prevention. Having a detailed strategy allows you to take proactive action to address future problems before they arise and reduce the likelihood of their occurrence. Timely prevention is a part of effective time management as you do not have to spend much time to treat the risk when it occurs.
  • General assessment of a project. It allows you to assess the progress of your current project and develop best practices for the future.

The risks occurrence is unavoidable in all kinds of projects. If you have a clearly defined risk management plan to guide you in this process, you can solve issues more effectively.

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how a data catalog enables data democratization
How a Data Catalog Enables Data Democratization

For many organizations, data is a business asset that’s owned by the IT department. Based on this ‘data ownership’ model, there’s limited access to data across the organization, and no transparency around what’s available internally.

Now, an increasing number of organizations are rushing to mandate organization-wide data strategies. But with the isolated data ownership model in place, how can organizations ensure that everyone who needs data can find it and use it? 

Although data scientists and analysts are the ones closest to data, all business units now need data (and data know-how) in order to achieve digital transformation goals. That means data access and sharing needs to be a priority.

The 2021 New Vantage Partners Big Data and AI Executive Survey reports that more than three quarters of these executives said they haven’t created a data culture. Furthermore, only about 40% said they are treating data as a business asset and that their enterprises are competing on data and analytics.

It’s clear that data is top of mind for most companies, but it’s still a separate idea rather than the foundation of every decision. Across business units, and even within individual departments, there are still barriers, silos, and isolated workflows that slow progress. To drive a data-first culture, data has to be the central point that every department and decision can be built on – and that’s achievable through data democratization. 

What is data democratization?

Data democratization makes data accessible within your organization so that everyone, not just your IT department, has access to data. Bernard Marr, bestselling author of “Big Data in Practice,” puts it clearly: “It means that everybody has access to data and there are no gatekeepers that create a bottleneck at the gateway to the data. The goal is to have anybody use data at any time to make decisions with no barriers to access or understanding.”

Data democratization lays the roadways for people to find, understand, and use data within their organization to make data-driven decisions.


The internal resistance against data sharing

Data is a commodity that can unlock new opportunities, so it makes sense that better access means better results. However, there’s a lot of data that contains sensitive information, meaning that easier access to the data breeds security risks. This threat has led to all data being treated more or less the same way – closed by default, access being granted on a case-by-case, need-to-have basis.

This does make sense; data privacy should be a priority. But often, useful data that should be more available gets lumped in with sensitive information. In fact, Forrester reported that within enterprise companies, 73% of data still goes unused. Where else in your business would you be okay running at 27% capacity?

Another obstacle in the way of data democracy is the assumption that data isn’t used the same way, so it therefore can’t be shared. Every department uses data for different purposes, so it makes some sense to assume it can’t be shared among business units. That leads to the same data being purchased in several different places, or duplicative work in building connectors and data prep & cleansing. Either way, you’re probably spending money on the same problem more than once.

For example, we can assume that every division of a given bank tracks economic indicators. But without wider data asset visibility, every division manages that data separately. This means multiple purchases of the same data, redundant work, lower efficiency, and an erosion of your bottom line.

There are a lot of tools that will transform, warehouse, ingest, or present data – all of the things you need to do, right? But no matter the toolset, if there’s no cultural alignment among data initiatives, there’s no chance of reaping the full reward. Cost savings, new revenue, and improved decision-making truly take off when data is considered as part of the design and process, not a separate, black-box add-on. 


How a data catalog enables data democratization

The first step towards data democratization is to break down data silos. That sounds like a tall order, but the right tools can help.

data catalog is a popular solution, as it allows organizations to centralize their data, then find, manage, and monitor data assets from one single point of access. Gartner reported that organizations with a curated catalog of internally and externally prepared data will realize double the business value coming from analytics investments this year.

Key advantages to data catalogs are that they allow users to discover all the data your organization has access to, no matter the source or which department acquired it, but under strict governance rules. Additionally, they can also offer data virtualization capabilities so that users can retrieve data without moving it from its existing warehouse. This is a major advantage for data privacy and residency requirements.

There’s a variety of data catalog solutions available in the market. Ensure the solution you choose provides a foundation for data governance and data sharing. By 2023, organizations promoting data sharing will outperform their peers on most business value metrics.


How ThinkData enables data democratization

ThinkData’s catalog solution offers visibility and governance of any data assets from any source. Once data is accessible from a centralized location, you need to think about how your organization will be able to share and connect to data with integrity.

Since the GDPR was launched in 2018, over €274M (over $350M) in fines have been passed down – and 92% of these fines were the result of insufficient legal basis for data processing and security. The ThinkData catalog is built to help you comply with GPDR, CCPA, and other regulatory requirements. What’s more, the platform is flexible enough to adapt to changing market conditions. 

We surveyed data science experts in our ThinkData State of Data 2021. What we found is that 86% of data scientists name role-based access control an important or very important feature when managing datasets. The ThinkData catalog enables effective data management through role-based access control and data forensics activities. Using Namara, users can grant or restrict data access; track datasets across updates; and audit data access, dataset health and more.

We also offer a seamless connection to the world’s largest repository of open, public, and partner data on our Data Marketplace. This provides access to trusted, product-ready datasets and increases speed of discovery, shortens time to insights, and bolsters data confidence (note: if you want to offer data on our Marketplace, send us a message).

Forging a data culture isn’t easy. The right training and executive support need to be in place across your business functions, not just your technical teams. That common goal and framework will foster cultural alignment in centring operations around a data catalog.

Data should be used by more and more people, not just data scientists, and most companies are working towards this goal. But if there’s a cultural mismatch between tools and training, it will be an uphill battle trying to meet your goals. We offer introductory data governance assessments that will help you discover the blind-spots in your current strategy. 

Democratizing data internally improves data access, reduces overhead costs, and promotes confidence and consistency. In an incredibly unpredictable environment, it’s no surprise that organizations are racing to implement a data-first approach to safeguard and optimize their operations. Promoting intra-organizational transparency will enrich your company’s understanding, capabilities, and resilience, and it’s never been more important.

Do you think your business has a need for a data catalog to find, understand, and use trusted data to drive business outcomes? Please reach out.



Originally published at https://blog.thinkdataworks.com.

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finger on the pulse using ai to turn blurry images into hi res cgi faces
Finger On The PULSE: Using AI To Turn Blurry Images Into Hi-Res CGI Faces

For all the photographers out there who haven’t mastered the art of the steady hand: this one’s for you. Researchers at Duke University in North Carolina have applied an AI-based solution to touching up blurry photographs, creating a program capable of touching up blurry faces into an image sixty times sharper. It’s not going to turn you into an artist, but it could work wonder on your holiday snaps!

The Duke team’s system is called PULSE, standing for Photo Upsampling via Latent Space Exploration. The system creates entirely new high-resolution computer-generated images based on the blurry sample photograph, and then scours then scales the new images down, working backwards to finding the closest matches to the original low-res sample.

PULSE is actually made up of two neural networks, a machine learning tool called a GAN, or a generative adversarial network. When combined, these two networks produce lifelike high-resolution output images. The first AI generates new human faces, initially using its own programming but learning from feedback from the second network to improve its processes. The second network analyses the output images to “decide” if they’re convincing enough, feeding its analysis back into the first network to improve the process.

Traditional upscaling tools have assumed that there’s one true upscaled image based on any low-resolution (LR) input and have then worked linearly to add detail to an input image, slowly improving its resolution. But this assumption about a “true image” requires the program to smooth out any details that it can’t guess at. Typically, the image produced is around eight times sharper than its original, but details such as wrinkles, hairs and pores are absent, as the computer doesn’t want to guess at them. Output images suffer from a lack of texture, and look uncanny, like a too thoroughly airbrushed model – somewhere between human and CGI.

PULSE throws this assumption out the window, as any LR image could actually have hundreds of corresponding high-resolution outputs. By recognizing this, says Larry Gomez, a business writer at Revieweal and Assignment Help, “the team that worked on PULSE knew they could produce a vastly sharper image, where no details are smoothed out. The generative adversarial network works backwards, producing images and then shrinking them to see if they closely match the input image, all the while reappraising its process through machine learning to get better at both the image production process and the matching process.”

(PULSE Authors Example)

When the results from PULSE were tested against the images generated from other models, the PULSE images scored the best, approaching the scores given to real hi-res photographs. The algorithm can take an image of just 16×16 pixels and produce a realistic output image of 1024×1024 pixels. Even images where features are barely recognizable, eyes or mouths reduced to single pixels, can be used to produce life-like outputs.

The team at Duke focused on images of faces, but this was just a proof of concept for PULSE. “In theory, the process can be applied to blurry images of anything. This could have practical applications beyond your family photo album, in disciplines such as medicine and astronomy where blurry images are the norm. Sharp, realistic images could be generated to help us guess at what we’re looking at, whether that’s in the human body or deep space,” says Julia McAdams, a marketer at Coursework help service and State Of Writing.

One thing the team are keen to emphasize that PULSE can’t do is upgrade existing blurred images – say, blurred out photographs to protect individuals’ identities – and produce the original image. The output images produced by PULSE are computer generated – they look plausibly real, but aren’t actually images of anyone who exists. This dystopian model for unmasking protected identities doesn’t exist: indeed, the PULSE team say it’s impossible.

The power of AI and machine learning continues to be harnessed to create self-learning algorithms with impressive power to produce lifelike results. PULSE’s upscale tool is only one possible application of generative adversarial networks. It has been used in other areas to have algorithms produce their own video games. Smart algorithms will be infiltrating all walks of life in a few years, with impressive results.

Lauren Groff is a writer and editor at Lia Help and Big Assignments with a passion for AI and computer science. More of her writing can be found at Top essay writing services blog.

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a guide to amazon web services aws scalable secure cloud services
A Guide to Amazon Web Services (AWS) – Scalable & Secure Cloud Services

So even before we put forward and present a case for AWS, why it should be used and most importantly the staggering benefits that come along, it is important to take a stock of who all are using it ?

Well from start-ups to mid-size companies to industry leaders such as Netflix, Facebook and LinkedIn, AWS has captivated one & all!

So what exactly is AWS?

AWS is the most advanced, widely used & comprehensive suite that offers the best in class services than any other provider as a cloud platform.

AWS presents several solutions, tailor-made to meet particular requirements and facilitates exponential growth for businesses whilst being a cost effective managed service provider.

How to scale up to cloud?

Amazon web services can significantly reduce costs and also save organisations from redundant and dated infrastructure and operating models. By constituting a well thought-out DevOps approach, most organisation can look to scale and be more efficient, both in terms of cost and time.

To break it into 3 easy & actionable steps:

Step 1 – Do away with inefficient practices where dev teams have inter-dependencies with Ops teams and most builds take a large amount of time.

Step 2 – Setting up of the right DevOps process, which also leads to reduction in manpower as most processes are not only automated but run directly via API calls from cloud.

Step 3 – Once the DevOps have been executed meticulously, AWS which is the cloud service provider comes in the as the virtual infrastructure, removing issues of latency, time, high over-head costs and most importantly inefficiencies in delivering a seamless offering to the end user with practically zero intervention in terms of managing either the hardware or be worried of downtime and system performance.

Amazon web services that can power your growth:

 

Complete Guide to Amazon Web Services

Amazon EC2

It facilitates developers to build apps and to automate scaling as per peak periods, making it far more efficient to handle storage, look after virtual servers and reducing the dependency on traditional hardware.

Amazon S3

It is designed for storage and retrieval of large chunks of data for mobile app and web apps. Being extremely economical, scalable, secure and manageable, S3 is the desired and preferred option for most developers who are building apps that can be accessed by users globally.

Amazon VPC

It forms the core of AWS services. Essentially, it facilitates the connectivity of several on-premise resources to a private network that is hosted virtually. Custom VPC and the ability to peer your own VPC with another are all possibilities that can be successfully explored.

Amazon Lightsail

For early starters, AWS Lightsail is a recommended option. A vast majority of app developers get an easy and customisable access to a private server. Lightsail offers a secure static IP and a storage of upto 80GB. Simply put it also acts as an easy to handle load balancer.

Amazon Route 53

An in-demand service, helps connect the world wide traffic to several servers that are hosting the desired or requested web application. It is a new age mechanism aimed at traffic routing that is both scalable and secure.

Amazon Load Balancing

Elastic load balancing is all about distributing in coming traffic requests within a single or multiple servers, automatically taking care of the increase in traffic/demand and closely monitors the health of in-coming requests and directs them to the most appropriate instances. Nodes of various capabilities can also be configured alongside the load balancer to efficiently manage the in-coming data requests.

Amazon Auto Scaling

It is usually interconnected with load balancing, as the cloud monitoring details along with the utilisation of CPU’s will help determine the auto scaling operations. Autoscaling dynamically increases or decreases the capabilities of the virtual servers, thereby eliminating the need for manual intervention.

Amazon CloudFront

It is essentially a CDN and greatly minimises the cost incurred in retrieving the data as it first looks up its own cache, if found, it starts to share the same with the user who has requested for the same and does not always send across a hot to server or the bucket that is hosting the data, in the process saves on time & cost.

Amazon RDS

It is actually not a database but a cloud solution that takes care of several tasks such as DB, patching, recovery and maintenance. It also supports most of the popularly available relational databases solutions.

Amazon IAM

It empowers the user to manage and define the level of access to AWS. It enables creation of several users, all having their own credentials and connected to a single AWS account. Multifactor authentication and ease of integration with other AWS services are the key standout features.

Amazon WAF

It is an application level firewall offering. So rather than setting up separate firewall servers, this can be setup straight from the AWS console, saving time and providing the much needed protection from DDoS attacks and SQL injections.

Amazon CodeBuild, CodeDeploy, CodePipeline and CodeCommit

CodeBuild is a secure and scalable offering for compiling and testing a codebase. CodeDeploy helps to deploy the code via cloud anywhere. CodePipeline is for swift continuous integration & delivery. CodeCommit is a service that facilitates smooth integration with industry standards such as Git.

Amazon SES, SQS, SNS and Cloudwatch

These are managed & scalable message queue and topic services that provide easily implementable APIs. Amazon SNS and Amazon CloudWatch are usually integrated in order to provide easy to collect, view, and analyse metrics for every active SNS notification.

Amazon AMI

It is a virtual image that is used to create a virtual instance within EC2. Multiple instances can be created using single or multiple AMI with either same or different configuration.

Terraform

It is an open source cloud agnostic solution that seamlessly integrate a multi cloud scenario into a single workflow. It can handle infrastructure changes across public and private cloud, thus making it a multipurpose tool.

Reasons why you should opt for AWS:

Firstly, it is most economical and hassle free solution that pretty much takes care of all your backend infra requirements and allows you to scale without having to worry about security. Additionally, it reduced the cost to manage with cutting down on manpower cost.

Secondly, all major services come with auto scale options allowing you to upgrade basis case-on-case requirements.

Thirdly it is one of the most safest and fastest solution out there that can power your mobile and web apps.

Last and by no means the least, you only pay if you use. Thus if few services are dormant there are zero over-head charges, majorly in data storage and retrieval.

At Orion we have a coterie of dedicated professionals who have extensive experience in formulation, managing and executing the above as a managed service provider so that your business can grow at an exponential pace. To know how we can help or discuss a peculiar scenario that you have in mind, write to us at – info@orionesolutions.com

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a complete guide to amazon web services aws scalable secure cloud services
A Complete Guide to Amazon Web Services (AWS) – Scalable & Secure Cloud Services

So even before we put forward and present a case for AWS, why it should be used and most importantly the staggering benefits that come along, it is important to take a stock of who all are using it ?

Well from start-ups to mid-size companies to industry leaders such as Netflix, Facebook and LinkedIn, AWS has captivated one & all!

So what exactly is AWS?

AWS is the most advanced, widely used & comprehensive suite that offers the best in class services than any other provider as a cloud platform.

AWS presents several solutions, tailor-made to meet particular requirements and facilitates exponential growth for businesses whilst being a cost effective managed service provider.

How to scale up to cloud?

Amazon web services can significantly reduce costs and also save organisations from redundant and dated infrastructure and operating models. By constituting a well thought-out DevOps approach, most organisation can look to scale and be more efficient, both in terms of cost and time.

To break it into 3 easy & actionable steps:

Step 1 – Do away with inefficient practices where dev teams have inter-dependencies with Ops teams and most builds take a large amount of time.

Step 2 – Setting up of the right DevOps process, which also leads to reduction in manpower as most processes are not only automated but run directly via API calls from cloud.

Step 3 – Once the DevOps have been executed meticulously, AWS which is the cloud service provider comes in the as the virtual infrastructure, removing issues of latency, time, high over-head costs and most importantly inefficiencies in delivering a seamless offering to the end user with practically zero intervention in terms of managing either the hardware or be worried of downtime and system performance.

Amazon web services that can power your growth:

 

Complete Guide to Amazon Web Services

Amazon EC2

It facilitates developers to build apps and to automate scaling as per peak periods, making it far more efficient to handle storage, look after virtual servers and reducing the dependency on traditional hardware.

Amazon S3

It is designed for storage and retrieval of large chunks of data for mobile app and web apps. Being extremely economical, scalable, secure and manageable, S3 is the desired and preferred option for most developers who are building apps that can be accessed by users globally.

Amazon VPC

It forms the core of AWS services. Essentially, it facilitates the connectivity of several on-premise resources to a private network that is hosted virtually. Custom VPC and the ability to peer your own VPC with another are all possibilities that can be successfully explored.

Amazon Lightsail

For early starters, AWS Lightsail is a recommended option. A vast majority of app developers get an easy and customisable access to a private server. Lightsail offers a secure static IP and a storage of upto 80GB. Simply put it also acts as an easy to handle load balancer.

Amazon Route 53

An in-demand service, helps connect the world wide traffic to several servers that are hosting the desired or requested web application. It is a new age mechanism aimed at traffic routing that is both scalable and secure.

Amazon Load Balancing

Elastic load balancing is all about distributing in coming traffic requests within a single or multiple servers, automatically taking care of the increase in traffic/demand and closely monitors the health of in-coming requests and directs them to the most appropriate instances. Nodes of various capabilities can also be configured alongside the load balancer to efficiently manage the in-coming data requests.

Amazon Auto Scaling

It is usually interconnected with load balancing, as the cloud monitoring details along with the utilisation of CPU’s will help determine the auto scaling operations. Autoscaling dynamically increases or decreases the capabilities of the virtual servers, thereby eliminating the need for manual intervention.

Amazon CloudFront

It is essentially a CDN and greatly minimises the cost incurred in retrieving the data as it first looks up its own cache, if found, it starts to share the same with the user who has requested for the same and does not always send across a hot to server or the bucket that is hosting the data, in the process saves on time & cost.

Amazon RDS

It is actually not a database but a cloud solution that takes care of several tasks such as DB, patching, recovery and maintenance. It also supports most of the popularly available relational databases solutions.

Amazon IAM

It empowers the user to manage and define the level of access to AWS. It enables creation of several users, all having their own credentials and connected to a single AWS account. Multifactor authentication and ease of integration with other AWS services are the key standout features.

Amazon WAF

It is an application level firewall offering. So rather than setting up separate firewall servers, this can be setup straight from the AWS console, saving time and providing the much needed protection from DDoS attacks and SQL injections.

Amazon CodeBuild, CodeDeploy, CodePipeline and CodeCommit

CodeBuild is a secure and scalable offering for compiling and testing a codebase. CodeDeploy helps to deploy the code via cloud anywhere. CodePipeline is for swift continuous integration & delivery. CodeCommit is a service that facilitates smooth integration with industry standards such as Git.

Amazon SES, SQS, SNS and Cloudwatch

These are managed & scalable message queue and topic services that provide easily implementable APIs. Amazon SNS and Amazon CloudWatch are usually integrated in order to provide easy to collect, view, and analyse metrics for every active SNS notification.

Amazon AMI

It is a virtual image that is used to create a virtual instance within EC2. Multiple instances can be created using single or multiple AMI with either same or different configuration.

Terraform

It is an open source cloud agnostic solution that seamlessly integrate a multi cloud scenario into a single workflow. It can handle infrastructure changes across public and private cloud, thus making it a multipurpose tool.

Reasons why you should opt for AWS:

Firstly, it is most economical and hassle free solution that pretty much takes care of all your backend infra requirements and allows you to scale without having to worry about security. Additionally, it reduced the cost to manage with cutting down on manpower cost.

Secondly, all major services come with auto scale options allowing you to upgrade basis case-on-case requirements.

Thirdly it is one of the most safest and fastest solution out there that can power your mobile and web apps.

Last and by no means the least, you only pay if you use. Thus if few services are dormant there are zero over-head charges, majorly in data storage and retrieval.

At Orion we have a coterie of dedicated professionals who have extensive experience in formulation, managing and executing the above as a managed service provider so that your business can grow at an exponential pace. To know how we can help or discuss a peculiar scenario that you have in mind, write to us at – info@orionesolutions.com

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