Top Open-source Data Visualization Tools

Data Visualization is a method of presenting data in a visual format. The pictorials and graphs help decision-makers comprehend information. Data visualization recognizes patterns, concepts, and trends in large data sets. Data visualization is a process that helps businesses of all sizes and industries.Visualization

Open Source Data Visualization tools have tremendously impacted the corporate world. In this article, we will learn about various open-source data visualization tools.

Here are a few benefits of businesses using free and open-source Data Visualization tools:

  • Open Source Data Visualization tools would help in decision making. It will fulfill tasks such as presenting data patterns, correlations, and trends using graphic elements.
  • There are multiple ranges of tools available. Each with features and functions to support user objectives.
  • The tools ensure data accuracy and protect vital information. The tools are said to collaborate with security solutions to maintain data security.
  • The tools alert and notify users about the completion of tasks. They also send out notifications in case a task is missed.
  • The tools comprehend data and provide suggestions to improve business performance.
  • The tools help small businesses by reducing costs as they are free and open source.

Open-Source Data Visualization Tools and their Key Features:

Tableau Public

Tableau Public is a free and open-sourced data visualization tool. It is a platform that allows users to freely share and explore data visualizations publicly.

They provide Data Visualization or “vizzes” as they call them, to help users comprehend data under any public topic.

Key Features:

  • It allows users to share visualized data publicly.
  • It provides over 3 million interactive data visualizations created by 1 million global users.
  • It is a fully hosted tool that can manage millions of viewers and infrastructure.

Google Charts

Google Charts is a simple and free data visualization tool. It is a cloud-based tool that provides a library of data charts.

It provides multiple default charts but also allows limitless customization. It connects users in an online Google Charts forum where they support one another to create visualized data.

Key Features:

  • It allows users to access charts and data tools from any web-browser without plug-ins.
  • It allows users to create multiple dashboards and also helps match the chart colors as per the website or business.
  • It manages the content on the charts and connects real-time data using data connection and protocol tools.

Leaflet

Leaflet is an open-source JavaScript library. It enables users to create mobile-friendly interactive maps.

Developers use the variety of mapping features already embedded in the tool.

Key Features:

  • It is a simple and lightweight tool with a size of only 38 kb of JavaScript.
  • It provides multiple plugins to add features and customizations.
  • It works well on mobile and desktop platforms.
  • It offers visual, user interaction, and performance features zoom, drag panning inertia, keyboard navigation, hardware acceleration, etc.
  • It provides mapping controls like zoom buttons, attribution, layer switcher, and scale.

D3.js

D3.js is a JavaScript library that develops and manipulates documents based on data. D3 stands for Data-Driven Documents that manipulate Data Object Model (DOM).

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Key Features:

  • It visualizes data for users with HTML, SVG, and CSS.
  • It uses the full capacity of a browser to develop visualizations without tying to a proprietary framework.
  • It connects users to a DOM and applies data-driven manipulations to documents.

Plotly

Plotly is an open-sourced browser-based data visualization tool. It is an interactive solution built on d3.js visualization libraries.

Key Features:

  • It allows users to create d3.js visualizations by simply uploading excel files or connecting the SQL database.
  • It enables users to work with R or Python to create charts.
  • Comparing datasets becomes easier with its multi-chart visualization.
  • It creates and displays complex charts on dashboards and websites.
  • It allows users to collaborate and share data with different teams and members.

Charted

Charted is a free and open-source tool that automatically visualizes data. The Product Science at Medium created the tool in 2013.

It focuses only on visualization and does not transform format or store data.

Key Features:

  • It only requires a CSV file or Google Sheets link to create visualizations.
  • It analyzes and displays discoveries with the data science team.
  • The tool comes with integrated components that help with visualizations.
  • It also supports tab-delimited files and Dropbox links and requires no training for users.

Datawrapper

Datawrapper is an open-sourced tool that is mobile-friendly. It provides users with simple, accurate, and embeddable visualizations within minutes.

The tool was created by a team of 15 developers in 2011. It is vastly used by journalists although it is comprehensive enough for data scientists and researchers.

Key Features:

  • It provides free and paid versions for users.
  • It provides interactive charts for viewers to comprehend underlying values.
  • It helps create charts and reports within minutes.

Polymaps

Polymaps is an open-source JavaScript library. It creates dynamic and interactive maps in modern web browsers.

It is another tool to use SVG functionality that facilitates styling through CSS which enables interactivity.

Key Features:

  • It displays multi-zoom datasets over maps for users.
  • It leverages SVG to display and uses CSS to enable users to define the design.
  • It loads a full range of data to showcase information from the country level to states, cities, neighborhoods, and individual streets.

Candela

Candela is an open-source web-visualization tool from Kitware’s Resonant platform. It is a full suite of interoperable data visualization components.

It focuses on creating rich and scalable visualizations. Its API is used in real-world data science applications.

Key Features:

  • It creates rich and scalable visualizations for users.
  • It provides a normalized API to apply in real-world data science scenarios.
  • It enables installation through standard package repositories systems or from a source.

Dygraphs

Dygraphs is a flexible open-source JavaScript charting library. It enables users to explore and understand complex data sets.

Key Features:

  • Its primary feature includes handling heavy data sets and plotting millions of data points without getting bogged down.
  • It displays strong support for error bars and confidence intervals.
  • It is a customizable tool and this flexibility allows it to work well with all browsers.

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RAWGraphs

RAWGraphs is an open-source data visualization platform. The tagline on the website states “missing link between spreadsheets and data visualizations”.

The user can simply cut/paste data, upload, or provide a link for the data sets to access a variety of charts.

Key Features:

  • It provides users with multiple unconventional visualization models.
  • It is built on the D3.js library and is designed for technical as well as non-technical users.
  • It builds links between spreadsheets and vector graphics editors.
  • It is a web-based platform and handles data through browsers.

OpenHeatMap

OpenHeatMap is a basic online mapping tool. It enables users to upload csv, excel or Google Sheets files to create maps.

It uses data to build static or animated maps. It enables users to view the data in different locations and visualize changes.

Key Features:

  • Developers can use the tool to access mapping functionalities of their own website.
  • It helps users to communicate through interactive maps that may be static or animated.
  • It provides customer demographics data according to zip codes.

Palladio

Palladio is a free web-based tool that visualizes complex, historical and multidimensional data. It allows users to visualize data from CSV, TAB, and/or TSV files.

It is a product created in Stanford University’s Networks in History.

Key Features:

  • Its graph view enables users to visualize relationships between data dimensions.
  • Its list view feature helps users arrange the data in customized lists.
  • It easily visualizes complex historical data.

Databox

Databox is a cloud-based business data dashboard tool. Users can easily connect a data source and choose attributes to be auto-populated in the dashboard.

Key Features:

  • It collaborates with data sources like HubSpot CRM, Google Analytics, Instagram, and Facebook Ads.
  • It has a DIY Dashboard creator that allows users to choose from multiple templates and design dashboards without a designer or a coder.
  • Its key performance indicator scorecards, advanced data modeling, and goal tracking allow data analysts to predict business performance.

Mode

Mode is a free, interactive, and cloud-based platform. It analyzes complex datasets and provides reports.

It is a browser-based data visualization tool that streamlines data for users.

Key Features:

  • It provides a top-level and analytical workflow for users.
  • It provides a unique URL to each project which makes it easier to share the links among teams and members.
  • It works with servers like Microsoft Azure SQL, Amazon Redshift, Oracle, MySQL, SQL, etc.
  • It provides free courses for users to learn online.

Conclusion:

Open Source Data Visualization tools are an important aspect of data analytics. Businesses that use data visualization tools leverage actionable information from the analyzed data.

The changing weather of cloud infrastructure

The pandemic has highlighted how integral technology infrastructure is to help us work, shop and interact with each other. As more of our critical infrastructure and services become dependent on software hosted in the cloud, outages are more than just an inconvenience.

But many businesses are playing a risky game with their cloud providers. They often use one main provider, located in a small number of places around the world – meaning if downtime occurs, they are left high and dry. On top of this, there are various data sovereignty and privacy concerns associated with using one sole provider across borders.

infrastructure

In this piece we’ll explore the changing weather of cloud infrastructure, including the rise of local providers, the increasing data sovereignty complications, and how diversifying to a multi-cloud approach can help businesses address these challenges.

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Local cloud options

When choosing a cloud provider, large organisations are often drawn to using one of the ‘big five’ suppliers. Of these, four of the five (Amazon, Microsoft, Google and IBM) are American.

With the US having recently passed the CLOUD act, which has provisions that enable the US government to demand access to data stored by American companies overseas, many companies that handle sensitive information are concerned about the privacy aspect of storing their data with these US-based companies.

Businesses are therefore considering building their online presence across providers within each jurisdiction they operate in. By seeking local market providers who provide cloud-based durability, cost-effectiveness and ease-of-use, they can rest assured that they are operating within the legal framework of each country they are established in.

These local options are expected to increase over the next few years, given moves to promote competition, such as the EU’s recent ruling that countries should be encouraging local providers over the large US-based cloud vendors.

Data sovereignty complications across borders

Organizations who operate across several different countries are also impacted by a global web of data protection and residency legislation, which applies to the user data they hold, yet most companies are not even thinking about it.

This is because current national and international legislation around tax, data protection and privacy are not compatible with one another, which makes dealing with data and transactions ethically a quagmire.

There is a definitive need for a simplification of digital tax and data policy within major trading blocks. For example, although GDPR is a block-wide requirement in the EU, handling VAT on transactions is done on a nation-by-nation basis and needs to be managed independently for each country that gets serviced. This is incredibly complicated for a market that is increasingly dominated by digital transactions.

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Addressing these challenges

Over the next few years, and in absence of a universal simplification, the challenge for many global companies will be to ensure they are compliant to the increasing amounts of data protection legislations, which seek to regulate how they use and store data across countries.

This challenge, combined with a much larger public awareness of data privacy and consumer’s rights, means that organisations immediately need to be transparent about their use of data and who it can be accessed by.

To do this, awareness and protection are the first line of defence and, as well as getting an experienced lawyer to draft your company’s privacy policies, a risk assessment should be undertaken to determine potential exposure.

With increasingly aware customers, businesses should be especially aware of the possibility of receiving Freedom of Information Act (FOIA) requests from the public who want to know how their data is being used. To prepare, businesses should ensure they have systems in place to handle the formal processing of these requests.

Most importantly, in a time when the vaults of data businesses own and use are getting larger and more complex, companies need to ensure they’re compliant and avoid making mistakes. From marketing lists, to customer mailing lists and ad-hoc visitor lists, organizations need to clearly think through how they are working with people’s data and keep track of it.

Building a multi-cloud approach

To help address these challenges, business leaders should consider building their applications across a range of providers within their own borders in order to mitigate their risk around compliance.

For businesses, doing this also means that they can access data centres in areas which are not provided by the primary cloud provider and manage costs and resources more effectively by taking advantage of reduced prices or specialized offerings which are not available with large vendors.

A key consideration when looking at moving to a multi-cloud approach is the role of API management.

As moving data tends to rely heavily on APIs, supporting a multi-cloud strategy requires evaluating your API management approach – this includes finding an API management solution that is capable of working in a multi-cloud, multi-region configuration, while ideally providing a centralised view.

With countries around the world beginning to build their own internal cloud infrastructure and with the increasing demand for domestic data storage solutions, the future for businesses is multi-cloud.

Although the temptation may be to simply think short-term amid the pandemic, true business leaders will be focused on building for the future. Along with enabling remote working, this means investing in improving agility and efficiency. Considering a multi-cloud strategy, with all the flexibility, cost benefits and competitive advantages it offers, will help them to do that.

What’s Your Route to Enterprise AI Adoption?

Artificial intelligence (AI) is currently an inherent piece of our everyday lives. We don’t consider anything but seeing personalized product recommendations on Amazon or optimized real-time directions on Google Maps. The day isn’t far when we will have the option to bring driverless vehicles to take us home, where Alexa would have just arranged dinner subsequent to checking stock with our smart oven and fridge. That being stated, enterprise adoption of AI has been increasingly estimated however, it is advancing quickly to achieve tasks extending from planning, anticipating, and predictive maintenance to customer service chatbots and the like.

Understanding the province of Artificial Intelligence deployment, how comprehensively it is being utilized, and in what ways it is challenging for some business chiefs. AI and different innovations are progressing altogether quicker than many foreseen only a couple of years ago. The pace of development is accelerating and can be difficult to grasp.

AI

KPMG 2019 Enterprise Artificial Intelligence Adoption Study is conducted to pick up understanding into the province of AI and automation deployment efforts to select huge top organizations. This is associated with in-depth interviews with senior pioneers at 30 of the world’s biggest organizations, as well as secondary research on work postings and media coverage. These 30 exceptionally powerful out of Global 500 organizations represent noteworthy worldwide economic value, on the whole, they utilize roughly 6.2 million individuals, with total incomes of US$3 trillion. Together, they additionally represent a noteworthy part of the AI market.

Almost all the employees so surveyed consider Artificial Intelligence to be playing a job in making new champs and losers. Artificial intelligence has wide enterprise applications and the possibility to move the competitive position of a business. The advances under the AI umbrella are as of now adding to product and service upgrades and they will be significant drivers of innovation for completely new products, services, and business models.

O’Reilly survey results show that AI efforts are developing from prototype to production, however, organization support and an AI/ML skills gap remain snags.

5 Reasons to Develop AI Systems In-House

1: The Best Core Technologies Are Open-source Anyway

The academic origins of open-source GPU-accelerated machine learning frameworks and libraries over the last ten years have made it all but impossible for well-funded tech giants to cloister promising new AI technologies into patent-locked, proprietary systems.

This is partly because nearly all the seminal contributing work has been the result of international collaborations involving some mix of academic research bodies and government or commercial institutions, and because of the permissive licensing that facilitated this level of global cooperation.

With occasional exceptions for the military sector and parts of Asia, state-funded research is publicly accountable by necessity, while commercial attempts to take promising code into private branches would starve them, fatally, of ongoing community insight and development.

Ultimately all the major tech players were forced to join the open-source AI Eco structure in the hope that some other differentiating factor, such as Microsoft’s business market capture, Amazon’s gargantuan consumer reach, or Google’s growing data mountains could later reap unique corporate benefits.

This unprecedented level of transparency and open technology gifts any private commercial project with free world-class machine learning libraries and frameworks, all not only adopted and well-funded (though not owned) by major tech players, but also proofed against subsequent revisionist licensing.

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2: Protecting Corporate IP

Most in-house AI projects have a more fragile angle on success than the FAANG companies, such as a patentable use-case concept or the leveraging of internal consumer data — instances where the AI stack configuration and development is a mere deployment consideration rather than a value proposition in itself.

In order to avoid encroachment, it may be necessary to tokenize transactions that take place through cloud infrastructure, but keep local control of the central transaction engine.

Where client-side latency is a concern, one can also deploy opaque but functional algorithms derived from machine learning methods, rather than trusting the entirety of the system to the cloud, and encrypt or tokenize data returns for local analysis.

Such hybrid approaches have become increasingly common in the face of growing breach reports and hacking scandals over the last ten years.

3: Keeping Control of Data Governance and Compliance

The specificity of the input data for machine learning models is so lost in the training process that concerns around governance and management of the source training data might seem irrelevant, and shortcuts tempting.

However, controversial algorithm output can result in a clear inference of bias, and in embarrassingly public audits of the unprocessed training source data and the methodologies used.

In-house systems are more easily able to contain such anomalies once identified. This approach ensures that any such roadblocks in machine learning development neither overstep the terms and conditions of the cloud AI providers nor risk infringing the lattice of varying location-specific privacy and governance legislation that must be considered when deploying cloud-based AI processing systems.

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4: AIaaS Can Be Used for Rapid Prototyping

The tension between in-house enterprise AI and cloud-based or outsourced AI development is not a zero-sum game. The diffusion of open-source libraries and frameworks into the most popular high-volume cloud AI solutions enables rapid prototyping and experimentation, using core technologies that can be moved in-house after the proof-of-concept is established, but which are rather more difficult for a local team to investigate creatively on an ad-hoc basis.

Rob Thomas, General Manager of IBM Data and Watson AI, has emphasized the importance of using at-scale turnkey solutions to explore various conceptual possibilities for local or hybrid AI implementations, asserting that even a 50% failure rate will leave an in-house approach with multiple viable paths forward.

5: High-Volume Providers Are Not Outfitted for Marginal Use Cases

If an in-house project does not center around the highest-volume use cases of external providers, such as computer vision or natural language processing, deployment and tooling is likely to be more complicated and time-consuming. It’s also likely to be lacking in quick-start features such as applicable pre-trained models, suitably customizable analytics interfaces, or apposite data pre-processing pipelines.

Not all marginal use cases of this nature are SMB-sized. They also occur in industries and sectors that may be essential but operate at too limited a scale or within such high levels of oversight (such as the nuclear and financial industries) that no ‘templated’ AI outsourcing solution is ever likely to offer adequate regulatory compliance frameworks across territories, or enough economy of scale to justify investment on the part of off-the-shelf cloud AI providers.

Commodity cloud APIs can also prove more expensive and less responsive in cases where the value of a data transaction lies in its scarcity and exclusivity rather than its capacity to scale at volume or address a large captive user base at a very low latency.

Gaining Google Trust is the Best Local SEO Strategy

A guy comes to your house, Google says he can add a room, fix your roof, and install new windows. He gives you an estimate that seems good, very good. Almost too good. In fact you start to wonder if you can trust him. Google wonders if it can trust you and your company. Gaining Google’s trust is the most important factor the best step for dominance local SEO.

Google

On August 1 2018 Google released an update that created the anagram E.A.T. . E.A.T. stands for Expertise, Authority and Trust. Along with E.A.T. came YMYL, Your Money Your Life. The updates highlighted Google’s attempt to weed out weak, spammy and malicious sites when Googlers were looking for information concerning either the health or their finances. Clearly, people needing information on that kind of subject needed search choices that were knowledgeable and honest. Trustworthiness was always a high ranking factor in Google searches. The E.A.T. updated added expertise to the main list of criteria for search.

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The Three Factors important for SEO:

But what about websites that don’t concern themselves with health or finance? It has been long recognized by the SEO industry that the three most important factors in local SEO are authority, relevance and trust.

Authority

Authority is the qualitative gauge which bolsters the prominence and ranking of a website, A main factor in local SEO is to increase authority. This is done through informative content and building valuable, high value links.  Authority by itself won’t guarantee search visibility.

Relevance

Relevance refers to how closely your website, or web page answers the query the user is asking. Along with relevance another local SEO factor is prominence. What business/website is the most highly considered and capable in this area for this query.

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Trust

Getting Google to trust your business and website takes time and effort. Trust us when we say the effort will be worth it. Here’s what you need to do to gain Google’s trust.

  1. Linking to websites that have authority (trustworthiness) and offer relevance to the content on the page you’re trying to rank. Site authority is measured differently by various entities. Google has no published measurement. The most popular tool for measuring site authority is Domain Authority from Moz.
  2. Google likes Terms and Conditions pages and Privacy notices. Make sure you have both on your site. Along with this, make sure your website has an SSL certificate assigned to the site.
  3. You should try to reduce your bounce rate. Keeping visitors on your website is a clue to Google that the content on your website is useful and engaging. Make sure your website pages are well organized and delivers the content your title tags promise. Speaking of title tags, you should use them. If you do, don’t over-stuff them with your key phrases. The page should read naturally. You should be writing for the the visitor, not Google.
  4. Letting your visitors know who you are with an About page is another trust factor Google values. Although images help with SEO, visitors seeing pictures of people on an About page increases trust with them, a goal you should also be pursuing.
  5. Maintain a regular schedule for updating your website with fresh content. Blog articles are great at accomplishing this important task. Businesses in some niches, construction for example, use case studies to highlight their expertise and add content to their site. If they add a link to the client website that’s even more authority.

If Google trusts your business, you can be that your sure visitors will too. It’s a win win for everybody.

7 Reasons CRM Is the Best Software For Remote Teams

COVID-19 Pandemic has affected our business in different ways. As most companies are now working remotely, the need for the best software for remote teams is more than ever. To efficiently manage your business remotely, increase collaboration among teams and ensure that you deliver the best customer experiences during this crucial time, you must leverage CRM software.

Software

As the CRM platform has got you covered, let’s dive in to learn more about how CRM software can help businesses operating remotely and what makes it the best software for remote team management.

Seamless Integration with Other Productivity Apps

As CRM software can be integrated with other productivity applications, you can cut the hassle of juggling different software and losing track of your tasks. Simply integrate your CRM platform with other business software and tools by leveraging CRM integration services to streamline your activity pipeline and improve task management. Moreover, the integration process is more seamless if you are using SugarCRM as it is flexible, easy to use and has an interactive user interface.

Mobile CRM

Equip your teams to better communicate with clients, manage tasks and stay updated with everything about the business with Mobile CRM. With SugarCRM implementation, you can access it anywhere and at any time to ensure that all business operations are run smoothly and quickly respond to your customers.

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Actionable Insights for Better Strategizing

In times of crisis, it’s important to be flexible in decision-making and change strategies to better adapt to the changing business situations. Now, with the CRM software in place, your data will be automatically updated and you can utilize it to derive actionable insights and plan your next move.

For example, if you leverage SugarCRM, you can make the most of your CRM investment to stay ahead of the curve and use it for robust reporting and interactive dashboards. Hence, teams working from home or remotely can leverage CRM as the best software for remote teams by making the most of predictive analytics.

Building Trusting Customer Relationships

During difficult economic situations, it’s crucial for a business to develop trusting customer relationships and utilize all customer touchpoints to know more about their customers. You can do it by integrating your CRM with Sugar Market to send personalized emails to your customers and let them know that you are with them in the time of crisis and will continue to deliver excellent results.

Sales On the Go

For remote teams, cloud-based software such as SugarCRM will ensure that the efficiency of the sales team is not affected. CRM helps in removing all bottlenecks in communication as all CRM users get a 360-degree view of the customers and the sales pipeline to work together and maximize the revenues.

Moreover, another reason that SugarCRM is a top option when it comes to choosing the best software for remote teams is its enhanced sales intelligence functionalities and accurate sales forecasting.

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Streamline Communication Among Teams

For teams to work better in a remote setting, there is no better option than SugarCRM as the best software for remote teams. CRM platform will provide end-to-end visibility of the activity pipeline and ensure that all employees are updated with the current business scenario and are proactively working to adapt to the changing business situations. Additionally, you can integrate Google Calendar in Sugar with the help of SugarCRM plugin- RT G Sync and easily schedule meetings and stay on top of your day to drive efficiency in business operations.

Boost Productivity

With seamless communication, CRM helps teams to boost productivity by eliminating redundant tasks through automation. This will allow your team to save the time spent on repetitive tasks such as data entry so they can focus on answering customer queries, regaining customer confidence and assuring them that they will be provided with the best customer service.

It’s A Wrap!

When employees are working remotely, the decision of choosing the best software for remote teams is critical. Investing in CRM software for working remotely will help in managing teams, building trusting relationships with customers and planning proactively by making data-driven decisions. Moreover, you can also leverage the expertise of our SugarCRM Certified Team to enhance the functionalities of your Sugar to boost the productivity of your remote teams and springboard your business to the next level.

The Global SD-WAN Market to Touch $53 Billion by 2030

The rapid adoption of 5G solutions and infrastructure will substantially dominate the global SD-WAN market, claims a recent study. With the pandemic-induced digital marketplace, the IT infrastructure is rapidly expanding with evolving business and technology needs. This includes security threat solutions, adoption of cloud platforms for different business teams, remote working tools, and more.

As a result, this adoption rate is anticipated to fuel the progress of the SD-WAN market in the coming years. A recent report by Persistence Market Research revealed that the global SD-WAN market is anticipated to grow rapidly – reaching a valuation of $53 billion globally by the end of 2030.

Global

Enterprises currently prefer a software-defined vast area network as it allows the bounding of several internet access resources. This is valid for digital subscriber lines (DSL), cables, and cellular/ any other IP transport to deliver high throughput data channels.

As per experts, WAN solutions enhance application performance, reduce costs, and increase agility – while addressing countless IT challenges. Hence, companies adopt SD-WAN solutions to tackle cyber risks and simplify WAN network management. Besides, it is efficient for offloading expensive circuits.

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The principle highlights from the study are:

  • The appliances division in the SD-WAN market is projected to gain significant share – owing to the growing adoption of cloud platforms.
  • The increasing requirement for fast services, application agility, and secure access into cloud applications heightens the demand for SD-WAN solutions.
  • The enterprise segment by end-user is most likely to hold a significant share in the market, attributable to the adoption of the associated SD-WAN services.
  • This rapid adoption of 5G apps and infrastructure is expected to result in substantial dominance of North America – in the worldwide SD-WAN market.
  • With companies globally relying more on remote operations due to the ongoing pandemic, the SD-WAN market is all set to proliferate extensively from now.

As mentioned in the report – “Number of partnerships between service providers and vendors in the SD-WAN marketplace is growing quickly. SD-WAN services offer service providers new opportunities to enhance the consumer experience. This factor is expected to increase adoption of SD-WAN during the forecast period.”

Certainly, the technology advancements in the SD-WAN solutions will boost the market growth. The rising use of cloud, IoT, and mobile applications have increased the need for edge services. In its essence, cloud-based services are the major centers for deploying IT tools as they lower the IT infrastructure costs.

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Moreover, it powers the speed of services for businesses. Hence, the cloud-based solution segment is estimated to witness high demand – due to its wide range of functionalities, including automation, increased flexibility, and faster services.

How To Plan & Develop Social Media Mobile App

Nowadays, no matter what, you’ll have at least one social media app on your smartphone. These connecting apps fill the void in many people’s lives and make them feel connected to their family & friends. Hence, it has become an almost impossible task to live without it. The market for such apps is continuously growing. This is an ideal time to invest in social media app development from a business perspective.
Social Media
As per the Statista report, 3.6 billion people are using social media apps, which constitutes approx. 45% of the population. This number is expected to rise to almost 58% in 2025. This indicates that social media trends are going to go up in the future. Therefore let’s begin with developing a social networking app, ending with the cost of developing it.
How to Build a Social Media App?
1) Define Strategy & Purpose
Building an app idea is not adequate. You will be required to study the market to discover the competitive field & evaluate the needs. Creating a social media app is a challenging task as you need to understand your potential users’ likes & dislikes. Once you are clear, it’s time to put ideas together to develop a social networking app.
Think of the options to retain the users, the techniques to grow and interact with the community. And if you plan to gain money using the social media app, you must plan your monetization options meticulously.
2) Design the Workflow

After outlining core features & functionalities, it’s time to design the workflow of your app. The designing process consists of several steps:
> Goal Defining
> Specification
> Wireframe
> Prototype
>Visual Design
>Interface Animation
>Testing
Sketching
This is a way to meet the basic outlines of future apps. It evaluates the project’s future logic, the no. of screens, and the interaction between them. It also lets you determine design issues even before you begin app designing.
Wireframing
Wireframing helps the development team to visualize the app working and idea to link pages. In a nutshell, it provides you the app’s structured view & what a user can expect from the app.
Prototyping
Another step is prototyping, and it includes building an app’s working model. This will provide developers a better idea about the product. The mockup will make it simpler to modify before the coding process begins if needed. Meaning, you are in a stronger position for the social media development process.
App Design
In the last stage of designing a workflow, change wireframes in the social app design. Research the current solutions, watch the latest trends and give a detailed UI/UX design to get the best possible answers.
3) Development & Quality Assurance
The development & social media processes go together in the software development lifecycle. After deciding the social media app platform and doing the app’s mockup, it is time to develop the back-end by setting up databases, APIs, servers, and working out perfect storage solutions.
Moreover, meet all the technical needs, platform standards, and user guidelines. Try manual & automatic testing of program’s each part to make sure there is no glitch in the code & all is ok with the project’s UX.
4) Publish & Expand your Community
After developing and publishing your app, it’s time to connect with potential users to build your community. Apply the best strategies in your initial social media marketing requirements. Discover how to influence people to install the app or what incentive you can render to your users. This way, you reach a broader audience.
5) App Analysis

The app analysis is a crucial step to evaluate your social media app’s success. There is a broad range of analytics tools that can help you with it.
> Cost/Install (CPI) – to track installs of users coming from marketing
> Customer Acquisition Cost (CAC) – the amount invested in attracting users
> User Activation – active users than downloads
> User Retention – users who used the app again
> Churn rate – users who have ceased using the app
> Traction – patterns to show the user’s growth each month
> Burn rate – money absorbed for the server costs, staff, & affiliate marketing
You can see the response of your active users or the time they invest in the app. Continuous track of engagement will provide you a clear picture of pragmatic changes for the future. This will even ensure to deliver the best user experience to your users.
How to Choose the Best Social Media App Developer?
To choose the best social media app developers, you need to find them. You can either go for an in-house team, freelancer app developer or outsource the best app development agency.
You can also refer to various blogs to know the top mobile app developer before hiring one. Several websites will help you select the best social media app, developers. You can also consider Hyperlink Infosystem; having developed more than 3200 apps for over 2300 clients, worldwide Hyperlink is one of the world’s top app development companies with a strength of 250+ skilled employees using the latest technology.
Below are the points you can consider before choosing your app developer:
– Determine the cost to hire app developers & the amount they need to finish the project.
– You must verify the expertise & developer’s portfolio to ensure their skillsets.
– Make sure you are clear with your needs about the product concept & the TA.
– Finally, know the app development process, legal contracts for the app development, & project management.
Cost to Develop the App
The cost to develop the app depends on several factors such as location, complexity, platform, hours spent, and more. However, if you want to know the approximate cost, it can range between $15,000 – $50,000. This app development cost is more affordable in India compared to other countries.

What’s Your Route to Enterprise AI Adoption?

Generally, emerging technologies that are valuable enough to become popular tend to decentralize at the earliest opportunity. From the print bureau to the home printer, the processing lab to the smartphone camera, the mainframe to the personal computer — the phase prior to this consumerization is hallmarked by business services gatekeeping the new technology and meting it out to consumer demand in small and increasingly profitable measures as hardware costs reduce — eventually reducing enough to diffuse the technology and kill the ‘gatekeeper’ business model.AI

The explosion of data storage and processing needs over the last twenty years has not only kept this from happening in the business information services sector, but has, according to some sources, practically eradicated the in-house data center in favor of the cloud.

5 Reasons to Develop AI Systems In-House

1: The Best Core Technologies Are Open-source Anyway

The academic origins of open-source GPU-accelerated machine learning frameworks and libraries over the last ten years have made it all but impossible for well-funded tech giants to cloister promising new AI technologies into patent-locked, proprietary systems.

This is partly because nearly all the seminal contributing work has been the result of international collaborations involving some mix of academic research bodies and government or commercial institutions, and because of the permissive licensing that facilitated this level of global cooperation.

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2: Protecting Corporate IP

Most in-house AI projects have a more fragile angle on success than the FAANG companies, such as a patentable use-case concept or the leveraging of internal consumer data — instances where the AI stack configuration and development is a mere deployment consideration rather than a value proposition in itself.

In order to avoid encroachment, it may be necessary to tokenize transactions that take place through cloud infrastructure, but keep local control of the central transaction engine.

Where client-side latency is a concern, one can also deploy opaque but functional algorithms derived from machine learning methods, rather than trusting the entirety of the system to the cloud, and encrypt or tokenize data returns for local analysis.

Such hybrid approaches have become increasingly common in the face of growing breach reports8 and hacking scandals over the last ten years.

3: Keeping Control of Data Governance and Compliance

The specificity of the input data for machine learning models is so lost in the training process that concerns around governance and management of the source training data might seem irrelevant, and shortcuts tempting.

However, controversial algorithm output can result in a clear inference of bias, and in embarrassingly public audits of the unprocessed training source data and the methodologies used.

In-house systems are more easily able to contain such anomalies once identified. This approach ensures that any such roadblocks in machine learning development neither overstep the terms and conditions of the cloud AI providers nor risk infringing the lattice of varying location-specific privacy and governance legislation that must be considered when deploying cloud-based AI processing systems.

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4: AIaaS Can Be Used for Rapid Prototyping

The tension between in-house enterprise AI and cloud-based or outsourced AI development is not a zero-sum game. The diffusion of open-source libraries and frameworks into the most popular high-volume cloud AI solutions enables rapid prototyping and experimentation, using core technologies that can be moved in-house after the proof-of-concept is established, but which are rather more difficult for a local team to investigate creatively on an ad-hoc basis.

Rob Thomas, General Manager of IBM Data and Watson AI, has emphasized the importance of using at-scale turnkey solutions to explore various conceptual possibilities for local or hybrid AI implementations, asserting that even a 50% failure rate will leave an in-house approach with multiple viable paths forward13.

5: High-Volume Providers Are Not Outfitted for Marginal Use Cases

If an in-house project does not center around the highest-volume use cases of external providers, such as computer vision or natural language processing, deployment and tooling is likely to be more complicated and time-consuming. It’s also likely to be lacking in quick-start features such as applicable pre-trained models, suitably customizable analytics interfaces, or apposite data pre-processing pipelines.

Not all marginal use cases of this nature are SMB-sized. They also occur in industries and sectors that may be essential but operate at too limited a scale or within such high levels of oversight (such as the nuclear and financial industries) that no ‘templated’ AI outsourcing solution is ever likely to offer adequate regulatory compliance frameworks across territories, or enough economy of scale to justify investment on the part of off-the-shelf cloud AI providers.

Commodity cloud APIs can also prove more expensive and less responsive in cases where the value of a data transaction lies in its scarcity and exclusivity rather than its capacity to scale at volume or address a large captive user base at a very low latency.

Must-Have Features For An eBook Reading App

With the advent of technology in every domain of life, nothing is left untapped, and printed books and papers are no exception. Ebooks are replacing printed books. Currently, ebooks are in high demand for the way it is structured, viewed, and conveyed. If you are wondering what an ebook is, it is a strong mobile service that is created to make the reading process more simple, comfortable, fun, and hassle-free.
eBook
After reviewing several ebooks, we have come across some essential features that must be included in your app if you are planning to develop one.
1. Massive Collection Of Book
An incredible ebook reading experience starts with a massive collection of available books, both installed and ready to read, and those that can be sourced. Apart from the typical categorization based on the genre like romance, non-fiction, historical, professional, etc., other things are also expected, like the status of various books, such as in-progress or completed, also sorting based on ratings or length, or other mechanisms.
New apps which developed by top app developers usa 2020 are also expected to utilize AI and machine learning to facilitate suggestions based on user behavior, such as which books they read and how they communicate with readers when they do.
2. Support Various Formats
The ebook apps support different formats, such as MOBI, EPUB, TXT files, PDF, Word Documents, and even encoded ebooks like those with Adobe DRM. Multiple reasons have led to their adoption, a few due to the abilities they render, some because they are supported and marketed by famous platforms. But the fact remains that the readers will have various eBooks bridging different formats. Hence, it makes perfect sense to support several forms possible.
An alternate model to support is to render an in-built conversion mechanism. The reading apps supports one or a small number of formats and performs really well.
3. Store & Sync Your Favorite Books
It is nothing new that a modern ebook reader app will store an ebook locally on the device for prompt and offline access. Many times, these ebooks would be rendered directly by the user. But once added to your app’s library, storing them to a back-up cloud mechanism allows the user to empty their device’s local store without stressing about their favorite books’ status. They would be available on-demand when required.
This further facilitates a sync mechanism where the reading apps available or are being viewed are available with reading status details across all devices owned by the user.
4. Different Platform Support

Your ebook app integrates across devices and performs both acknowledge the fact and facilitates users to resume enjoying their reads in various contexts on multiple form factors.
As more devices become amplified, operating on multiple OS, a success factor is how easy you make it for your users not just to read, but resume reading as their choice changes. Meaning, being available on Android and iOS, tablets and smartphones, and even colossal form factor devices like desktop computers.
5. A reader-friendly interface
Another factor that contributes to a successful reading app is a well-designed and intuitive user experience. The interface has to be well-planned and executed to render a pleasant user experience. Many interactions are based on the real-life experiences of reading printed books. Simultaneously, many innovations have been based on the capabilities of the platform.
There are well-established conventions, such as permitting various sizes to read the text, displaying a progress bar, adjusting the overall folio to show the updated sizing, and allowing people to pick the colors for the text. Some fascinating innovations are brewing up. These include taking the time of the day into account to change from blue to red tone or utilizing surrounding sensors to fix other aspects that impact readability.
6. Reading Tools
Since the reader indulges in the fantastic reading experience, another task is to make it more noticeable with tools and services that make it enjoyable. This can be done with standard and also expected tools, such as the bookmarking, capability to attach notes to selected text, an in-built dictionary, and the like.
Some ebook-reading apps have little more advanced tools like easily finding passages where a specific character has been addressed or cross-referencing a specific item. It has become easy for ebook readers to imitate a basic audiobook with text readout in the user’s favorite voice, with most platforms facilitating text-to-speech.
7. Reading gamification
There are only a few apps that lack some level of gamification. Ebook reading apps are not untapped, and several activities can be used to render an engaging, gamified experience to the users.
Features such as stickers, badges, streaks, levels, and more, frequently supported by rewards, are standard features. There are particular activities specific to reading ebooks like the speed of reading that are frequently used to facilitate these.
8. Social Media Integration

In the end, all mobile apps have to realize the significance of social interactions in everything that we do as humans. Conventionally where books were lent as suggested reading or people got together to read a book and communicate, the latest social integration apps have made it simpler to do it with people across the globe.
Services such as Goodreads have facilitated readers’ communities to get together, and social media allow for standard features like a social introduction to more new things like reading challenges. Besides suggesting books, people can also discuss them with like-minded people.
Conclusion
Ebook reading apps are obtaining popularity as the written material is erupting, and more people discover the joy of reading. There will always be a need for the ideal ebook reader app with fast digital accesses and a falling cost of devices.

How to Make the Most Useful Dashboard

From sports car to aircraft to super tanker, successful operation depends upon the pilot’s understanding and urgent timely use of a dashboard.  Real time information is critical to real time decision-making, and increasingly in the modern business world, decisions are made by management without extended meetings or discussion with others.

dashboard

Managers need real time information

And with the rise of modern technology-driven businesses, the same is true of management in the business world.  A good dashboard of relevant real time information is now available for most any business, often created by computer software from data derived from monitoring real time tasks within the business.

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Consider these critical pieces of information

You should consider creating such a dashboard or reviewing the one you use if already driving with one at hand.  I’ve developed four criteria for use in creating and evaluating your dashboard.  When constructing yours, you should consider the following:

  1. Controllable outcomes: There is no use for information for which there is no ability to control changes as a result of analysis.  Ensure that you include only information for which you have a way to alter future outcomes in a positive direction.  An example would be a real time display of the value of the dollar against the yen.  If your business has no trade with Japan that could be affected by arbitrage, early shipments or other tactics that take advantage of the moving value of these currencies, that statistic is irrelevant to the dashboard – even if interesting to you.
  2. Earliest warning metrics:  What good is information if you can’t act upon it in a timely manner?  Find metrics that will be “leading indicators” of trouble to come.  Think of labor efficiency (future product or service delivery impairment) or warehouse inventory (sales slowdown, supply chain management problems) as examples.
  3. Items in the critical path (bottlenecks): This is one of my focus issues for my workshops, it is so important. One of your chief duties is to remove bottlenecks in the delivery process for your product or service, enabling all resources before and after the bottleneck to achieve maximum efficiency.  If a critical path machine or employee is slow or down, your own email box overflowing with questions from subordinates needing answers, or any other measure of critical path impairment in need of fixing, you should know about it at the earliest possible moment.  Add a measure of each that you identify with to your dashboard.
  4. Items impacting cash (now or later): Cash is the oil of your business.  Slowing of production, deliveries, raw materials, receivables collections, billing for work completed – all are going to influence cash flow soon and should be tracked when out of expected range.

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Some simple indicators you can track

Simple indicators that affect multiple areas above include increasing backlog, call center delay time denigration, increases in finished goods inventory amounts, unbalanced work in process inventory buildups, and reduced efficiencies in billed time for consultants or experts.

And how about projecting cashflow?

How about projecting cash on your dashboard:  cash on hand plus expected accounts receivable collections subtracting necessary accounts payable payments and payroll.  You will find many more candidates for your personal dashboard.  Try to limit yours to five or fewer critical measures that can be updated no less often than daily if not in real time.

You will be steps ahead of most of your competitors and in a much better place to succeed if you create and maintain an effective dashboard.