How Your Small Business can Benefit from Machine Learning

How Your Small Business can Benefit from Machine Learning

The practice of Machine Learning (ML) is no longer an exotic concept for businesses. No matter if you have a small business or a Fortune 500 enterprise; the chances are that you can benefit from the nuances of AWS Machine Learning. While prominent organizations have different ways of using Machine Learning than their smaller siblings, there is a multitude of ways in which even small businesses can benefit from Machine Learning techniques.

What Exactly is Machine Learning?

Machine Learning is a type of artificial intelligence which uses programs, algorithms, and data to drive learning and automation. Under normal circumstances, it’s something you most likely already encounter on a day to day basis. For example, if you are using software like Amazon’s Alexa, Microsoft’s Cortana, Google’s Assistant, or Apple’s Siri, then you have already had a taste of the power of Machine Learning.

On the other hand, Machine Learning and Artificial Intelligence can be used in businesses as well; it isn’t just for asking about the latest weather conditions. For instance, many websites are making use of chatbots to assist customers. Businesses, irrespective of their size, are using the likes of Machine Learning to help customers while driving efficiency and monitoring social media accounts.

How can AWS Machine Learning Help Business?

Amazon has established themselves as a leader in customer service and operations. Such execution can be found with the Amazon Web Services (AWS) Machine Learning tool. These data learning devices are aimed at catering to data scientists, researchers, developers and even small businesses who are enthusiastic to use Machine Learning to their advantage.

The extent of Machine Learning advantages is not limited to just the essentials. Solutions such as Amazon Comprehend and AWS DeepLens are some of the top-notch services being provided by Amazon these days. Through these services, developers can inherit the ability to use neural networks to gain insight with regards to computer vision projects.

Developers can also train chatbots, which can cater to a customer’s specific incoming request. Machine Learning and Artificial Intelligence can even be utilized to organize a website’s content, as various defined logical algorithms come into play. A small business can also coordinate their website’s inventory using artificial intelligence.

If you are running a small business, and feel as though you don’t wish to dapple in artificial intelligence alone, then you can count on the consulting services of companies such as Idexcel. Experienced teams are always available to help businesses of any scales accomplish their goals and increase their cloud repertoire.

How does AWS Machine work with Small Businesses?

Small businesses often need to use predictive models to enhance their revenue and sales models. One of the ways to improve these models is through the use of machine learning. Entrepreneurs, who are running small businesses, often don’t have sufficient time or the resources to sift through massive data and derive intelligent decisions out of it; this is where machines learning techniques come to the rescue.

Such business owners can benefit immensely from the use of AWS Cloud-based services and AWS Machine Learning. The vast amount of data which is collected can be sorted, sifted, and analyzed to deliver helpful business-related insight efficiently.

Through the use of machine learning, small businesses can save on operating costs, while at the same time make sound decisions, and earn better profits than before. However, it is import to know that small businesses cater to customers at different stages. For this reason, it’s imperative to understand how customer behavior can change from time to time. Through predictive analytics and machine learning, such tactics can become a breeze.

No matter what the type of business you have, machine learning can come to your aid at any given point in time. From data collection to data storage and insights you can have it all; it not only helps enhance your business’s image through the use of chatbots but also helps you manage your inventory efficiently. Such is the power Machine Learning gives to its users.

For every small business owner out there, there is a unique benefit that you will get with the use of AWS Machine Learning techniques. It all depends on how you use the services to meet your company’s needs and wants at the end of the day.

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The Future of Data Science Lays within Cloud-Based Machine Learning and Artificial Intelligence

The Future of Data Science Lays within Cloud-Based Machine Learning and Artificial Intelligence

From working in solitary cubicles to working with artificial bots, automation has come a long way and has changed how the modern generation works. Today, Artificial Intelligence (AI) and Machine Learning (ML) have become regarded as the future of tomorrow’s workforce and culture. At Idexcel, we have been keeping track of these ongoing trends.

It has been said that “with great power comes great responsibility.” If we tweak this statement a bit to reflect more contemporary times, we can also assuredly say that “with great technology, comes heaps of data.” The more we progress on the path of digitization, the more massive our datasets have become, and the idea that fascinates all data scientists is linked with the emergence of AI and ML technologies – how can they be used efficiently?

Here are top 10 trends that you should look out for as they shape the direction of data analytics in our future:

Augmented Analytics: This technology broadly utilizes the power of machine learning to automate data preparation and presentation. Through the use of augmented analytics, data scientists hope to be able to aid human intelligence, to produce rapid outcomes in different data-driven domains.

Artificial Intelligence and Machine Learning: Many of us might still be living in a bubble when it comes to AI assisted work. However, the fact of the matter is, that this bubble is going to burst. With robotics and artificial intelligence taking over at an increasing pace, there is a very heavy emphasis on getting data up and running to meet organizational goals. AI and ML will be used extensively to simplify work processes through the use of Big Data analytics.

Big Data: As technology has been advancing over the years and more affordable machines have emerged, faster processing powers have been available to businesses. Now, as cloud services are taking over traditional storage methods, there is a lot to look forward to regarding the increased output of processed information. As all these sources of information generate data, there is an imminent need to draw meaningful conclusions from the data – this is where Big Data comes into the picture. As the sources for storage get defined, Big Data provides excellent methods for allowing the manipulation of stored data to draw analysis and get the ball rolling.

Cloud and Edge Computing: One can easily say that technology has reached the Clouds. Companies such as Amazon, Google, and Microsoft are providing Cloud Services to organizations for storing their day to day data. Edge Computing, which is another form of shared computing, has become the next generation’s technology. Through the means of Edge Computing, organizations can overcome connectivity and latency issues, so that the distance data has to travel is reduced significantly. Edge Computing has seen an increasing rate of growth in mobile computing, as well as in the decrease of computer hardware. The rising use of IoT-enabled devices has ushered in an era of new technology.

Predictive Analytics: As more problematic situations emerge, there is a need to develop systems which can solve problems with ease and provide meaningful solutions. Predictive analytics prove to be the solution for such issues. The better the insights, the more structured are the solutions. Such are the capabilities of predictive analytics, as they help organizations gear up to tackle the worst possible issues.

Blockchain Technology: Digital currencies, such as BitCoin, owe their very existence to Blockchain technology. Given the success rate of cryptocurrencies, there is a lot of focus on merging Blockchain technology with the world of data science. The idea is to fuse the two methodologies together, to maximize the results. Since Blockchain technology is a versatile source, it can store any digital data; it has become a well-received option with data scientists.

As more and more organizations are taking analytics and data science seriously, there is an imminent need to progress to the next level of technology. Here at Idexcel, we work with clients every day to provide DataOps Consulting and Services; it has become an inseparable part of the modern organizational structure. As we progress into the future, the thin line between business intelligence and artificial intelligence will be removed; data will become smarter than ever before.

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AWS IoT Analytics Provides Intelligence Data For Businesses

AWS IoT Analytics Provides Intelligence Data For Businesses

One of the significant highlights of the Amazon Web Services (AWS) re:Invent 2017 conference is the company’s IoT Analytics; a fully-managed service that makes the experience of running sophisticated analytics on massive volumes of IoT data flawless. The new AWS system eliminates the worry of cost and complexity typically incurred during the build and deployment of a personal IoT analytics platform. AWS IoT Analytics has rendered an effortless way to run analytics on IoT data, along with gathering ongoing insights to better the experience of decision making for IoT applications and machine learning.

The Complexities of Unstructured Data

Since IoT data is highly unstructured, it became a mission for AWS to simplify data structures so that it would become easier for cognitive computing solutions to analyze the IoT database. This idea is executed through business intelligence tools that are designed to process large unstructured data. IoT data is procured mainly through reasonably noisy processes, which in turn produces extensive and complex data with gaps, corruption, false reading and so on; this data needs to be taken care of before any analysis can occur. Besides, IoT data is often integrated into the context of other data from external sources and must be managed appropriately.

Are you utilizing analytics and the existing information provided by your system to increase problem solving and overcome the obstacles to processing big data? Amazon’s AWS IoT Analytics allows for customers to solve complex problems without complex solutions. Our team here at Idexcel is at the ready and available to work with those who want to ensure they are getting the most out of their AWS setup. Be sure to reach out for our cloud advisory services and accelerate your journey to the cloud.

Analyzing Problems and Providing Solutions

AWS IoT Analytics automates each of these problematic steps that are required to analyze data from IoT devices. IoT Analytics acts as a catalyst that filters, transforms, and enriches information before storing it in a time-series data storage for analysis. The service can then be customized according to the business: which, how much, and when to use appropriate data. AWS IoT Analytics applies mathematical equations to process and then enrich the data with device-specific metadata. Data is then analyzed by running queries using the built-in SQL query engine. IoT Analytics kick starts the process and provides better scope for outputting high accuracy information. IoT Analytics also exhibits the ability to facilitate machine learning through employing pre-built models of common IoT use cases; it can then quickly respond to probable system failure or system incompatibility and suggest replacement of hardware.

AWS IoT Analytics can keenly examine and scale automatically to support up to petabytes of IoT data; it helps analyze data from millions of devices and build fast, responsive IoT applications without managing different hardware or infrastructures. The service complements the driving forces of current IoT infrastructure with differing advancements.

It is worth noting some of the most important benefits of IoT Analytics include:

Quick and Easy Queries on Massive IoT Data – With the help of a built-in IoT Analytics SQL query engine, it becomes effortless to run ad-hoc queries; this service enables the user to use standard SQL queries to extract data directly from the data store to answer potential questions.

Time-Series Analytics – AWS IoT Analytics also supports time-series interpretations to analyze the performance of devices over time in a recurring pattern, and understand their place and manner as they are being employed. Analytics can continuously monitor device data and suggest maintenance actions as needed. The system can also observe sensors to analyze and react to environmental conditions.

Data Storage Optimized for IoT – AWS IoT Analytics stores processed device data and can deliver fast response times on IoT queries. The source data is automatically stored for later processing or to reprocess it for another use case, creating a more intelligent dataset.

Prepare IoT Data for Analysis – AWS IoT Analytics also performs data preparation that makes it easy to prepare and process your data for analysis. Integrated with AWS IoT Core, the service makes it easier to ingest device data directly from connected devices. IoT Analytics filters the data apart from corruption, false readings, and errors, and then the system performs mathematical transformations of message data. Using conditional statements the analytical service filters data, and then collects specific data required for analysis; it also gives the option of using AWS Lambda functions to enrich device data from external sources.

Tools for Machine Learning – AWS IoT Analytics is well suited for machine learning on IoT data as it has the ability hosts Jupyter notebooks. The administrator can directly connect IoT data to the notebook to build, train, and execute models right from the IoT Analytics console. Machine learning algorithms are applied to data all the more readily, which produces a health score for each device in the fleet.

Automated Scaling with Pay-As-You-Go Pricing – AWS IoT Analytics follows a pay-as-you-go service, with which one can analyze an entire fleet of connected devices without managing hardware or infrastructure. As the administrator’s needs change, they can expand or contract computation power. The data store will also automatically scale up or down, which results in the billing of only employed resources.

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The 2018 HIMSS Conference & Exhibition


Date : MARCH 5-9, 2018
Location : LAS VEGAS
Venue: VENETIAN – PALAZZO – SANDS EXPO CENTER

Event Details: The 2018 HIMSS Conference & Exhibition, March 5–9, 2018 in Las Vegas, brings together 45,000+ professionals from around the world for five days of education, innovation and collaboration to help uncover the promise of health information and technology. No other conference brings you the world-class education, cutting-edge products and solutions, and unique networking opportunities you need to solve your biggest health information and technology challenges – all at one time, all in one place. Choose from 300+ education sessions, 1,300+ vendors, hundreds of special programs, and endless networking events. HIMSS18: Where the World Connects for Health.

[Know more about the Conference]

About Idexcel: Idexcel is a Professional Services and Technology Solutions provider specializing in Cloud Services, Application Modernization, and Data Analytics. Idexcel is proud that for more than 20 years it has provided services that implement complex technologies that are innovative, agile and successful and have provided our customers with lasting value.

Anand Allolankandy – (Sr. Director Technical Sales & Delivery at Idexcel) will be attending this event. For further queries, please write to anand@idexcel.com

The Challenges and Benefits of Modernizing Legacy Applications in Cloud

The Challenges and Benefits of Modernizing Legacy Applications in Cloud
It was right from its inception that cloud computing displayed a revolutionizing potential—it had an unforeseen scope over diverse targets including individuals, companies and governments. The major services available in these sectors and the ever growing inventions of the modern world do indeed call for a more advanced and flexible application of cloud computing. It is seen by many as the new wave of information technology. In 2010, the World Economic Forum published a report which evaluated the impact of cloud computing technologies and signaled the large potential benefits of adoption, ranging from economic growth and potential improvements in employment to facilitating innovation and collaboration.

Need being the mother of invention, Cloud has evolved beyond basic SaaS, IaaS, and PaaS offerings, as the cloud matures to become the engine of enterprise technology innovation. It is moving towards a faster and more efficient world. However, the Information Technology is increasing its demands to solve the arising complexities. Take for example the modernizing of legacy applications in cloud. It extends both challenges and opportunities, as the facets of a coin, but in each way it moves towards a more advanced and intricate web of complexities.

Most of the large enterprises run at least some form of a legacy application, for which updates and replacements can sometimes be tricky. However, failing to modernize out-of-date systems may hinder the pace of information exchange due to slow runtime speeds and inefficient load balancing. Many organizations have, thus, begun to modernize their legacy applications which will yield long term benefits such as portability and scalability, better speed and resource management, and granular visibility.

Since the start, enterprises have run on time-consuming manual processes and tools that are involved with legacy applications also hinders modernizing efforts. Manual processes take up significant amount of time and still leave room for errors. However, at the same time, enterprises say they need to move to the cloud, but they don’t really understand why, nor do they realize how difficult it can be. This includes applying cloud services to a non-compatible old legacy application and facing challenges when trying to re-host. They must be cautious of the processes involved in migrating the valuable data. If one moves one application to cloud which has business logic or IT logic of another application that isn’t migrated to cloud, they might run into issues. Therefore, it is better to consult the professionals before landing into problems. In this league of advancement, the infrastructure might face challenges such as:

Cost adjustments: The cost of maintaining and upgrading Legacy systems renders the firm a challenge of combatting the financial balance. The challenge preparers the employees learn the skills of pulling the firm through the tight passage without de-establishing the financial pace of the organization.

Inflexible and closed architectures: There are some architectures used by organizations that hinder Web and mobile enabling and integration with contemporary platforms, therefore, they turn out to be challenging opportunities for the modern minds at work.

Limited Integration: Legacy systems might sometimes not go in cohesion with the integration to contemporary technologies like Mobile Apps/Devices, Enterprise Content Management Systems, Automated Workflow, E-Forms/E-Signatures, Geographic Information Systems, and so on, therefore pose a major obstacle for the integrators.

User Friendliness: The existing system uses command-based screens and cannot provide a contemporary Graphical User Interface (GUI), web, or mobile which have become commonplace, however, if it is in constant practice, the newer models of commanding may pose an oddity for quite some time for the old hands. Therefore, the migrators have to go an extra mile to ease the way by employing less complicated systems.

On the other hand, there are various benefits of applying this modernization. If the engineers handle the aforementioned challenges wisely and implement the newer technology with greater precision, there indeed some charming benefits await, such as:

Enhanced flexibility: Creates a flexible IT environment with new architectural paradigms such as web services; aligns IT systems to dynamic business needs.

Modern development tools: Legacy and new developers can use the same or similar tools, enabling both to develop Legacy applications.

Lower risks: Re-use of business rules where data becomes less risky than alternatives.

Shorter development times: Modernizes development tools and retrains developers which lead to shorter development times.

Reduced cost: Lowers high maintenance cost of existing old fashioned Legacy platforms and development tools, resulting in substantial savings in IT budgets.

Minimized disruption: Reduces the risk when modernizing Legacy platforms by combining two decades of development experience with contemporary platforms, a proven modernization framework and rich domain knowledge.

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Amazon ECS for Kubernetes: Bridging the Migration gaps

Amazon ECS for Kubernetes
AWS has unveiled a new container service that will allow its users to run Kubernetes on AWS server without needing to install and operate a separate Kubernetes cluster. The service can be identified as a major advancement for AWS which will allow the users migrate smoothly, who had, though, previously found Amazon ECS slightly rigid when it yielded optimum results only when operated on AWS’ own server.

Amazon Elastic Container Service for Kubernetes is a managed service that transcends this obstacle. With this cross platform achievement, AWS will certainly attract (or at least keep) its customers for it has eradicated one major obstacle of transferring clusters on personal server of AWS—inter-cloud exchange. Kubernetes is known to be an open-source system used for automating the deployment, scaling, and managing containerized applications. While Kubernetes had previously posed significant challenges to producing applications, where one was required to manage scaling and availability of Kubernetes masters and persistence layer, Amazon EKS has eased this tedious task by rendering an automatic selection of appropriate instance types. It runs them across multiple Availability Zones along with replacing unhealthy masters through constant heath monitoring. Even the patch and upgrade routines of master and worker nodes no longer need to be monitored manually, which required a lot of expertise and, above all, a tremendous amount of manpower and time. Amazon EKS automatically upgrades the nodes and prepares them for high availability. It runs three Kubernetes masters across three Availability Zones to achieve this flawless feat.

Amazon EKS, just like ECS, can be integrated with many AWS services to provide direct scalability and security for various applications, including Elastic Load Balancing for load distribution, IAM for authentication, Amazon VPC for isolation, AWS PrivateLink for private network access, and AWS CloudTrail for logging. It runs the latest version of the open-source Kubernetes software, which allows the user to have all the latest and existing plugins and tools from the Kubernetes community. Due to the absolute compatibility offered with Amazon EKS for application running on standard Kubernetes Environment, the user can easily migrate any standard Kubernetes application to Amazon EKS without any code modification.

Having stated the common properties of Amazon EKS, let’s look at the major benefits for opting it:

Secure
Security is of paramount importance in this cloud based IT world. With more advanced features, the Amazon EKS is loaded with highly advanced security features for the Kubernetes Environments of any managed cloud service. The migrated workers are launched on the user’s Amazon EC2 instances, where no compute resources are exposed to other customers.

It allows the users to manage the Kubernetes cluster using standard Kubernetes tools such as kubectl CLI for managing Kubernetes, through AWS Identity and Access Management (IAM) authenticated public endpoints or through PrivateLink.

Fully Compatible with Kubernetes Community Tools
Since Amazon EKS runs the latest version of the open-source Kubernetes software, all the existing and even newer features, plugins, and applications are supported in it. Applications that are already running in an existing Kubernetes environment will be fully compatible, and can be flawlessly moved to Amazon EKS cluster.

Fully Managed and Highly Available
Amazon EKS eradicates the need to install, manage, and scale personal Kubernetes clusters. With this development, EKS is one step ahead of the ECS. The worker and master clusters of Kubernetes are automatically made highly available which are distributed across three different Availability Zones for each cluster, due to which, worker and master servers start functioning more smoothly than ever before. Amazon EKS manages the multi Availability Zone architecture and delivers resiliency against the loss of an Availability Zone. Furthermore, it automatically detects and replaces unhealthy masters and provides automated version upgrades and patching for the masters.

Amazon EKS integrates IAM with Kubernetes which enables the user to register IAM entities with the native authentication system in Kubernetes. The user no longer has to worry about manually setting up credentials for authenticating with the Kubernetes masters which also allows IAM to directly authenticate with the master itself as well as granularly control access to the public endpoint with regards to the targeted Kubernetes masters.

Besides that, it also gives the option of using PrivateLink to access Kubernetes masters directly from personal Amazon VPC. With PrivateLink, Kubernetes masters and Amazon EKS service endpoint appear as an elastic network interface with private IP addresses in Amazon VPC, which opens the threshold for accessing the Kubernetes masters and the Amazon EKS service directly from Amazon VPC, without using public IP addresses or requiring the traffic to traverse the internet.

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Pink18: IT Service Management Conference & Exhibition

Pink18
Date : February 18-21, 2018
Location : Florida
Venue: JW Marriott Orlando, Grande Lakes

Event Details
The conference theme will be covered in over 120+ sessions and 12 tracks to show how you can master the dynamics of today’s business environments by adopting, adapting and applying tried and true best practices. Subjects include: ITSM, ITIL, Lean IT, Agile, Scrum, DevOps, COBIT®, Organizational Change Management, Business Relationship Management, and more!

[Know more about the Conference]

About Idexcel:idexcel is a global IT professional services and technology solutions provider specialized in AWS Cloud Services, DevOps, Cloud Application Modernization and Data Science. With keen focus on addressing immediate and strategic business challenges of customers, idexcel is centered at providing deep industry and business process expertise. The idexcel team thoroughly dedicates itself to the occupation of technology innovation and business improvisation. Aware that all businesses involve specific areas unique to their culture and environment, the Idexcel team encourages flexibility and transparency across all levels of interactions with clients. Our team of AWS certified experts ensure that clients benefit from the latest cutting-edge technology in AWS cloud.

Our Mission: Our mission is to provide effective, efficient and optimal IT professional services meeting our client’s needs. Our extensive and proven technical expertise enables us to provide the high quality of services and innovative solutions to our clients.

Allolankandy Anand Sr. Director Technical Sales & Delivery will be attending this event. For further queries, please write to anand@idexcel.com