WebSphere Application Server is a software product which helps to perform the role of a web application server. WebSphere is a flagship product and a set of Java-based tools by IBM which allows customers to create and manage sophisticated business Web sites. It was originally created by Donald F. Ferguson, who later became CTO of Software for Dell and the first version was launched in 1998.   

While the central WebSphere tool is known as WebSphere Application Server (WAS). WAS is an application server that helps the customer to connect Web site users with Servlets or Java applications. A Servlet is a Java program that runs on the server rather than on the user's application as Java applets do. Servlets are developed to replace the traditional common gateway interface (CGI) scripts. These scripts are usually written in C language, Practical Extraction or Reporting Language to run much faster and to control all other user requests that run in the same process space. 

In addition to Java, WebSphere also supports the open standard interfaces such as Common Object Request Broker Architecture (CORBA) and Java Database Connectivity — JDBC.  WebSphere is designed to use across different operating system platforms. You have an option of selecting the version suitable for your business purpose, as one edition of WebSphere will be offered for small to medium size businesses and another edition is for larger businesses with a huge number of transactions. It also has a Studio, which is a developer's environment added with additional components which allow creating web pages’ for a website and you can also the web pages accordingly. Both the versions support Solaris, Windows NT, OS/2, OS/390, and AIX operating systems.  

While the WebSphere Studio includes a copy of the Apache Web server; which helps the developers to test Web pages and Java applications at any given time.

What is WebSphere?

The moment you ask this question, the first thing that strikes in your mind is WebSphere is an application server; but in reality, WebSphere is the name of the product in IBM family. IBM has many more products under the brand name WebSphere, here are some of them WebSphere Application Server, WebSphere MQ, WebSphere Message broker, WebSphere process Server, WebSphere business modeler, WebSphere business monitor, WebSphere integration developer, WebSphere partner gateway.  

WebSphere Application Server Architecture

WAS is built using Open standards such as Java EE, XML, and Web Services. WebSphere application is supported on the following platforms; Linux, Windows, AIX, Solaris, IBM i and z/OS. It was started with Version 6.1 and the latest version is Version 8.5. While the open and standard specifications are aligned across all the platforms. Platform utilization is to an extent it takes place, but now it is done below across all open standard specifications line. 

Security

The WebSphere Application Server security model is based on the services provided by the operating system and as per the Java EE security model. WebSphere Application Server provides implementations of user authentication and authorization mechanisms given that support for various user registries:

•    Local operating system user registry

•    LDAP user registry

•    Federated user registry (version 6.1)

•    Custom user registry

The authentication mechanisms supported by WebSphere are

• Lightweight Third Party Authentication (LTPA)

Digitalization, digital networking, research, network automation, education and educational networks; are all these the buzz words of recent technology and for education institutions?  Why everyone is talking about digitalization and networks, how are these both interconnected; and what is network automation and education networks are what we are going to know on this blog today .

While what the smaller research say about the education networks and individual campus networks; we can say that both stand for the same aim which is implementing education through current network automation strategies and tools. Are these tools, strategies, and significant efficiencies or the network automation wave more hype than these smaller institutions?

Let us look at some of the regional networks, how they are succeeded and what are the challenges involved in this path of deploying various network automation with relatively small and outsourced staff and support. Also discussed will be the experience of working with this diverse technology and how it increased the awareness about the possible proposed value of network automation and how regional’s can assist smaller schools through this network path. 

Digital learning and collaboration have become an essential part of today’s education. From k-12 schools are implementing the methods of digital learning. These blended learning methods and one to one computing programs are reshaping the classroom studies and engaging more students to become tech-savvy’s. The higher educational institutions are announcing BYOD- which means bring your own device concept; students are also allowed to use their smart phones, laptops, tablets and other gadgets to be connected. This helps the institutions to meet the unprecedented demand for connectivity with high performance and to get recognized as highly reliable campus and data network center solution provider.

Challenges:

The hike of latest technologies, mobile devices and growing appetite for applications and rising security concerns are placing new burdens on educational networks. To meet these challenges, schools are expanding their networks to meet student and faculty expectations for high performance, highly reliable, and always-on connectivity.

The school network is always mission-critical, and downtime will be more and un-tolerable when class lectures, research projects, assignments are involved. We can see diversity and richness using these educational applications as learning is increasingly leveraging interactive curricula, collaboration tools, streaming media, and digital media. The success of the Common Core Assessments hugely depends on connectivity. The higher education, universities, and colleges that have poor quality, non-ubiquitous network access, quickly discover that this is affecting their registration/enrollment rates.

The other challenge is with the number of Wi-Fi devices and the types of devices students bring to a university or college campus; Students commonly have three or more devices like; smartphone, tablet, laptop, gaming device, or streaming media player and expect flawless connectivity. While higher education is deploying wireless IP phones for better communications, IP video cameras to develop physical security, and sensors for a more efficient environment. The projections for the Internet of Things, which will connect hundreds of billions of devices in a few short years, are nothing short of staggering.

The trends that educational networks are looking today for students, faculties and administrator expectations is that of for the connectivity which is rising and the complexity and cost of networking are also growing exponentially. In addition to this growth, the “adding on” to networking equipment for old designs is causing the network to become ever more fragile. IT budgets are tight, and technology necessities are growing faster than the funding.

What if schools took a step back and had a unique opportunity to proactively aim their networks to meet the challenges which hit today and tomorrow? What if deploying the network was simple, not a manual, time-consuming chore? What if your initial design and build could scale for years to come, without having to build configurations on the fly every time? What if networks were easier to plan and build, configure and deploy, visualize and monitor—and had automated troubleshooting and broad reporting?

The tools which are of high configurations help the educational networks are Juniper Networks, HP, CODE42, DLT, EKINOPS, Level 3, cloudyCluster, OSI and much more. It’s time to update the educational institutions towards the design, building, and maintaining the network and taking the advantage of automation and modern management tools to create scale, consistency, and efficiency.

Artificial intelligence has been spread over a very large area of computing since the beginning of the computer, but we are getting closer than ever with cognitive computing models. What are these models and why are we talking about it today. 

Cognitive computing comes from a mash-up of cognitive science which is the study of the human brain and how it functions and a touch of computer science and the results will have far-reaching impacts on our private lives, healthcare, business, and more.

What is Cognitive Computing?

The aim of cognitive computing is to replicate human thought processes in a programmed model. It describes technology platforms that broadly speaking, and which are involved in self-learning systems that use data mining, natural language processing, and pattern recognition to mimic the way the human brain works. With the goal to automate the IT systems that are capable of solving the problems without requiring human assistance the Cognitive computing is growing very fast.

Cognitive computing systems use machine learning algorithms; which repeatedly acquire knowledge from the data fed into them by mining data for information. These systems treat the way they look for patterns and as well as the way they process data so they have become competent of anticipating new problems and modeling possible solutions.

Cognitive computing is used in numerous artificial intelligence applications (AI), including expert systems, neural networks, natural language programming, robotics and virtual reality.  While computers are proved the faster machines at calculations and meting out the humans for decades; these machines haven’t been able to accomplish some tasks that humans take for granted as simple, like understanding natural language, or recognizing unique objects in an image. The cognitive computing represents the third era of computing: it from computers that could tabulate sums (the 1900s) to programmable systems (1950s), and now to cognitive systems.

The cognitive systems; most remarkably IBM and IBM +0.55%’s Watson, depend on deep learning algorithms and neural networks to process the information by comparing it to an education set of data.  The more data the systems are exposed to, the more it learns, and the more accurate it becomes over time, and this type of neural network is a complex “tree” of decisions the computer can make to arrive at an answer.

What can cognitive computing do?

As per the recent TED Talk from IBM, Watson could ultimately be applied in a healthcare setting also, this helps the administrative department of healthcare to collate the span of knowledge around conditions, which include the patient history, journal articles, best practices, diagnostic tools, and many more. Through this, you can easily analyze that vast quantity of information, and provide your recommendations as needed.

The next stage is to examine, which will be proceeded by the consulting doctor, who will then be able to look at the evidence and based on the recorded evidence the treatment options will be released based on these large number of factors including the individual patient’s presentation and history. Hopefully, this will lead to making better treatment decisions.

While in other scenarios, when the goal is not to clear and you look to replace the doctor, and the doctor’s capabilities by processing the humongous amount of data available will not be retained by any human and thus providing a summary of potential application will be overdue. This type of process could be done for any field such as including finance, law, and education in which large quantities of complex data will be in need to be processed and analyzed to solve problems.

However, you can also apply these systems in other areas of business like consumer behavior analysis, personal shopping bots, travel agents, tutors, customer support bots, security, and diagnostics.  We see that there are personal digital assistants available nowadays in our personal phones and computers like —Siri and Google GOOGL -0.21% among others, which are not true cognitive systems; and have a pre-programmed set of responses and can only respond to a preset number of requests.  But, as tech is on high volume we will be able to address our phones, our computers, our cars, our smart houses and get a real time in the near future when thoughtful response rather than a pre-programmed one.

The coming future will be more delightful for us as computers will become more like humans and they will also expand our capabilities and knowledge. Just be ready to welcome the coming era when computers can enhance human knowledge and ingenuity in entirely new ways.

When your customers value your business propositions, what should be the next is the question to be asked to every business entrepreneur today.  As per the recent survey, 80% of you do, but only 8% of your customers actually come back to you and agree that you provide superior value.

Now it’s not going to help you out as it is a sad state of affairs, for you and for your customers too. It’s self-evident that great customer satisfaction drives customers loyalty as well a wish to repeat your business levels to more or to next stage; this will, in turn, help you to grow fast and more generously with expected revenues.  Best example:  When you follow up on your sales leads and identified by your loyalty surveys that your revenue increases of more than you expected.

Since we know that everyone today is more cautious about keeping their date safe, collecting it, or using it to improve and maintain their customer relationship for as long as they can. But, back then there are still constraints on server and storage capacity, which leads to lack of high-scale software tools, limited companies’ ability to understand their customers.

Today, all that has changed, using the resources are available in the cloud, but how far, as you know that virtually unlimited amounts of cheap storage, complicated analytics, and gadget learning, to name a few is possible now to gain of detailed and actionable insights as never before; and you can truly know our customers.

Take an example: A famous sports franchise captures every interaction the championship team has with its fans from the website to online merchandising to mark on social feeds and grabs more attention towards its brands.

If you want to implement such advanced techniques to your business growth then there are tools available in the market such as Dynamics Online, Dynamics Marketing, Microsoft Office 365 and Power BI for Data Visualization.

Many businesses do not use application analytics for improving their customer relationships. According to Forrester, it’s more likely to use analytics first and foremost to monitor and improve the performance of your applications.  That’s a good thing to do- but if performance is all you need to monitor, as you are leaving your money on the table; make sure that your priorities in digital marketing must include by improving your customer engagement, your customers wants, which makes you too easy the work and measure convenience, personalization and trust.  

Successful companies including your competitors are increasingly aware that they are all inevitably becoming software and analytics companies.  All the data is in use or the data they collect from their customers can be analyzed to maximize your relationship and of course your profits. That means that software which is not ready must become a core competency for your company.

MARC ANDREESSEN famously remarked as venture capitalist a few years ago marked — Software, is “eating the world.”

Big or small, companies today are finding different ways to capture and use more data. Almost everyone agrees to this that Big Data has taken the business world by storm. But what’s next?  What are the technologies which will develop around it?

Or Will data continue to grow; and can it become a relic as quickly as the next trend — Cognitive Technology? Fast Data? - appears on the prospect. Let’s look at some of the predictions from the foremost experts in the field, and how likely they are to come to pass and see how the push to make big data more mainstream and stronger in 2016. 

• Volume of Data will grow. There’s absolutely no question that companies will continue generating larger and larger volumes of data, particularly considering the number of handheld devices and Internet-connected devices are expected to grow exponentially by 2020.
• Ways to examine data will advance. Though SQL is still the standard, Spark is rising as a paired tool for analyzing and will continue to grow, according to analysts.  
• More tools for analysis. Microsoft MSFT +2.24% and Salesforce are recently announced features to let non-coders create apps to view business data, furthermore the tech experts are on developing more tools.
• Regulatory analytics will be built in to business analysis software. As per IDC predictions half of all business analytics software will be integrated to the intelligence by 2020.
• Real-time streaming insights into data will be the certifying the data winners moving forward according to Forrester. There will be huge growth as many users will want to be able to use data to make decisions in their real time with programs like Spark and Kafka.   
• Device learning is going to be top strategic trend for 2016, according to Gartner predicts, we can see more that of device learning; as it will become the necessary element for data preparation and predictive analysis in businesses to move forward.  
• BD will face vast challenges around privacy, especially with the new privacy regulation introduced by the European Union. Companies and businesses will be forced to address the ‘gaint in the room’ around their privacy controls and procedures. Gartner predicts that by 2018, more than 50% of business ethics violations will be related to Data.
• Companies will look for a Chief Data Officer. As per Forrester the future businesses will be in need of a CDO; who will see a rise in prominence in the short term. But again for certain types of businesses and even generational differences will see less need for them in the future.
• Independent agents and things will be the huge trends; Gartner includes that robots, autonomous vehicles, virtual personal assistants, and smart advisers will the future trends.  

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• Data staffing shortages will grow from analysts and scientists to include experts and architects in Data Management according to IDC.  
• BD talent crunch may ease; as companies employ new strategies and the International Institute for Analytics predicts that organizations may increase their recruiting and provide internal trainings to get their personnel problems solved.
• Data-as-a-service model is on the scope. Forrester suggests that after IBM, more businesses will attempt to monetize their Data.
• Cognitive technology will be the new buzzword for many businesses in future, the link between cognitive computing and analytics will become identical in much the same way that businesses now see similarities between analytics and Big Data.
• Companies and Data businesses will grow; according to Forrester more companies and businesses will attempt to drive value and revenue from their data.  
• Businesses using their data will see billions in productivity benefits; according to International Institute for Analytics this will happen over their competition not using data by 2020.
• Fast Data and Actionable Data is going to replace Big data; some of the experts say that  argument is that big isn’t necessarily better when it comes to data, and that businesses don’t use a fraction of the data they have access too. Instead, the idea suggests companies should focus on asking the right questions and making use of the data they have — big or otherwise.

Time will only tell which of these predictions will come to real pass and which will merely pass into darkness. But the important takeaway will be all about Big data that is only going to get bigger and every business for and into data and for those companies that ignore it will be left further and further behind.