Tag: Desktop-as-a-Service (DaaS) Solution

Why is AIOps an Industrial Benchmark for Organizations to Scale in this Economy?

Posted on by Subhadeep Datta

Ashish Joseph

Business Environment Overview

In this pandemic economy, the topmost priorities for most companies are to make sure the operations costs and business processes are optimized and streamlined. Organizations must be more proactive than ever and identify gaps that need to be acted upon at the earliest.

The industry has been striving towards efficiency and effectivity in its operations day in and day out. As a reliability check to ensure operational standards, many organizations consider the following levers:

  1. High Application Availability & Reliability
  2. Optimized Performance Tuning & Monitoring
  3. Operational gains & Cost Optimization
  4. Generation of Actionable Insights for Efficiency
  5. Workforce Productivity Improvement

Organizations that have prioritized the above levers in their daily operations require dedicated teams to analyze different silos and implement solutions that provide the result. Running projects of this complexity affects the scalability and monitoring of these systems. This is where AIOps platforms come in to provide customized solutions for the growing needs of all organizations, regardless of the size.

Deep Dive into AIOps

Artificial Intelligence for IT Operations (AIOps) is a platform that provides multilayers of functionalities that leverage machine learning and analytics.  Gartner defines AIOps as a combination of big data and machine learning functionalities that empower IT functions, enabling scalability and robustness of its entire ecosystem.

These systems transform the existing landscape to analyze and correlate historical and real-time data to provide actionable intelligence in an automated fashion.

Data Center Migration Planning Tools

AIOps platforms are designed to handle large volumes of data. The tools offer various data collection methods, integration of multiple data sources, and generate visual analytical intelligence. These tools are centralized and flexible across directly and indirectly coupled IT operations for data insights.

The platform aims to bring an organization’s infrastructure monitoring, application performance monitoring, and IT systems management process under a single roof to enable big data analytics that give correlation and causality insights across all domains. These functionalities open different avenues for system engineers to proactively determine how to optimize application performance, quickly find the potential root causes, and design preventive steps to avoid issues from ever happening.

AIOps has transformed the culture of IT war rooms from reactive to proactive firefighting.

Industrial Inclination to Transformation

The pandemic economy has challenged the traditional way companies choose their transformational strategies. Machine learning-powered automations for creating an autonomous IT environment is no longer a luxury. The usage of mathematical and logical algorithms to derive solutions and forecasts for issues have a direct correlation with the overall customer experience. In this pandemic economy, customer attrition has a serious impact on the annual recurring revenue. Hence, organizations must reposition their strategies to be more customer-centric in everything they do. Thus, providing customers with the best-in-class service coupled with continuous availability and enhanced reliability has become an industry standard.

As reliability and scalability are crucial factors for any company’s growth, cloud technologies have seen a growing demand. This shift of demand for cloud premises for core businesses has made AIOps platforms more accessible and easier to integrate. With the handshake between analytics and automation, AIOps has become a transformative technology investment that any organization can make.

As organizations scale in size, so does the workforce and the complexity of the processes. The increase in size often burdens organizations with time-pressed teams having high pressure on delivery and reactive housekeeping strategies. An organization must be ready to meet the present and future demands with systems and processes that scale seamlessly. This why AIOps platforms serve as a multilayered functional solution that integrates the existing systems to manage and automate tasks with efficiency and effectivity. When scaling results in process complexity, AIOps platforms convert the complexity to effort savings and productivity enhancements.

Across the industry, many organizations have implemented AIOps platforms as transformative solutions to help them embrace their present and future demand. Various studies have been conducted by different research groups that have quantified the effort savings and productivity improvements.

The AIOps Organizational Vision

As the digital transformation race has been in full throttle during the pandemic, AIOps platforms have also evolved. The industry did venture upon traditional event correlation and operations analytical tools that helped organizations reduce incidents and the overall MTTR. AIOps has been relatively new in the market as Gartner had coined the phrase in 2016.  Today, AIOps has attracted a lot of attention from multiple industries to analyze its feasibility of implementation and the return of investment from the overall transformation. Google trends show a significant increase in user search results for AIOps during the last couple of years.

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While taking a well-informed decision to include AIOps into the organization’s vision of growth, we must analyze the following:

  1. Understanding the feasibility and concerns for its future adoption
  2. Classification of business processes and use cases for AIOps intervention
  3. Quantification of operational gains from incident management using the functional AIOps tools

AIOps is truly visioned to provide tools that transform system engineers to reliability engineers to bring a system that trends towards zero incidents.

Because above all, Zero is the New Normal.

About the Author –

Ashish Joseph is a Lead Consultant at GAVS working for a healthcare client in the Product Management space. His areas of expertise lie in branding and outbound product management. He runs a series called #BizPective on LinkedIn and Instagram focusing on contemporary business trends from a different perspective. Outside work, he is very passionate about basketball, music, and food.

Significance of CI CD Process in DevOps

Posted on by Site Admin

Muraleedharan Vijayakumar

Developing and releasing software can be a complicated process, especially as applications, teams, and deployment infrastructure grow in complexity themselves. Often, challenges become more pronounced as projects grow. To develop, test, and release software quickly and consistently, developers and organizations have created distinct strategies to manage and automate these processes.

Did you know?  Amazon releases a new production code once every 11.6 seconds.

Why CI/CD/CD?

The era of digital transformations demands faster deployments into production. Faster deployments do not warrant defective releases, the solution – ‘DevOps’. The development team, operations team, and IT services team have to work in tandem and the magic circle that brings all of them together is DevOps.

To adopt a DevOps culture, implementing the right DevOps tools with the right DevOps process is essential. Continuous integration/continuous delivery/continuous deployment (CI/CD/CD) help us developers and testers ship the software faster and safer in a structured environment.

The biggest obstacle that needs to be overcome in constructing a DevOps environment is scalability. There are no definite measures on the scalability of an application or product development, but DevOps environment should be ready to scale to meet business and technology needs. It lays a strong foundation for building an agile DevOps for the business.

Continuous Integration and Deployment has seen many benefits in the software delivery process. Initiating automated code builds once checks are completed, running automated test suites, flagging errors and breaking builds if not adhered to compliance have eased the way of deploying a stable release into staging or production environment and eliminating manual errors and human bias.

How is CI/CD/CD Set Up?

Version control tools play an important role in the success of our DevOps pipeline. And designing a good source stage is pivotal to our CI/CD success. It ensures that we can version code, digital assets, and binary files (and more) all in one spot. This enables teams to communicate and collaborate better — and deploy faster.

Our code branching strategy determines how and when developers branch and merge. When deciding on a strategy it is important to evaluate what makes sense for our team and product. Most version control systems will let you adopt and customize standard strategies like mainline, trunk-based, task/feature branching, etc.,

Typical Branching Model Followed

A basic workflow starts with code being checked out. When the work in the branch is committed, CI processes are triggered. This can be done with a merge or pull request. Then the CI/CD pipeline kicks into high gear.

The goal of CI/CD is to continuously integrate changes to find errors earlier in the process, as known as ‘Shift Left’.  The ultimate goal of having an automated CI/CD process in place to identify errors or flag non-compliance at an early stage of the development process. This increases the project’s velocity by avoiding late-stage defects and delays. It creates an environment where code is always ready for a release. With the right branching strategy, teams are equipped to deliver success.

Continuous Integration: Integrating newly developed code with the central repository is continuous integration. Automated CI results in automated builds that are triggered to merge the newly developed codes into the repository. As part of this process, plugins can be added to perform static code analysis, security compliance checks, etc., to identify if the newly added code would have any impact on the application. If there are compliance issues, the automated build breaks, and the same is reflected to the developer with insights. Automated CI helps in increasing the productivity of the developers and the team.

Continuous Delivery: At the end of a successful CI, Continuous Delivery is triggered. CD ensures to automate the software delivery process and commits to deliver the integrated code into the production stage without any bugs or delays. CD helps in merging the newly developed code into the main branch of the software so that a ready to production product is available with all the checks in place.CD also checks the quality of the code and performs tests to check whether it can release the functional build to the production environment.

Continuous Deployment: The final and most critical part of DevOps is Continuous Deployment. After the successful merging of certified code, the pipelines are triggered to deploy the code into the production environment. These pipelines are also triggered automatically. The pipelines are constructed to handle the target environment be it jar or container deployments. The most important aspect of this pipeline is to tag the releases that are also done in the production environment. If there are rollbacks these tags help the team to roll back to the right version of the build.

CI/CD/CD is an art that needs to be crafted in the right and most efficient way that will help the software development team achieve their success at a faster pace.

Different Stages & Complete DevOps Setup

What is the CI/CD/CD  Outcome?

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About the Author –

Murleedharan is a senior technical manager and has managed, developed, and launched cutting edge business intelligence and analytics platforms using big data technologies. He has experience in hosting the platform in Microsoft Azure by leveraging the MS PaaS. He is a product manager for zDesk – A Virtual Desktop offering from GAVS.
His passion is to get a friction-less DevOps operational in an environment to bring down the deployment time to a few seconds.

Design-led Organization: Creative Thinking as a Practice!

Posted on by Site Admin

Gogul R G

This is the first article in the series of ‘Design-led organization’ writing about creative thinking as a practice in GAVS. It is the first step for the readers to explore the world of design and creativity. So, let’s get started!

First let’s see what is design thinking is all about

There is a common misconception that design thinking is new. But when you look back, people have applied a human-centric creative process to build meaningful and effective solutions. Design has been practiced for ages to build monuments, bridges, automobiles, subway systems, etc. Design is not only limited to aesthetics, it is more of a mindset to think of a solution. Design thinking is a mindset to iteratively think about a complex problem and come up with a viable solution. 

Thinking outside of the box can provide an innovative solution to a sticky problem. However, thinking outside of the box can be a real challenge as we naturally develop patterns of thinking that are based on the repetitive activities and commonly accessed knowledge surround ourselves. It takes something to detach away from a situation where we’re too closely involved to be able to find better possibilities.

To illustrate how a fresh way of thinking can create unexpectedly good solutions, let’s look at a famous incident. Some years ago, an incident occurred where a truck driver had tried to pass under a low bridge. But, he failed, and the truck became firmly lodged under the bridge.

IT Infrastructure Managed Services

The driver was unable to continue driving through or reverse out. The struck truck caused massive traffic problems, which resulted in emergency personnel, engineers, firefighters, and truck drivers gathering to negotiate various solutions to dislodge the truck.

Emergency workers were debating whether to dismantle parts of the truck or chip away at parts of the bridge. Each of one were looking for a solution with their respective level of expertise. A boy walking by and witnessing the intense debate looked at the truck, at the bridge, then looked at the road and said, “Why not just let the air out of the tires?” to the absolute amazement of all the specialists and experts trying to resolve the issue.

When the solution was tested, the truck could drive with ease, having suffered only the damage caused by its initial attempt to pass underneath the bridge. It symbolizes the struggles we face where often the most obvious solutions are the ones hardest to come by because of the self-imposed constraints we work within.  

“Challenging our assumptions and everyday knowledge is often difficult for us humans, as we rely on building patterns of thinking in order not to have to learn everything from scratch every time.“

Let’s come back to our topic “What is Design thinking?” Tim Brown, Executive Chairman of IDEO – an international design and consulting firm quoted design thinking as below.

“Design thinking is a human-centered approach to innovation that draws from the designer’s toolkit to integrate the needs of people, the possibilities of technology, and the requirements for business success.”

Now let’s think about our truck example. A boy with his fresh mindset provides a simple solution to address a complex problem. Yeah! this is the sweet spot. Everyone is creative and capable of thinking like a designer, and out of the box, to come up with a solution. This way of inculcating design as a mindset for a solution is known as Design thinking.

Yes, you read it right, everyone is creative…

We forget that back in kindergarten, we were all creative. We all played and experimented with weird things without fear or shame. We didn’t know enough not to. The fear of social rejection is something we learned as we got older. And that’s why it’s possible to regain our creative abilities, even decades later. In the field of design and user experience, there are individuals to stick with a methodology a while, they will end up doing amazing things. They come up with break through ideas or suggestions and work creatively with a team to develop something truly innovative. They surprise themselves with the realization that they are a lot more creative than they had thought. That early success shakes up how they see themselves and makes them eager to do more.

We just need to rediscover what we already have: the capacity to imagine, or build upon, new to the world ideas.  But the real value of creativity doesn’t emerge until you are brave enough to act on those ideas.

Geshe Thupten Jinpa, who has been the Dalai Lama’s chief English translator for more than twenty years, shared an insight about the nature of creativity. Jinpa pointed out that there’s no word in the Tibetan language for ‘creativity’ or ‘being creative’. The closest translation is ‘natural’. In other words, if you want to be more creative, you should be more natural! So…be natural!

At your workplace, the complex problems can be easily sorted out when you find a solution using creativity with the mindset of design thinking. Creativity can be improved by following the below steps.

  1. Go for a walk.
  2. Play your favorite games.
  3. Move your eyes.
  4. Take a break and enjoy yourself.
  5. Congratulate yourself each time you do something well.
  6. Estimate time, distance, and money.
  7. Take a route you never have taken before.
  8. Look for images in mosaics, patterns, textures, clouds, stars…
  9. Try something you have never done before.
  10. Do a creative exercise.
  11. Start a collection (stamps, coins, art, stationery, anything you wish to collect)
  12. Watch Sci-Fi or fantasy films.
  13. Change the way you do things – there are no routine tasks, only routine way of doing things.
  14. Wear a color you do not like.
  15. Think about how they invented equipment or objects you use daily.
  16. Make a list of 10 things you think are impossible to do and then imagine how you could make each one possible.
  17. For every bad thing that happens to you, remember at least 3 good things that happened.
  18. Read something you have not read yet.
  19. Make friends with people on the other side of the world.
  20. When you have an idea, make a note of it, and later check to see if it happened.
  21. Connect a sport with your work.
  22. Try food you never tried before.
  23. Talk to grandparents and relatives and listen to their stories.
  24. Give an incorrect answer to a question.
  25. Find links between people, things, ideas, or facts.
  26. Ask children how to do something and observe their creativity.

Start doing the above-mentioned steps to inculcate a creative mindset and apply it in your day-to-day work. Companies like GE health care, Procter & Gamble, UBER practiced design thinking and implemented in their new product launches and for solving complex problems in their organizations. Be natural to be more creative! When you are more creative, you can apply design thinking for seeking any solution for a complex problem in your work.

This is the first article in the series of Design led Organization in GAVS. Keep watching this space for more articles on design and keep exploring the world of design-thinking!

References:

About the Author –

Gogul is a passionate UX designer with 8+ years of experience into designing experiences for digital channels like Enterprise apps, B2C, B2B apps, Mobile apps, Kiosk, Point of Sale, Endless aisle, telecom products. He is passionate about transforming complex problems into actionable solutions using design.

Center of Excellence – Security

Posted on by Site Admin

The Security Center of Excellence was instituted to set standards in the practice and be the point of contact for technical solutions, problem solving, etc. The broad objectives of this CoE are as follows:

  • Develop and maintain technical assets that can be leveraged across GAVS.
  • Enable Quality Governance by providing support in gating of architecture and design related deliverables.
  • Enable Operational Governance by establishing cadence for tech review of projects.
  • Create domain-based SMEs within the practice.
  • Train and upskill members in the practice.
  • Improve customer satisfactory index by implementing new ideas and innovations across all engagements.
  • Create additional SOC services for market competency.
  • Automation – Detect, investigate and remediate cyberthreats with playbooks and response workflows.

COVID and the changing nature of threat landscape

For many industries, it has been challenging period ever since the COVID outbreak, more so for those in security. Clearly, the bad actors have lot of time at their disposal which is reflective in the innovative techniques being used to attack targets. The level of vigilance required in monitoring the alerts and application of threat hunting techniques is key to diagnosing problems at initial stages of compromise in the worst-case scenario.

Microsoft Cloud Solution Provider

Remote Infrastructure Monitoring Services
Source: IBM X-Force Research

For enterprises that have no clue about MDR (Managed Detection and Response), this is a good time for them to start. We have innovative, cost effective solutions – “Make Hay while the Sun shines”. Small and large corporations alike have lost business and money because of lapse in security controls and monitoring. Now is not the time to make headlines that you are the victim of a major breach.

Our team is developing a vulnerability alerting tool, which we intend to equip customers with to provide qualified bulletin alerts, i.e. alerts only on vulnerabilities that affect them. This is a first of a kind in the market. This will greatly benefit existing and new customers.

Expanding into IAM and PAM

Security practice is expanding into Identity & Access Management (IAM) and Privileged Access Management (PAM) services. With new customers being onboarded into this focus areas for products such as Sailpoint, Thycotic, Ping, Cyberark, Okta and Azure PIM, we are expanding our talent pool through recruitment and through training and certification. This should largely benefit our existing customers and prospects who intend to leverage our security practice to fulfil their cyber security needs.

Expansion of our Red Team

Our Red Team within the practice has been expanded with many talented members, including some with bug bounty bragging rights. This has enormously helped in performing intensive tests on our internal product platforms, security assessments for customers. We have also extensively invested on tools for the Red Team to help them reduce assessment times.

Certification drive

With some more analysts having certified across AZ-500, Cyberark and trained on Darktrace. GAVS’ security analysts are taking full advantage to increase their knowledge thanks to the generosity of our alliances and training sites like Pluralsight. Even the mighty Microsoft opened their learning website for free, enabling young talent to equip themselves with critical DevOps and Cloud security skills.

As part of CoE initiatives, we have;

  • Aligned our security roadmap based on industry trends and to ensure solutions tailored for customer pain points.
  • Extended our SOC practice with IAM and PAM in 2020.
  • Identified domain-based SME and product-based SME for quick support.

We are currently in the process of creating security products, GVAS and GSMA, to help customer in proactively identifying and addressing vulnerabilities and self-maturity assessment of their cybersecurity posture. We are also underway to add Operational security to our Security practice.

If you have any questions about the CoE, you may reach out to them at COE_INFOSEC@gavstech.com

CoE Team Members

  • Venkatakrishnan A
  • Shivaram J
  • Alex Nepolian Lawrence
  • Ravindran Girikrishnan
  • Aravindah Sadhasivam Subramanian
  • Vijayakumar Veerapandiyan
  • Thubati Uday
  • Ganta Venkata Sandeep
  • Sundaramoorthy S
  • Sukanya Srinivasan

Center of Excellence – Java

Posted on by Site Admin

The Java CoE was established to partner with our customers and aid them in realizing business benefits through effective adoption of cutting-edge technologies; thus, enabling customer success.

Objectives

  • Be the go-to team for anything related to Java across the organization and customer engagements.
  • Build competency by conducting training and mentoring sessions, publishing blogs, whitepapers and participating in Hackathons.
  • Support presales team in creating proposals by providing industry best solutions using the latest technologies, standards & principles.
  • Contribute a certain percent of revenue growth along with the CSMs.
  • Create reusable artifacts, frameworks, solutions and best practices which can be used across organization to improve delivery quality.

Focus Areas

  1. Design Thinking: Setting up a strong foundation of “Design Thinking and Engineering Mindset” is paramount for any business. We aim to do so in the following way:
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2. Solution and Technology: Through our practice, we aim to equip GAVS with solution-oriented technology leaders who can lead us ahead through disruptive times

IT Operations Management Software

3. Customer success

  • Identify opportunities in accounts based on the collaboration with CSMs, understand customer needs, get details about the engagement, understand the focus areas and challenges.
  • Understand the immediate need of the project, provide solution to address the need.
  • Java council to help developers arrive at solutions.
  • Understand architecture in detail and provide recommendation / create awareness to use new technologies
  • Enforce a comprehensive review process to enable quality delivery.

Accomplishments

  • Formed the CoE team
  • Identified the focus Areas
  • Identified leads for every stream
  • Socialized the CoEwithin GAVS
  • Delivered effective solutions across projects to improve delivery quality
  • Conducted trainings on standards and design-oriented coding practices across GAVS
  • Publishedblogs to bring in design-oriented development practices
  • Identified the areas for creating re-usable artefacts (Libraries / Frameworks)
  • Brainstormed and finalized the design for creating Frameworks (For the identified areas)
  • Streamlined the DevOps process which can be applied in any engagement
  • Built reusable libraries, components and frameworks which can be used across GAVS
  • Automated the Code Review process
  • Organized and conducted hackathons and tech meetups
  • Discovered potential technical problems/challenges across teams and offered effective solutions, thereby enabling customer success
  • Supported the presales team in creating customized solutions for prospects

Upcoming Activities

  • Establishing tech governance and align managers / tech leads to the process
  • Setting up security standards and principles across domain
  • Buildingmore reusable libraries, components and frameworks which can be used across GAVS
  • Adopting Design Patterns / Anti-patterns
  • Enforcing a strong review process to bring in quality delivery
  • Enabling discussions with the customers
  • Setting up a customer advisory team

Contribution to Organizational Growth

As we continue our journey, we aim to support the revenue growth of our organization. Customer Success being a key goal of GAVS, we will continue to enable it by improving the quality of service delivery and building a solid foundation across all technology and process streams. We also want to contribute to the organization by developing a core competency around a strategic capability and reduce knowledge management risks.

If you have any questions about the CoE, you may reach out to them at COE_JAVA@gavstech.com

CoE Team Members

  • Lakshminarasimhan J
  • Muraleedharan Vijayakumar
  • Bipin V
  • Meenakshi Sundaram
  • Mahesh Rajakumar M
  • Ranjith Joseph Selvaraj
  • Jagathesewaren K
  • Sivakumar Krishnasamy
  • Vijay Anand Shanmughadass
  • Sathya Selvam
  • Arun Kumar Ananthanarayanan
  • John Kalvin Jesudhason

Observability versus Monitoring

Posted on by Site Admin

Sri Chaganty

“Observability” has become a key trend in Service Reliability Engineering practice.  One of the recommendations from Gartner’s latest Market Guide for IT Infrastructure Monitoring Tools released in January 2020 says, “Contextualize data that ITIM tools collect from highly modular IT architectures by using AIOps to manage other sources, such as observability metrics from cloud-native monitoring tools.”

Like so many other terms in software engineering, ‘observability’ is a term borrowed from an older physical discipline: in this case, control systems engineering. Let me use the definition of observability from control theory in Wikipedia: “observability is a measure of how well internal states of a system can be inferred from knowledge of its external outputs.”

Observability is gaining attention in the software world because of its effectiveness at enabling engineers to deliver excellent customer experiences with software despite the complexity of the modern digital enterprise.

When we blew up the monolith into many services, we lost the ability to step through our code with a debugger: it now hops the network.  Monitoring tools are still coming to grips with this seismic shift.

How is observability different than monitoring?

Monitoring requires you to know what you care about before you know you care about it. Observability allows you to understand your entire system and how it fits together, and then use that information to discover what specifically you should care about when it’s most important.

Monitoring requires you to already know what normal is. Observability allows discovery of different types of ‘normal’ by looking at how the system behaves, over time, in different circumstances.

Monitoring asks the same questions over and over again. Is the CPU usage under 80%? Is memory usage under 75% percent? Or, is the latency under 500ms? This is valuable information, but monitoring is useful for known problems.

Observability, on the other side, is about asking different questions almost all the time. You discover new things.

Observability allows the discovery of different types of ‘normal’ by looking at behavior, over time, in different circumstances.

Metrics do not equal observability.

What Questions Can Observability Answer?

Below are sample questions that can be addressed by an effective observability solution:

  • Why is x broken?
  • What services does my service depend on — and what services are dependent on my service?
  • Why has performance degraded over the past quarter?
  • What changed? Why?
  • What logs should we look at right now?
  • What is system performance like for our most important customers?”
  • What SLO should we set?
  • Are we out of SLO?
  • What did my service look like at time point x?
  • What was the relationship between my service and x at time point y?
  • What was the relationship of attributed across the system before we deployed? What’s it like now?
  • What is most likely contributing to latency right now? What is most likely not?
  • Are these performance optimizations on the critical path?

About the Author –

Sri is a Serial Entrepreneur with over 30 years’ experience delivering creative, client-centric, value-driven solutions for bootstrapped and venture-backed startups.

Dashboard SAP Lumira Designer – Write Back Functionality

Posted on by Site Admin

Mohammed Fazal Uddin Kashif

Dashboards are considered to be one of the key success factors of businesses. Easy access to real-time KPIs allows them to be proactive and address business challenges before they impact the bottom line.

SAP Lumira Designer, formerly known as SAP Design Studio, is one of the robust products available in the market for developing top-of-the-line analytical applications and business dashboards. However, every tool by its core functionality has limitations for some use cases and business processes. One of such considerable cases is the ability to write back to a database directly from the dashboard.

Write back functionality assists business users to modify the data while analyzing from the dashboard rather than doing it in the source system. This functionality facilitates business users to manipulate the data and reflects refreshed data in the dashboard for further review and assessment.

This article introduces the use of Lumira SDK Extension component, POST RESPONSE PARSER, which enables the core range of Lumira designer to expand its boundary to include write-back functionality by integrating external Web API into the Lumira Dashboard.

Integrating Post Response Parser SDK Extension, the Lumira dashboard could be transformed from a pure data visualization application into an interactive data management analytical application.

Data Exploration & Smart Visualizations

Dashboards are analytical tools that visually track, analyzes and display Key Performance Indicators (KPIs) to the business processes or the portfolios. It provides a comprehensive snapshot of the performance of a key component within the portfolio. KPIs are business metrics which assists the leadership team to arrive at key decisions and drive towards the goals.

Business Dashboards and analytical applications provide at-a-glance visual and graphical representation of data which eliminates the need to go through long and complex excel spreadsheets.

Also, it’s time-consuming and difficult to pull out the most important business information whereas presenting that information in an appealing, visual way is more result-driven and effective.

Interactive dashboards enable us to visualize the data, filter on demand and simply click to dive deeper, quickly engage end-users, and provide an intuitive experience and insights.

Among various visualization tools available in the market, SAP Lumira has an edge being an SAP tool where end-user consumption of analytical applications is governed and secured by the SAP Business Objects BI Platform.

Extending the Dashboard Functionality

Lumira designer provides extensive customizations through scripting, styling with CSS and above all, the integration of external SDK Components makes it a pinnacle tool to achieve the desired functionalities.

Like any other technology, dashboards are constantly evolving, with versatility and impactful ability of integrating SDK components assisting the rapidly developing scope and scale of visualizations for the organizations.

Along those lines, Business users expect the ability to modify the data that lies behind a visualization component by providing data inputs to the dashboard while analyzing the data and anticipate the changes to be reflected immediately in the dashboard.

Lumira designer leverages support for updating or modifying the data in underlying database through write back functionality.

Benefits of write back in the dashboard:

  • It transforms a traditional dashboard to Interactive analytical application which supports business data modifications
  • It allows data analysis and data update from the same dashboard, rather switching over different applications for each task

SDK Extensions

SDK stands for Software Development Kit. SDK is set of tools, libraries, code samples, processes and guides that allows developers to create applications on a specific platform.

SDK Extension components can be integrated flawlessly into the core application to utilize its features for the customized product developments. The visualization of extension components is based on HTML, JavaScript and CSS.

Web Application Programming Interface

Web API is an Application Programming Interface over the web which can be accessed using HTTP protocol.

Web API is an extensible framework for building HTTP based services that can be accessed in different applications on different platforms such as web, windows, mobile etc.

Integrating Web APIs into the Lumira designer enhances the dashboard functionality by adding abilities not offered in the baseline version of the tool, such as providing the possibility of writing back to the source database directly from the dashboard itself.

Post Response Parser

Post Response Parser is an SDK Extension, with which you can model your application to make AJAX (Asynchronous JavaScript and XML) calls to any Web API and evaluate the response for desired interactivity in Lumira designer.

Feature of Post Response Parser:

  • Opens a request via AJAX call to any specific URL
  • Accepts parameters along the Request
  • Supports BIAL (BI Action Language) Scripting for interactive control at runtime

Business Use Case

In Banking, Credit Control & Monitoring department uses exception reports on their day to day operations for the analysis of their customers credit performance. Based on the outcomes, the team decides on the action to be taken for the respective customers with the various levels of audits.

Business Team faces challenges to maintain and track the remarks and comments on each customer by looking at the reports. So CCM wants to develop a dashboard with the ability to update their observations and comments on the same dashboard which in turn gets stored in database.

Lumira designer provides sub-optimal workarounds for capturing the filters and remarks with technical components like Bookmarks and Comments which comes along with the core application, but these components cannot not write back to the database, but incorporating  SDK Extensions along with the core would be able to achieve the desired customization in the dashboard application.

Functionality and Process Flow

The Post Response parser integrates external Web API into the Lumira designer, this SDK extension passes the parameters from the dashboard to the underlying stored procedure in Web API which in turn updates to the database.

Snippet of process to be followed:

  • Install Post Response Parser SDK Extension at client and server system
  • Encapsulate the parameters as global variable and enable its property to expose as URL Parameter
  • Create a Web service for dashboard to accommodate the database updates
  • Define an event to trigger the SDK Extension in Lumira application
  • Reload the data source through script to reflect the changes in dashboard

Conclusion

Lumira designer is competent to build Business Intelligence Applications that can be dynamic and customizable as per the business users’ workflow.

An interactive prototype is the best way for both users and designers to learn about their specific needs.

In conclusion, Lumira Designer with SDK Extensions offers that capabilities to accommodate our design process and it stands strong in its ability to build simple or complex Analytic Applications and Executive Dashboards.

About the Author:

Kashif is a SAP Business objects consultant and a business analytics enthusiast. He believes “Ultimate goal is not about winning, but to reach within the depth of capabilities and to compete against yourself to be better than what you are today.”

Discover, Monitor, Analyze & Predict COVID-19

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Bargunan Somasundaram

“Uber, the world’s largest taxi company, owns no vehicles. Facebook, the world’s most popular media owner, creates no content. Alibaba, the most valuable retailer, has no inventory. Netflix, the world’s largest movie house, own no cinemas. And Airbnb, the world’s largest accommodation provider, owns no real estate. Something interesting is happening.”

– Tom Goodwin, an executive at the French media group Havas.

This new breed of companies is the fastest growing in history because they own the customer interface layer. It is the platform where all the value and profit is. “Platform business” is a more wholesome term for this model for which data is the fuel; Big Data & AI/ML technologies are the harbinger of new waves of productivity growth and innovation.

With Big data and AI/ML is making a big difference in the area of public health, let’s see how it is helping us tackle the global emergency of coronavirus formally known as COVID-19.

DISCOVERING / DETECTING

Chinese technology giant Alibaba has developed an AI system for detecting the COVID-19 in CT scans of patients’ chests with 96% accuracy against viral pneumonia cases. It only takes 20 seconds for the AI to decide, whereas humans generally take about 15 minutes to diagnose the illness as there can be upwards of 300 images to evaluate. The system was trained on images and data from 5,000 confirmed coronavirus cases and has been tested in hospitals throughout China. Per a report, at least 100 healthcare facilities are currently employing Alibaba’s AI to detect COVID-19.

Ping An Insurance (Group) Company of China, Ltd (Ping An) aims to address the issue of lack of radiologists by introducing the COVID-19 smart image-reading system. This image-reading system can read the huge volumes of CT scans in epidemic areas.

Ping An Smart Healthcare uses clinical data to train the AI model of the COVID-19 smart image-reading system. The AI analysis engine conducts a comparative analysis of multiple CT scan images of the same patient and measures the changes in lesions. It helps in tracking the development of the disease, evaluation of the treatment and in prognosis of patients. Ultimately it assists doctors to diagnose, triage and evaluate COVID-19 patients swiftly and effectively.

Ping An Smart Healthcare’s COVID-19 smart image-reading system also supports AI image-reading remotely by medical professionals outside the epidemic areas. Since its launch, the smart image-reading system has provided services to more than 1,500 medical institutions. More than 5,000 patients have received smart image-reading services for free.

The more solutions the better. At least when it comes to helping overwhelmed doctors provide better diagnoses and, thus, better outcomes.

MONITORING

  • AI based Temperature monitoring & scanning

In Beijing, China, subway passengers are being screened for symptoms of coronavirus, but not by health authorities. Instead, artificial intelligence is in-charge.

Two Chinese AI giants, Megvii and Baidu, have introduced temperature-scanning. They have implemented scanners to detect body temperature and send alerts to company workers if a person’s body temperature is high enough to constitute a fever.

Megvii’s AI system detects body temperatures for up to 15 people per second and up to 16 feet. It monitors as many as 16 checkpoints in a single station. The system integrates body detection, face detection, and dual sensing via infrared cameras and visible light. The system can accurately detect and flag high body temperature even when people are wearing masks, hats, or covering their faces with other items. Megvii’s system also sends alerts to an on-site staff member.

Baidu, one of the largest search-engine companies in China, screens subway passengers at the Qinghe station with infrared scanners. It also uses a facial-recognition system, taking photographs of passengers’ faces. If the Baidu system detects a body temperature of at least 99-degrees Fahrenheit, it sends an alert to the staff member for another screening. The technology can scan the temperatures of more than 200 people per minute.

  • AI based Social Media Monitoring

An international team is using machine learning to scour through social media posts, news reports, data from official public health channels, and information supplied by doctors for warning signs of the virus across geographies. The program is looking for social media posts that mention specific symptoms, like respiratory problems and fever, from a geographic area where doctors have reported potential cases. Natural language processing is used to parse the text posted on social media, for example, to distinguish between someone discussing the news and someone complaining about how they feel.

The approach has proven capable of spotting a coronavirus needle in a haystack of big data. This technique could help experts learn how the virus behaves. It may be possible to determine the age, gender, and location of those most at risk quicker than using official medical sources.

PREDICTING

Data from hospitals, airports, and other public locations are being used to predict disease spread and risk. Hospitals can also use the data to plan for the impact of an outbreak on their operations.

Kalman Filter

Kalman filter was pioneered by Rudolf Emil Kalman in 1960, originally designed and developed to solve the navigation problem in the Apollo Project. Since then, it has been applied to numerous cases such as guidance, navigation, and control of vehicles, computer vision’s object tracking, trajectory optimization, time series analysis in signal processing, econometrics and more.

Kalman filter is a recursive algorithm which uses time-series measurement over time, containing statistical noise and produce estimations of unknown variables.

IT Infrastructure Managed Services

For the one-day prediction Kalman filter can be used, while for the long-term forecast a linear model is used where its main features are Kalman predictors, infected rate relative to population, time-depended features, and weather history and forecasting.

The one-day Kalman prediction is very accurate and powerful while a longer period prediction is more challenging but provides a future trend. Long term prediction does not guarantee full accuracy but provides a fair estimation following the recent trend. The model should re-run daily to gain better results.

GitHub Link: https://github.com/Rank23/COVID19

ANALYZING

The Center for Systems Science and Engineering at Johns Hopkins University has developed an interactive, web-based dashboard that tracks the status of COVID-19 around the world. The resource provides a visualization of the location and number of confirmed COVID-19 cases, deaths and recoveries for all affected countries.

The primary data source for the tool is DXY, a Chinese platform that aggregates local media and government reports to provide COVID-19 cumulative case totals in near real-time at the province level in China and country level otherwise. Additional data comes from Twitter feeds, online news services and direct communication sent through the dashboard. Johns Hopkins then confirms the case numbers with regional and local health departments. This kind of Data analytics platform plays a pivotal role in addressing the coronavirus outbreak.

All data from the dashboard is also freely available in the following GitHub repository.

GitHub Link: https://bit.ly/2Wmmbp8

Mobile version: https://bit.ly/2WjyK4d

Web version: https://bit.ly/2xLyT6v

Conclusion

One of AI’s core strengths when working on identifying and limiting the effects of virus outbreaks is its incredibly insistent nature. AI systems never tire, can sift through enormous amounts of data, and identify possible correlations and causations that humans can’t.

However, there are limits to AI’s ability to both identify virus outbreaks and predict how they will spread. Perhaps the best-known example comes from the neighboring field of big data analytics. At its launch, Google Flu Trends was heralded as a great leap forward in relation to identifying and estimating the spread of the flu—until it underestimated the 2013 flu season by a whopping 140 percent and was quietly put to rest. Poor data quality was identified as one of the main reasons Google Flu Trends failed. Unreliable or faulty data can wreak havoc on the prediction power of AI.

References:

About the Author:

Bargunan is a Big Data Engineer and a programming enthusiast. His passion is to share his knowledge by writing his experiences about them. He believes “Gaining knowledge is the first step to wisdom and sharing it is the first step to humanity.”

The Crucial Component of Data-driven Organizations

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Sankul Seth

Data is a crucial component for any organization to generate revenue and provide the best-in-class experience for their customers. Various studies have shown that 60% of the organizations fail to implement UI tools, which are heavily dependent on data-driven technologies because organizations spend millions on buying these tools but not investing in the right talent to achieve them. Understanding of data is the first stepping stone for any organization to be data-driven. I implemented various data solutions from inception to implementation, which helped organizations to derive data-driven decisions. After fifteen years of extensive experience across multiple data technologies and platform, I have developed numerous critical data frameworks which have benefited organizations to be data-driven. The first essential pillar is to build a cohesive and robust enterprise data team.

Data Center Consolidation Initiative Services

Data is a driver for any business intelligence, analytics, insights, marketing campaigns, UI applications, tools, and technologies. It’s crucial to understand why and what the business needs before deciding to invest in any data technologies. Today, organizations are leveraging data for executing campaigns and defining customer 360-degree views to provide personalized and OMNI-channel experience using data KPIs. There are unlimited data tools available, and it became difficult to pick the right one, which fits all the requirements for the business and delivers a perfect solution. It all goes back to find the right leader who has deep experience on both sides of the coin (Business and Technology). It’s hard to find such talent but not impossible, and this decides the success or failure of any data implementation projects.

About the Author:

Sankul is the Vice President of the Enterprise Data Team at PSCU. is a value-driven and business-oriented data and IT technology leader with a proven track record for building enterprise applications and data-driven platforms. He believes the current generation and future leaders should be focused and good listeners, as it helps to perceive and deliver solutions.