BDD – Be Agile, Create Value & Build Highly Visible Test Automation

Everybody likes to complete things in their own specific manner. However, when it comes to software programming, it would always be beneficial in having a set of principles for each phase of software development.

Opening the discussion and keeping various technical teams on the same note can allow software to work seamlessly. As organizations move towards coding phase they need to adjust the procedures to fit their present work processes. So what is it that can define user behaviour prior to writing test automation scripts?

That is called BDD (Behaviour Driven Development).

What is BDD?

BDD is a development process, which explains the behaviour of an application for the end user. It is an extension of TDD (Test Driven Development). In BDD, the behaviour of the user is defined and converted to automated scripts to run against a functional code. These test scripts are written in a business readable and domain specific language known as Gherkin, which ultimately reduces a risk of developing a code. Following are some of the points, which clearly outline the value of BDD.

1. BDD is not testing, it is a process of developing a software. It considers questions like ‘where to start in the testing process; what to test and what not to; how much to test in one instance; what to name the tests and how to understand when and why it fails. It is what can be called a rethinking of unit testing and acceptance testing.

2. Before BDD, TDD had tests that were developed first and failed until a functional code was arrived at. This point was when a test was considered to have passed. This enhanced with BDD, where the tests were written in a specific format.

3. Since the language used in BDD was domain specific the requirements are now more real time and meaningful, where all stake holders are on the same page, as opposed to the earlier ‘ only developer and tester friendly’ ones.

4. BDD does not change/replace traditional UI automation tools like selenium or appium.

5. In terms of test automation, it represents a presentation layer, in other words it can present data in a clear-cut manner and in a standardized format.

As you can clearly see, BDD has nothing to do with the technical side of the Testing, let us try to understand why and how BDD is important.

BDD helps bridge the communication gap between clients, developers and other stakeholders.

Collaboration – In traditional testing, nobody would recognize what part of the test/scenario was failing. With the BDD approach, everyone including stakeholders, product team and developers understand testing, making it a win-win situation for organizations.

Requirement Change Management – Traditionally, the requirements clarity were logged in collaboration tools like Jira or other project management tools. With BDD, any changes in requirements would automatically be documented as tests.

Test Management Tools – In traditional method, test management was separate and were automated and manually marked within the test repository. But, with the advent of BDD tools, static metrics such as “#” of specs, “#” of scenarios are collected automatically. Furthermore, other test metrics can effectively be expanded.

Single Source of Truth – Traditionally, requirements would be transferred from project management to test management, and finally to automation. With BDD, in a mature agile process, specs are written correctly in Jira and can serve as source of truth. This is in contrast to testers reading requirements.

Phases of BDD

The overall BDD process involves two important phases – Process insights & Tools/Technologies. Let us look in detail how vital Process insights & Tools/Technologies are when it comes to BDD process.

a.  Process Insights

To benefit from BDD based test automation, it is imperative to have process overarching Planning, BDD Design and Test Automation Framework.

Planning – Priority based stories/features should be picked up for automation.  Undertaking  an iterative discussion helps to know what activities would be beneficial to ongoing automation efforts.  For best results, effort estimation could be followed up by stabilization of test automation activity instead of the usual factory approach, if the product is still evolving.

BDD Design – It is recommended that, scenarios be designed by QA/BA rather than Quality Engineers. This is instinctively due to fact that they are owners of product quality. In addition to this, principle of collaboration mandates that, they own up this part of automation effort.

Also the scenarios should be reviewed from the point of functional flow, behavior semantics and step reusability by all concerned stakeholders – QA, BA and Engineers. Review process should be a de-facto part of design process.

Test Automation Framework – BDD design ensures that reusability is complemented by the implementation component. Standard automation and development practices must be followed to ensure efficient output.

b. Technologies/ Tools

Some automation tools that support BDD are listed below:

Platform BDD Tool
Java JBehave, Cucumber, Gauge
C# SpecFlow
Python Behave
Ruby Cucumber
Javascript GaugeJS
PHP Behat

Apart from automation tools, Test Management based on BDD test designs play an important role. There are tools like TestRail, HipTest, which now support BDD based test editor functionality and guarantee better integration of processes and implementation.

Business Benefits

Once the Process insights & Tools/Technologies are in-sync, BDD automatically offers benefits:

  • Know What You Test (KWYT) – Since testing is not performed in isolation, continuous tracking and reading of what is being tested becomes possible. Coverages cannot be missed and product owners can now chip in proactively if something is being missed.
  • High Visibility – Due to collaboration, the tests, their quality and their results are visible to all management stakeholders which gives confidence in taking decisions for product releases.


Behaviour Driven Development helps in building quality and creating value. Instead of having tests that are only useful for engineers, BDD aims at tests useful for all. Additionally, it improves the partnership between the parties and allows developers to get a clearer scope of essential features and the customer gets a better knowledge of what will be delivered, with accurate estimates.

Nitor excels at streamlining and operationalizing BDD Based Test Automation through its ready-to-use frameworks, successfully employed strategies and efficient use of tools/technologies.

If you are interested in finding out more about BDD, write to us at

Boost your business foundation with Microsoft Dynamics xRM

Regardless of what industry your company works, clients are your most vital resource and handling those client relationships is the establishment for developing your business. Additionally, plenty of the organizations look for CRM to manage sales, customer service and marketing. A CRM (Client Relationship Management) software can help gather, sort and deal with the majority of your client information, and is integrated from finance to operations.

One such CRM, Microsoft Dynamics, is one of the most popular tools in the market. Not only does it meet the needs as well as the budgets of smaller, middle-sized and large organizations but it also makes marketing more effective and assists you in getting more out of your customer relationships. Furthermore, Microsoft Dynamics CRM offers the flexibility of both on-demand and on-premise deployments. Additionally, the powerful CRM program offers unparalleled integration with Microsoft Office suite, Microsoft SQL Server, Microsoft Exchange Server, and Microsoft SharePoint, some of the most widespread applications in the business world.

Do you need a Software that is a Step ahead?

A term often associated with CRM, with a twist- is– ‘xRM’ or ‘eXtreme Relationship Management’. xRM is nothing but an extension to CRM, if your organization deals with policies, property taxes, building assets and list goes on. With xRM you can manage the relationship of anything within your company. Additionally, xRM is ‘extended Relationship Management’, which represents the extension of CRM platforms allowing organizations to thrive by helping them manage employees, process, suppliers, assets and much more.

An XRM has a several key components, which can give a strategic approach to building a unified system that connects all aspects of a business together. Following are the XRM components:

1. Entities & Records

2. Fields

3. Forms

4. Web Resources

5. Workflow Processes

6. Plugins

7. Web Services

As you can clearly see, the above components are essential to manage xRM. However, the question remains is, is it useful to deploy a solution like xRM? Will organizations reap any benefit out of it? Or is it just a fad? Well, to answer that honestly xRM is necessary if you already have the CRM within your organization. It has several crucial advantages, which can be vital for developers as well as for organization.

What is in it for Developers/Organizations?

These days there is little time to write a lot of custom code to deliver solutions. With xRM, developers can aim to develop applications rapidly. To meet requirements for business applications, xRM has a framework that provides the agility and flexibility to adapt to changes and get user acceptance and adoption.

From an organization’s point of view, when you take Dynamics 365 and utilize it as a stage for building an XRM system, you get a rock-solid foundation on which to build ‘line-of-business’ (LOB) solutions. Everything can be tailored according to your company’s need and incorporated smoothly with other critical systems.

xRM solutions offer flexibility and customization to meet almost any business or organizational need. Integrating an xRM solution with the Microsoft Dynamics CRM will provide you with several important advantages.

Automation at its best – Microsoft Dynamics integration with xRM automates important tasks that employees would otherwise have to complete manually.

Rapid deployment – Developers do not have to worry about building an LOB software from scratch, as software plugins extend the functionality of the core Microsoft Dynamics CRM system.

Robust Security – Another key advantage is that xRM provides robust security features. It has security roles for users and objects that restrict access to sensitive data, SSL connections for data transfer, and more.

Native Integration – xRM solutions can connect existing systems to CRM, freeing data trapped in outdated systems. Microsoft Dynamics CRM also provides native integration with Microsoft SharePoint® and Microsoft Office® applications including Outlook®, Excel®, and Word.

We at Nitor take pride in our xRM solution capabilities. We specialize in xRM plug-in development, OOTB customizations and creating custom workflows to benefit your organizational requirements.

Find out how xRM would eliminate silos and build a unified marketing & sales funnel, write to us at

Dynamic Data Masking: It’s time to secure and transform your data

What is Dynamic Data Masking?

According to Microsoft Dynamic data masking helps prevent unauthorized access to sensitive data by enabling customers to designate how much of the sensitive data to reveal with minimal impact on the application layer. DDM can be configured on the database to hide sensitive data in the result sets of queries over designated database fields, while the data in the database is not changed. It does not encrypt the data, and a knowledgeable SQL user can defeat it.

In any case, it comes with a basic method to administer from the database, what information the different clients of a database application can and cannot see, making it a valuable tool for the developer. Having said the above Dynamic data masking needs a proper implementation. Let us look at how exactly the Dynamic data masking is implemented:

  • To implement DDM, you define masking rules on the columns that contain the data you want to protect. 
  • For each column, you add the MASKED WITH clause to the column definition, using the following syntax:

    MASKED WITH (FUNCTION = ‘<em><function></em>(<em><arguments></em>)’)

  • Dynamic data masking limits (DDM) sensitive data exposure by masking it to non-privileged users. It can be used to greatly simplify the design and coding of security in your application.
  • Dynamic data masking helps prevent unauthorized access to sensitive data by enabling customers to designate how much of the sensitive data to reveal with minimal impact on the application layer. This can be turned into the server as possible
  • DDM can be configured on the database to hide sensitive data in the result sets of queries over designated database fields, while the data in the database is not changed.
  • Dynamic data masking is easy to use with existing applications, since masking rules are applied in the query results.

To summarize, when it comes to sensitive fields in the database, a centralized data masking policy acts directly. Additionally, it assigns personal roles or users that do not have access to the sensitive data. DDM features full masking and partial masking functions, as well as a random mask for numeric data.

What makes Dynamic Data Masking Special?

As you can clearly see, the data masking practice is vital and can help address organization with data breaches. Here are some of the additional dynamic data masking benefits, which organizations need to look at:

  • Regulatory Compliance – A strong demand for applications to meet privacy standards recommended by regulating authorities.
  • Sensitive Data Protection – Protects against unauthorized access to sensitive data in the application, and against exposure to developers or DBAs who need access to the production database.
  • Agility and Transparency – Data is masked on the fly, with underlying data in the database remaining intact. Transparent to the application and applied according to user privilege.

As you can clearly see above Dynamic Data Masking has number of benefits for organizations. Similarly, DDM can be an assest when it comes to Developers. Let’s have a look how Developers actually benefit from DDM

  • In DDM, simple and understandable rules are defined to operate on the data. The collection of these rules performs a series of known, tested and repeatable actions at the push of a button.
  • Data Masker handles even the most intricate data structures. It can preserve data relationships between rows in tables, between rows in the same table or even internally between columns in the same row
  • Data synchronization issues of this type can be automatically handled by the addition of simple, easily configured masking rules.
  • DDM works easily with tables containing hundreds of millions of rows.


Data security will never not be an issue; it will always be something we have to stay on top of.  However, with some of these practices in place we can avoid the at least giving the data away.

Information security is a never-ending issue; it will always be something we have to stay on top of. Dynamic data masking at least gives us a comfort zone where we can avoid at least giving the data away. Additionally, it minimizes the risk of accidental data leakage and dynamic obfuscation of sensitive data in the database responses.

Nitor’s Dynamic data masking services enables customers to focus on sensitive data elements in the desired databases. Our key objective is to provide customers with a working data masking solution while helping them establish knowledge and confidence. Additionally, we also believe that Dynamic Data Masking is complementary to other security features in SQL Database (e.g., auditing, encryption, RLS) and should be used as part of a comprehensive access control and data protection strategy.

To learn which implementation option best meets your organizations data masking needs please contact

Are you planning to migrate from your Healthcare legacy systems to a modern system? – Here are the things to keep in mind

Healthcare Technology is ever changing; the design and platform used nowadays could very well become redundant after 2 to 5 years. The increased use of automation within healthcare is not helping, as organizations are required to take immediate action to migrate and replace discontinued legacy systems.

For organizations, migrating from old architecture to the latest technology is difficult as it requires careful consideration. Furthermore, management needs to understand whether relocation requires migration of data into a new system, migration of application functionality, or both.

Migrating the healthcare legacy system to a modern system is like a sticky wicket. It involves the migration of principal business applications—functions that are deeply rooted in a healthcare organization’s workflow. Furthermore, they can also be difficult, as they involve numerous clinical and business systems, and require a major upfront investment in hardware or software that may lack immediate ROI.

Addressing these challenges strategically is difficult. The most taxing is the maintenance of service line support while the migration is underway. Let us look at some of the common concerns expressed by CIOs during migration.

Most common concerns expressed by CIO during such an activity:

  • What could be the go-to market time?
  • Will the workflow change?
  • How will the UI changes affect the existing users?
  • How much of the architecture could be re-used?
  • Will users need additional training before using the system?
  • How scalable is the new technology for future changes?

However, there is always a path and a positive side to the story. There is no need to panic about the excitement in migrating from legacy to a modern system. Migration is actually a logical process and is much simpler than widely thought of.

Let us divide the whole migration process into 4 logical parts:

  1. Migration planning
  2. Analysis and project planning
  3. Architecture, solution designing and development
  4. Comprehensive Testing and deployment
  • Migration Planning

One of the most important steps in migrating from a legacy system to a modern system is Migration planning. This includes pre-planning, impact analysis & technology expertise. Furthermore, identification & planning of resources according to skill sets is required as per project needs. Security governance can be critical when it comes to application sanity. Security governance should specify the accountability framework and provide oversight to ensure that risk is mitigated.

Additionally, configuration management documents including mapping, interface specifics, and detailing should be part of migration planning. This allows developers to understand the application easily. If done properly, organizations can understand whether the workflow will change.

  • Analysis and Project Planning

Like migration planning, analysis and project planning plays a pivotal role in technology migration. One major factor of project planning is the stakeholder communication plan, which helps in overall project integrity. A thorough analysis of the project will ensure that a project cost and go-to-market timeline are defined.

Moreover, some important documents, which need to be factored during project planning, include: Backlog of epics/features and project documentation including conflict management, RTM (Requirement Traceability Matrix), hardware and software specifics with NFR, creating a data dictionary, and source-target mapping at minimum.

  • Architecting, Solution Designing and Development

After analysis and project planning comes the important step of architecting, solution designing and development. During this phase, the documents that need to be created are: mapping design specification, data quality matrix and interface design specification. These documents help in taking appropriate decisions about the feasibility of the technology. Furthermore, hardware requirements and technology specifics can be finalized after due deliberation and comparative analysis. The overall phase helps in determining architectural reuse, UI changes and the scalability of the selected technology for future changes.

Prioritization development follows the completion of this phase.

  • Comprehensive Testing and Deployment

After the completion of the development phase comes the final stage, QA and testing. In order to have a bug-free application, the organization should have thorough testing documentation and a QA strategy. Testing of migration with dummy records and a live environment should be carried out for each module. Simultaneously, developing an independent migration validation engine is optional as per business need. In addition, a user manual helps a user to understand the system.

Every CIO should plan the above phases required in migration and ensure that every point discussed above is planned properly.

An experienced organization, which has worked on technology migration in past, holds the edge over a newbie because migration is not as simple as it looks. It needs lot of thought when it comes to solution design, architecture finalization, technology selection, security governance and quality assurance. All this purely comes with experience.

If you have technology migration on your mind and need help to get started, please reach out to

WebAssembly – Smart technology platform on the block

Since the last decade, JavaScript has been unable to ease the developer burden due to its dynamic nature. Furthermore, for applications in which performance is critical, Javascript is not fast enough. For areas in which significant engineering effort is required in another language, it may not make sense to convert to JavaScript.

Clearly, the need of the hour was to get a cutting-edge technology platform. Technologists found the answer in June 2015, when engineers on the WebKit project, along with Google, Microsoft and Mozilla announced that they were launching WebAssembly. WebAssembly is a new binary format for compiling applications from the web. The idea behind launching WebAssembly was to make it portable bytecode, which can be effective for browsers to download and load.

So what exactly is WebAssembly?

According to, WebAssembly (abbreviated Wasm) is a binary instruction format for a stack-based virtual machine. Wasm is designed to be a portable target for the compilation of high-level languages like C/C++/Rust, enabling deployment on the web for client and server applications. Following are the features of the WebAssembly:

  • Fast Execution
  • Useful in CPU-intensive operation
  •  Support for old & new Browsers
  • Secure

WebAssembly is still new, but it is supported in all major browsers such as Chrome, FireFox, Edge, Safari, etc.  Additionally, legacy browsers can be supported with the help of Asm.js. Below is the representation of how WebAssembly works.

                    (Source of the Diagram:

WebAssembly is a relatively new technology. As a result, creating complex applications using this language can be challenging. To understand it better, here are some of the key WebAssembly concepts you need to remember:

  • Module

Represents a WebAssembly binary that has been compiled by the browser into executable machine code.

  • Memory

A resizable array buffer that contains the linear array of bytes read and written by WebAssembly’s low-level memory access instructions.

  • Table

A resizable typed array of references (e.g. to functions) that could not otherwise be stored as raw bytes in Memory (for safety and portability reasons).

  • Instance

A Module paired with all the state it uses at runtime including a Memory, Table, and set of imported values.  An Instance is like an ES2015 module that has been loaded into a particular global with a particular set of imports.

In some ways, WebAssembly gives more power to the web developer. In addition, it changes the dynamics of the web, giving that additional advantage due to its near-native speed.

Some of the advantages include:

Effective and Rapid

WebAssembly performs at native speed by taking advantage of common hardware capabilities accessible on various platforms. The Wasm stack machine is structured to be encoded in a size- and load-time-efficient binary format.


Likewise, Javascript, Wasm describes a memory-safe, sandboxed execution environment. However, WebAseembly can enforce the same-origin and permissions security policies of the browsers once embedded in the web.

Open and Debuggable

WebAssembly is designed to look attractive while having a textual format for debugging, testing, experimenting, optimizing, learning, teaching, and writing programs. The textual format will be used when viewing the source of Wasm modules on the web.

Part of the open web platform

WebAssembly is designed to maintain the versionless, feature-tested, and backward-compatible nature of the web. WebAssembly modules will be able to call into and out of the JavaScript context and access browser functionality through the same Web APIs accessible from JavaScript. WebAssembly also supports non-web embedding.

While everyone is very optimistic about the current state of WebAssembly, there are people who are not well versed with its concepts. Here are some important points, which will help you understand WebAssembly better:

Be very clear that WebAssembly is not Java Applet/Active x, which are plugins. The browser natively supports WebAssembly and it is executed by the same virtual machine, which executes JavaScript. It runs in the same sandbox environment as JavaScript runs. Furthermore, WebAssembly is not a security risk. If you do not consider JavaScript as a security risk, then you should not be worried about WebAssembly as it runs on the same sandbox.

Most importantly, you should know that WebAssembly can not fully manipulate the DOM. It cannot directly access the DOM, but it can call out into JavaScript, and JS can then work on the DOM. Also, lot of people are keen on knowing which languages WebAssembly supports. Currently WebAssembly supports c and c++. Rust is also supporting Webassembly. There are also open source projects, which will add support for garbage collected languages such as C# and Java. Blazor is one such project that enables the development of WebAssembly through c#.


WebAssembly is a promising technology. It is web standard and supported by the most browsers. Nitor’s developers have started taking advantage of this technology where performance is critical. Obviously, there are some limitations for now but as technology evolves, they can be overcome.

Nitor thinks WebAssembly is going to do more of what a modern web browser already does: It is turning out to be a proper, cross-language target for compilers, aiming at supporting all necessary features for making a great all-round platform.


Blockchain: Revolutionizing Healthcare Management Technology

Blockchain technology in healthcare has the potential to transform healthcare, placing the patient at the center. Organizations have started to invest in research and POCs as Blockchain has the potential to connect fragmented systems to generate insights and to better assess the value of care. According to Gartner, about 20% of healthcare providers and payers will have use cases for healthcare settings; the business value addition of this emerging Blockchain technology will exceed $176 billion by 2025, and $3.1 trillion by 2030.

A Blockchain-powered system can dramatically simplify the data acquisition process. It allow the user to upload data directly to the system and give an individual permission to use his data if it was bought through the system using a transparent price formula determined by data value model. In addition, it guarantees fair tracking of all data usage activity.

Let us look at some use cases where Blockchain has been making an impact in healthcare:

  • Health Records: The problem with the health system is that the patient record is scattered across various health systems during the patient’s journey. Blockchain is interesting and reliable as it is easy to track the health record scattered across multiple systems with its data integration ability between proprietary systems. Additionally, it has an innate quality of holding the fragmented health records. Blockchain could very well become a standard in healthcare interoperability.
  • Data Security: Since the crux of Blockchain is that the information is distributed at various locations, it guarantees that a large number of providers can behold the trust of data safeguard without exposing any private patient/consumer data.
  • Revenue Cycle, Reconciliation & Fraud: The complex nature of today’s health system means that millions of dollars are spent annually trying to figure out which patient received what service from which service provider. Blockchain could potentially form the foundation of a high-integrity tracking capability that is updated in a near instantaneous manner. This would lead to much fewer errors (with both financial and patient care upsides), substantially reduce fraud, and save on administrative costs.
  • Network Contract and Performance Management cross Partner System: Blockchain’s architecture helps in optimization of the network across partner systems, thus helping healthcare organizations scale.

 Healthcare CIOs need to realize that Blockchain technology is new and yet to develop fully. Early adopters will, however, reap benefits by operationalizing Blockchain in the organization, as it will create unique opportunities to reduce complexities.

There are a few things which CIOs must consider while adopting Blockchain into their organization such as reviewing their business model, processes and regulatory requirements, suitability with their business need, up to what extent they require to use Blockchain and so on. The diagram below (Source: Gartner) depicts the decision tree to be adopted for Organizations.

Diagram – Decision tree logic for adopting Blockchain (Source and Copyright: Gartner)

Most common questions faced by Healthcare CIO while thinking of adopting blockchain are:

  • To what extent do I rely on Blockchain?
  • Healthcare data is distributed so how easy will it be for me to implement Blockchain?
  • How to adopt Blockchain in the organization?
  • What is the relevant use case for my organization?
  • To what level will I need architectural changes if I were to implement the Blockchain?
  • How could I use it for interoperability?
  • What should be my strategy to ensure data security?

Keeping the above challenges in mind, some of the mitigation strategies that we adopted for data security and interoperability were using consortium Blockchain ICO and Exchanges – wherein a special access layer protocol was used taking care of data security providing more control with whom information should be shared. Taking into consideration all the capabilities of Blockchain and our expertise in the healthcare industry, we believe that it has capability to become a pivotal innovation.


Let us know if your organization faces any of the above challenges! For more information, reach out to us at

GitHub Acquisition: Reconciling GitHub with Microsoft

Microsoft’s most recent business move has shrouded the developer community in a state of wariness. GitHub, a popular open source code collaboration platform for developers and scientists (basically anyone working with data), was acquired by the tech behemoth for $7.5 billion. This figure represents an amount thirty times (!) GitHub’s annual recurring revenue.

Before the acquisition, GitHub suffered from multiple issues. These included serious monetary and leadership problems. GitHub narrowed solutions down to two options: the first was to hire a new CEO to streamline the company’s business direction and thus gain invaluable funding opportunities. The second option was to be acquired. GitHub chose this easier, faster path.

The optimal candidates to be acquired by were companies with access to large enterprise customers/subscriptions. This insight is derived from GitHub’s revenue model; GitHub is free for individuals but requires enterprise users to pay. Google, Amazon and Microsoft were among the

companies enticing GitHub with offers of acquisition. In the end, GitHub decided to go with Microsoft because of the tech titan’s more generous value offering. GitHub was also fully aware of Microsoft’s increased appreciation of open source (especially with Satya Nadella as CEO) and of its desire to show this to the world.

In this situation, Microsoft had an excellent opportunity to advance their own interests. First was the opportunity to show the world their transition from a propriety/monopoly based business to an open source model. Next was the all-important target of grabbing networking opportunities. Microsoft acquired LinkedIn in 2016, which enabled access to a network of professionals. With the acquisition of GitHub, Microsoft now has access to a network of developers. With this access to the largest pool of developer mindshare, they can compete with the likes of Facebook. With GitHub being the one of the largest code repositories, Microsoft can easily monitor new projects, interests, technologies, and market trends to stay ahead of the competition. Microsoft can also capitalize on an opportunity to woo developers more effectively by creating more offers and generating value, for example by creating attractive Microsoft based tool chains in open source to gain traction towards Microsoft technology. Lastly, the acquisition may have been an exercise in building strategic value. The strategic value – which pertains to how a certain company’s offerings help a different company (usually larger) to be successful – of GitHub, is essentially in the 85 million repositories and 28 million developers it hosts worldwide. It is not difficult to imagine the value of access to these developers, who regularly use GitHub’s code repository products, especially when the developers can be installed in Microsoft’s immensely profitable developer environment.

Microsoft’s long history of generally running counter to open source software, however, has led to lukewarm reactions from the developer community. Many developers feel that despite Microsoft’s attempts to foster acceptance toward an open source culture, Microsoft is not good for GitHub. This comes from GitHub’s initial premise of hosting distributed version control for remote coding for a flexible coding experience that could boost a developer’s community presence. Behind the developers’ tepid reactions are fears that Microsoft might leverage or co-opt their code for future products, or that the developers will be muscled into using only Microsoft products. Additionally, there are some direct conflicts between Microsoft and GitHub. For example, there are certain GitHub projects that are Xbox simulators. It is quite likely that Microsoft will kill these projects. There are even rumors that Microsoft may add tracking or advertisements to GitHub’s sites. There has thus been an upsurge in developers shifting their code to GitLab, one of GitHub’s prime competitors. In all fairness, however, this might be a reaction to a temporary fear.

So what is the future for GitHub? Looks like only time will tell.

AI and ML: The Next big leap towards innovative patient pro-active participation

In the year 1955, the computer scientist ‘John McCarthy’ coined the term ‘Artificial Intelligence’. From 1955 to 2005 computer scientist mostly used ‘Artificial Intelligence’ for research purpose. Additionally, they also checked if AI could be implemented across different industries.

In the year 2011, Apple introduced ‘Siri’ into the market and quickly the whole world started thinking about AI to solve the day-to-day activities. The recent example of this is ‘Google Duplex’, which can help to book an appointment by using AI and Machine learning technologies.

Similar to other industries, many companies in the healthcare market are investing a lot on AI and Machine Learning to enhance the quality of care, operations and engagement. Many healthcare IT companies are investing a lot in tech space for getting more data insights, enhance the virtual care and move patient’s risk zone from ‘At Risk’ to ‘Healthy’. For Healthcare community enhancing patient engagement has become the topmost priority. Artificial intelligence can certainly play an important role in achieving those outcomes.

Why AI is required in Patient Engagement

As healthcare industry is moving from FFS (fee For Service) to value-based system, the patient should be aligned to the centre position to get a better quality of service at minimum healthcare cost. To achieve this alignment, patient engagement tool is vital, which helps patients, providers and payers. In last 8 to 10 years, we have observed remarkable progress in patient engagement technology, which has been helpful to solve multiple challenges like access to patients about their patient info, web/ mobile based scheduling, communication with caregivers and many more. On the other hand, patient engagement still faces many challenges that need to be addressed. Some of the challenges are below:

  • More patient information to capture (habits, behaviour trend, emotional quotient, etc.)
  • Capture patient info before appointment though HRA (Health Risk Assessment)
  • Not having personalized healthcare education
  • Not having personalized care plan and tracking of the care plan

Current patient engagement processes are allowing patient to participate in care delivery. But this participation is only restricted when system/app informs them to participate (feed the questionnaire, upload reports etc.). Moreover, the patient should participate more ‘Pro-Actively’ in care delivery process. In an ideal scenario, patient should participate in care delivery process in form of suggestions, sharing their thoughts/emotions/ feelings/symptoms, feedback about physicians, etc.

Patient Engagement: Access-> participation-> Pro-Active participation

For last 5-6 years, the penetration of web and mobile patient portals has increased at the moderate pace. However, the patient data these systems are generating is humongous and we are not utilizing it for ‘Pro-Active Patient participation’. Let us look at how patient engagement has evolved over a period of time, and how is going to look like in the near future.


Tomorrow’s Patient Engagement

While implementing ‘Pro-Active patient Participation’, technologies like AI and ML will be used for data aggregation, data analysis and extracting deeper insights.

Most of the providers have started online appointment scheduling for their patients. In upcoming months, we can use AI and ML to automate the scheduling part, which could be helpful to reduce the admin cost of providers. At the time of scheduling, one can extract detailed patient information through personalized health risk assessment by using AI technologies. In the current patient world, nearly 74% patients forget their care plan after leaving doctor’s appointment. To reduce the percentages health systems should suggest personalize care plan to physicians based on aggregated data from multiple data sources.

Technology acts as a bridge between caregivers and patients to connect patients at the personal level and improve their health. ‘Pro-active patient engagement’ is the way forward to achieve the goal. It is quite evident how advanced technologies are helpful for building powerful patient engagement solutions.

In the future, during care plan tracking, personalized AI based patient education will be the key to boost ‘Pro-Active patient Participation’. These advance patient engagement activities will be helpful for better ‘Patient – Physician’ relationship.

Now that it is established that AI and ML will be a win-win for every healthcare entity, when are you planning to implement AI-ML techniques to enhance your quality of care? If you would like to find out more, feel free to write to us at

The Health Pivot Framework – The Next-gen Paradigm of Rule Engine

In our previous blogs, we discussed the industry challenges and how rule engines help overcome those challenges; we also elaborated upon the characteristics of  an ideal rule engine and factors that any CIO should consider when choosing a rule engine.

We had a quick introduction to  Health Pivot – a new age ideal rule engine that could very well be a solution for the most pertinent healthcare industry challenges. Health Pivot helps users define business rules, an operational environment that can apply and execute those rules in software to enable automated decisions, and tools to help teams monitor and maintain the effectiveness of sets of rules in response to changing healthcare situations or requirements.

Additionally, Health Pivot comes with the ability to collate data from multiple sources in  multiple formats. At the same time, it allows the maintenance of data quality while educating the user about data consistency and missing fields in the data, therefore making Health Pivot a topmost choice for any healthcare CIO. Health Pivot plays a major role in improving health outcomes. It delivers the efficiency and agility needed for better health care, lower costs, and rapid response to change.

In addition to the usual Rule Engine qualities you can find anywhere, there are features specific to Health Pivot.  Let us look at the features Health Pivot offers making it a standout Healthcare Rule Engine:

  Maintain Patient Information

Set the rules for comprehensive patient profiles including demographic data, claims records, and authorization data as well as a full clinical profile.

Develop Case Management

Create and deliver the most effective, personalized treatment plan for the patient condition while setting flexible rules.

Set Emergency Alerts

Streamline patient tasks and interactions, including authorizations and pre-authorizations, notifications, alerts, interventions and correspondence.

View Real-time Information

 Identify, evaluate and engage customers to take action to close gaps in care. Get detailed insights and compliance tools, including population stratification, predictive modelling integration, program assessment and audit.

Choose Flexible Visualization

Choose any visualization layer according to the  business needs for displaying real-time dashboard and ad-hoc reports. Get tailored reports, providing insights on performance and regulatory compliances.

So where is Health Pivot’s sweet spot? The framework is particularly applicable to operational, financial & clinical decision-making.

Following are some of the Health Pivot benefits, which ensure Healthcare transformation.

 Health Pivot Sweet Spot: Financial, Clinical and Operational

 Ease of Operation

The most important part of  Health Pivot is ease of use. It comes with a simple drag and drop functionality to choose fields for the rule and arithmetic operations that can be performed swiftly. Health Pivot drastically reduces operation time by informing the user if the chosen fields carry data. This means that the user is not compelled to wait until rule execution to find that the field is empty.

Ease of Finance

 Using Health Pivot, you can easily set financial rules relating to accounts receivable, accounts payable, patient receivable and run various financial reports based on business needs.

Ease of Patient Management

 Health Pivot gives you the flexibility of various clinical rules such as alerts on patients’ vitals going beyond the certain range, allergy alerts, CDSS alerts, vaccination alerts, etc.

Here is How Health Pivot Works

Benefits of Health Pivot Across the Healthcare Industry

Now that you have seen how and where Health Pivot can deliver business value, let us explore how exactly it is going to benefit the healthcare industry.

Rule Engine is the  necessity of the hour in the US healthcare IT world, and Health Pivot is an ideal solution to deal with the industry challenges.

Applying Health Pivot to businesses will be beneficial in more than one respect, as it will solve multiple business cases. In case of providers, it will take care of regulatory reporting such as MACRA-MIPS. Smartness of Health Pivot will recommend provider’s rules, which will be best suited viewing  the data sets, helping focus more on the patient.

It does not stop here as providers can also set custom rules, such as alerts, according to  business needs . Additionally, some of the most popular use cases used in daily operations include patients’ vitals going beyond a certain range, accounts receivable reminder, account payable reminder, patient’s collection reminder and many more.

For payers, it is not any different when it comes to HEDIS regulatory reporting, as it could easily take care of custom rules set for members, providers, financials etc.

As you can clearly see, Health pivot is very smart and healthy proposition for entire healthcare industry. Health Pivot as a framework fares better than any other Rule Engine because of its capability to be flexible and scalable as per any organizational requirement. While Rule Engines as packaged solutions lack customization capabilities, our Health Pivot framework can blend into any solution that your organization requires.

 However, what happens when it is compared with other Rule Engines available in the market?

Let us see how Health Pivot shapes up when compared to other Rule Engines:

Health Pivot Vs Other Rule Engines

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Rule Engine: The next leap towards healthcare transformation

We clearly discussed in our last blog that the healthcare industry is experiencing a period of unprecedented change. Rising above all the chaos, Rule Engine is trying to bring lasting improvements in healthcare while minimizing expenditure. It might not be immediate, but a Rule Engine can play a pivotal part in improving operational flexibility for organizations. So what exactly is an ideal Rule Engine?

The Ideal Rule Engine

The term Rule Engine may sometimes sound confusing, as it can be any system that uses rules, in any form that can be applied to data to produce outcomes. This includes simple systems like form validation and dynamic expression engines. Many tools and technologies are used when it comes to engineering a rule engine such as Drools, JBoss, jBPM. They use expressions and delegates in its decision nodes, which control the transitions in a Workflow. It becomes confusing as to which rule engine suffices the need of the business.

An ideal Rule Engine should collate data from multiple sources, ensure data quality and allow the user to create a rule as per business needs. Business rule management gives an additional advantage over a general-purpose Rule Engine, as it provides an advantage for the custom rule creation, analysis, data collaboration, multi-facet collaboration, management, visualization of charts and graphs. For instance, what if a rule engine suggests to the user which rules can be created when multiple data sets have collaborated. Does this scenario sound helpful when it comes to regulatory reporting such as MACRA-MIPS and HEDIS reporting?

While a lot of Engines in market claim to be an ideal Rule Engine, following are some important factors that need to be taken into contention by CIO’s.

Factors to consider when selecting a rule-engine

Some of the very popular Rule Engines in the healthcare IT world does not provide flexibility to create own rules easily, and visualization has its own limitations as it is not in the user’s control. It also lacks the recommendation or suggestion part wherein a user can know which of the rules are feasible at the time of creation.

Important factors influencing CIO’s decision to choose a rule engine depends on how fast a rule engine can adopt to the existing workflow. An ideal Rule Engine allows to collate data from multiple sources, provides flexibility to create own customized rules.

You should explore the following capabilities in particular:

  • Is it easy for non-technical users to author rules?
  • Can authors use tools in collaboration with each other, or do they each have to work separately using their own individual tools?
  • Does it suggest what rules can be applied and does it provide visualization as per the choice of the user?
  • Can the engine quickly determine which rules or rulesets to apply based on the nature of the data?
  • How well the Rule Engine works when it comes to the data security?

The most important point to keep in mind – no single rule engine allows regulatory reporting and helps create rules of choice as per business need. It means that organization must have more than one Rule Engine and should keep different workflows in mind. Performance is also a big issue in some of the popular rule engine since it does not foresee that data could become so large.

What if we told you that there is an ideal rule engine that can take care of regulatory reporting and custom rule creation. In addition, it can take care of data collaboration from multiple sources, data security and ensure that performance is not hampered at any given time.

In future, technologies such as machine learning, artificial intelligence (AI) & robotic process automation will play an important role in Rule Engine – as it evolves from the current state. Furthermore, workflows will become more automated with minimum manual intervention. Nitor’s futuristic Rule Engine known as Health Pivot is one of the forerunners in applying AI-ML & RPA based concepts.

Health Pivot is a new generation ideal rule engine framework – which gives flexibility even for a non-technical person to create own rules and has the pre-defined rule to choose from a list of for regulatory reporting. It can easily collate data from multiple sources and ensure data quality as well.

In our next blog, we will discuss Health Pivot in detail, till the time stay tuned.