Latest Trends and Insights in Big Data Analytics

Are you Leveraging the Latest Trends and Insights in Big Data Analytics?

Majority of the firms are striving to leverage big data for their business insights. However, as technology advances the analytics capabilities tend to progress, a paradigm shift is underway moving to a more holistic system of engagement through applying big data—the new look at analytics for enhancing business performance, customer experience and operational efficiency.The progressive use of big data will influence the way that companies understand and use business intelligence. Some of the big data and analytics trends include innovative concepts, mix and merge of various computer technologies that are based exclusively on big data.

Translytical Systems- Merging Transactional Operations and Analytics
Making real-time decisions on operational or transactional data for applications and time-sensitive services requires the combination of operational and analytical systems. This requirement has given birth to modern enterprise architecture, merging OLTP (CRM, ERP, etc.) with OLAP (BI, data warehouse, etc.) systems.A hybridised transactional-analytical data processing platform unlocks the door for unique operational applications like hyper-personalised recommendations, content, dynamic pricing, Real-time business process optimisation, Real-time fraud analysis, and Predictive maintenance.

The translytical trend is particularly evident, with the growth of digital banking. As per the current scenario, the corresponding business influences are data-driven enhancements in information monetisation, customer experience, and operational efficiency.

Data as a Service

Data is stored in data stores, developed in order to obtain by specific applications. When the SaaS (software as a service) was familiar, DaaS was only a beginning. As with SaaS applications, DaaS uses the cloud technology to provide users and applications with on-demand information access without depending on where the applications or users may be.Data as a Service is one of the modern trends in big data and analytics and will deliver it easier for analysts to retrieve data for business review tasks and simpler for a firm or industry to share data.

Predictive Analytics

Big data analytics has always been a primary approach for firms to become a competing edge and to achieve their goals. They apply fundamental analytics tools to prepare big data and identify the causes of why particular issues arise. Predictive methods are executed to examine current data and past events to know customers and identify potential hazards and events for a business. Predictive analysis in big data is able to predict what may happen in the future.

This strategy is remarkably effective in correcting analysed collected data to predict the response of the customer. It permits firms to define the steps that they have to practice through recognising a customer’s next move before they do it.

Artificial Intelligence in Big Data Analytics

From the last decade, the use of AI has been increased tremendously. Big data techniques are making use of AI models only for particular tasks. For example, data analysts often use AIs for assistive roles. Such AI usage for augmenting human intelligence rather than changing it, and it is known as Augmented Intelligence. Augmented intelligence is one of the critical features of Artificial Intelligence to be adopted by the analytics industry, along with Natural Language Processing and Deep Learning that are falling beneath the same umbrella.

Modern learning algorithms are proficient enough to analyse patterns in huge volumes of data sets are ready to enter in the Big Data industry and provide automated decision-making techniques which lead to better data volume exploitation. However, the critical role of these models in association with Deep Learning and Machine Learning would continue the same, to strengthen decisions by giving an assistive role to human intelligence.

Big Data Analytics is Accelerating Digital Transformation

The technology trends are found in several industries, including insurance, financial services, retail & e-Commerce, and telecommunications. It is a clear sign of a comprehensive digital transformation already underway, led by big data and cutting-edge analytics. In turn, higher innovationand new data-driven strategies in the business.

RPA Plays A Vital Role in Digital Transformation and Simplifies Business Processes

RPA (Robotic Process Automation) is considered as a significant technological breakthrough because of its capabilities, and it is commercially viable for businesses. As such, many firms are now considering RPA as this technology supports in reducing errors, minimising cost, and improving workforce productivity.

RPA Market Overview
RPA markets are quickly evolving. RPA technology becomes trending in the industry because it offers a fast R.O.I. The number of businesses and industries that gained a clear view of RPA deployment is increased. At present, we can see the more real-world application of RPA and top-classbusinesses experience where bots fit in their workflow process automation.

Opportunities are grown for smart firms to capture the improved power of RPA tool when it is compiled with other distinguished technologies in the field of capture and data extraction, document classification, and Business Process Management (BPM). Moreover, the RPA vendors proceed to plot vital intelligence into bots to communicate the great value of intelligent automation.

Latest Trends in RPA
To bring extreme value to the market, RPA stimulates productivity enhancements and innovations. As RPA lights in automating routine and repetitive tasks in a firm, the present software bots can manage a growing number of front and back-office business activities. As RPA can adopt in assisted and unassisted machine learning, its functionalities proceed to expand. As a consequence, the potential for RPA will increase in the global market.

RPA Transformation
As businesses are encountering a positive R.O.I with the RPA deployment and integration with accessible platforms in the digital transformation, RPA will change their focus towards Smart Process Automation (SPA). This development will facilitate a smarter business process that works smart in decision making and collecting more intense data visions for further automation. This smart process automation technology will strengthen human capability and will promote businesses to attain more paces in their business processes automation journey.

RPA in Cloud
The companies found an important movement of the RPA solution to the cloud. This transformation will be combined with other business technologies in order to move to the cloud. Most businesses prefer this model since it ensures to minimise further their dependencies on the technical team and possible cost savings through a shared infrastructure.

RPA Role in IoT and Big Data
As more and more devices like mobile phones, tablets, the wearable devices, and industrial equipment are linked through IoT, there is an extensive amount of data in both unstructured and structured forms that can call the big data. The development in RPA technology delivers the bot to participate in the big data analysis as they can monitor along with recording their steps during implementation.

RPA also plays a vital role in IoT by improving data management and transforming the data processes. The RPA bots can analyse the data and reveal the time needed to process the data. In the end, it will show the number of automation actions left over. These features will support to uncover many business insights, hidden facts and figures, and trends that can emphasise the difficulties in business processes.

RPA Integration with Other Tools
The action of merging RPA with different technologies in the digital spacewill lead to an effective RPA avatar. The resulting advantage of the RPA will surpass its typical offering and delivers process outcomes quicker. RPA software will be integrated with distinct automation software. Undoubtedly, it will result in growth to the new digital workforce that will capture every potential benefit from the current automation technology.

The Latest Technology Trends in 2020


In the modern era, technology is evolving at a rapid pace that yearly forecasts of trends can appear out-of-date prior to become live. As technology continuously evolves, it allows even quicker change and advancement, creating an expedition of the rate of change till gradually it becomes exponential.

Artificial Intelligence (AI)
Artificial Intelligence (AI) has recently got a lot of buzzes, and it proceeds to be a trend to follow because it is impacting how we live and work in the early stages itself. Also, other wings of AI have emerged, including Machine Learning. AI means computer systems built to imitate human intelligence and execute tasks like recognition of speech, images, and decision making. AI can perform all these tasks quicker with more accuracy than humans.

Speech recognition attempts were taking place since the 1950s but did not reach allowing natural speech till the late 1990s. Machine learning (ML) has delivered the majority of speech recognition inventions in this century. Nowadays, 4 out of 10 use AI services in one form or another that includes streaming services, navigation apps, ride-sharing apps, personal home assistants, smartphone personal assistants, and smart home devices. In addition to customer use, AI is utilized to predict maintenance, schedule trains, assess business risk, and enhance the energy efficiency, among several other money-saving activities.

Today, the technology of speech recognition is everywhere. Users and technologists alike understand the advantages with voice command, like helping people with learning disabilities, along with lowering paperwork, also saving time and money which are correlated with the business operations. Artificial intelligence has already started to facilitate the abilities of voice command.

Machine Learning (ML)
Machine Learning is a part of AI. By using Machine Learning computers are programmed to learn and to perform something that they are actually not programmed to perform. They understand it via discovering insights and patterns from data. In common, there are two types of learning one is supervised, and the other one is unsupervised.

Now Machine Learning is deploying very quickly in all types of industries. Applications of Machine Learning is utilized for data mining, data analytics, and pattern recognition. On the user end, Machine Learning powers real-time ads, web search results, and detection of network intrusion were few among the various tasks that Machine Learning can perform.

Robotic Process Automation (RPA)
Similar to AI and Machine Learning, the Robotic Process Automation (RPA) is another technology which is used to automate jobs. Robotic Process Automation (RPA) is the practice of software to automate the processes of businesses like processing transactions, interpreting applications, handling data, and even responding to emails. RPA majorly automates the repetitive tasks, and the people used to perform.

Robotic Process Automation is an application of technology, supervised by business logic and programmed inputs, intended at automating processes of a business. Using RPA tools, an organization can build software, or a “robot,” to capture and evaluate applications for transaction processing, triggering responses, data manipulating, and interacting with other digital systems. RPA scenarios vary from something like as simple as building an automatic response to an email to deploying plenty of bots, every bot is programmed to automate tasks in an ERP system.

Significance of Artificial Intelligence is Tremendously Increasing in Recruiting Process


Significance of Artificial Intelligence is Tremendously Increasing in Recruiting Process
Artificial Intelligence (AI) and Machine Learning (MI) have become trending in recent discussions with business leaders about HR and recruiting associated technology plans for the coming year. It is obvious to say that the expectations of AI are increasing day by day. It is also apparent that while many are excited to AI due to the trendiness or coolness factor, a growing number of business leaders are now excited in how AI-powered capabilities can enhance the effectiveness and outcomes of their hiring attempts.

In this blog, we are highlighting some of the effective areas where applying AI is creating an impact and supporting to solve actual difficulties in talent acquisition. Most talent acquisition leaders are working in a recruitment environment that is more chaotic. While plenty of hiring data drifting around in enterprise HR systems, it is a big challenge for businesses to obtain valuable information from this data to support in recruiting decision-making and eventually better hiring.

AI Role in Talent Acquisition
Artificial intelligence making constant inroads into talent acquisition, it is now feasible to access this data. Most exercises in this area normally start with developments in regular and repetitive recruiting tasks like screening and scheduling automation and then advancing into more intelligence-based tasks like applicant engagement as well as forecasts to support with recruiting decision-making.

Below are the recruiting tasks that are generally automated using AI and machine learning to execute regular functions or augment human-centric skills.

Applicant sourcing:
surfacing eligible applicants from internal & external talent pools for the present vacancies.

Applicant screening:
evaluating applicant profiles and deciding their fit for a job opening.

Profile improvement:
automatically sourcing further information on a candidate from publicly accessible data over the web.

Personalised evaluations:
tailored solutions that adjust to each applicants’ abilities and skills.

Applicant matching:
recognising and assessing the most effective active or passive applicants for an open position based on their relevant experience, skills, or other specified criteria.

Programmatic job advertising:
automated distribution of job and budget optimisation that depends on past data and performance in the real-time campaign.

Chatbots:
conversational UI for applicants or prospects for Q&A, pre-screening, scheduling, and more.

Interview self-scheduling:
scheduling logistics automation, enhance hiring velocity with instant, real-time updates & confirmations, and enhance applicant experience by giving scheduling flexibility.

Here are a few areas in the recruiting process where AI and machine learning are creating an impact.

Applicant Engagement
AI-powered chatbots can support to create a compelling applicant experience by improving engagement and providing notifications to keep applicants updated on their status of the application.

Lessening bias with AI Recruiting
Insensible bias is possibly one of the most basic andhard-to-overcome obstacles of quality recruiting. With decision-making inspired by machine learning insights and algorithms, AI recruiting can assist in eliminating such biases, producing a more sensible and fair hiring process.

Predictive Models
Data-driven insights which are powered by AI-based recruiting technology– during various stages of the hiring process can empower stakeholders to make hiring decisions that are fair and maximise the possibility of success for the applicant as well as the company.

Fewer Errors with AI Recruiting
The functions that are automated with AI and machine learning are also less likely for human error and hence more chance for enhancing the overall improvement of the hiring process. Over time, with AI recruiting, organisations and recruiters can spend more time with applicants and less time doing repetitious tasks, eventually leading to greater productivity and lesser cost per hire.

Everything you Need to Know About Performance Testing and its Challenges


Software testing plays a significant role along with software development in the SDLC (software development lifecycle). This process of testing involves the examination of the software developed to make sure that it is as per the needs defined and error-free for end users. Software testing broadly categorized into two significant types those are
• Functional testing
• Non-functional testing

Some of the popular functional testing types are Acceptance testing, Sanity, Integration, Unit, System, Interface, Regression, etc. Some of the most popular Non-functional testing types are Endurance, Localization, Recovery, Reliability, and Performance testing, etc.

In these testing types, Performance testing is one of the primary testing processes that play a crucial role by assuring the software performs with stability and seamless even beneath various load conditions.

Performance Testing
Performance testing is a significant non-functional testing type and includes the process by which an application or software is examined to know its present system performance.

This sort of testing examines how your present system performs in terms of stability and responsiveness when examined below different workload conditions. Performance testing also assures that the application works as anticipated irrespective of the bandwidth availability and network fluctuations. Primarily, this process of testing identifies the speed with which the system works.

There are different types of performance testing that are usually adopted which comprise Load testing, Volume testing, Stress testing, Soak testing, Spike testing, Scalability testing, etc. and these testing processes determine the speed, and responsiveness of the app, the website, or the network when examined below the various workloads.

Importance of Performance Testing in Business Websites and Mobile Apps
Performance testing measures the scalability, speed, stability, and reliability of the software beneath varying loads thus assuring their stable performance. Every business application must be reliable and deliver steady results, irrespective of the number of users who are accessing it. Particularly, with respect to eCommerce apps, banking apps, etc. these apps must perform seamlessly even with multiple users, else it negatively affects the reputation of the brand.

Apparently, today it is necessary for businesses to assure the performance of websites and business apps are seamless in order to deliver exceptional customer experience

Performance tests like load and stress tests recognize the application behavior and help to verify whether the server is responding to the user with inquired data within the specified time.Hence performance testing is vital for mobile apps and business websites to work efficiently even under heavy load, as they need to ensure business continuity. So, Performance testing is crucial for the success of the business and needs to be leveraged through enterprises.

Performance Testing Challenges
• Similar to testing web and mobile applications, testers must consider factors like packet loss, latency, load, network bandwidth, etc. The effect of these factors can be far more severe.

• The most significant challenge that testers are compelled to face is of higher complexity. All the new devices linked in the network must be accounted for. A performance testing may be common with recording traffic from mobile devices, web browsers, etc., but testing the latest objects that do not permit a change of settings might be inconvenient.

• The diverse practice of conditions becomes another barrier altogether. While evaluating the performance of an app, the end user’s internet connection stability plays a vital role in discovering test results. Therefore, it is important to assure that data is identified and accurately stored during a disturbance in service.

A well testing strategy is essential to account for the various difficulties faced.

Top Trends in Reimagining IT Services in 2021

Artificial Intelligence Systems is Everything
The new challenges and constraints in the year 2021 can be managed through AI systems these systems can support to overcome all the obstacles. AI can support people to dream up innovative solutions and ideas to establish a more flexible organisation.Short-term use cases are apparent and workforces seriously need development.

A 2019 global study on AI discovered that one of the top roadblocks to scaling the technology is the shortage of employee adoption. If firms are able to invest in explainable AI and different tools that promote and facilitate real human-AI association, then people will experience the technology at its best. Winning today could open new opportunities for enterprises to reimagine their organisation and workforce in the future.

As per the latest report, Artificial Intelligence (AI) is inescapable by 2025, a minimum of 90% of new business apps will include AI. By the year 2024, more than 50% of user interface communications will utilise AI-enabled computer vision, natural language processing (NLP), and speech.This report also says AI and machine learning, IoT, analytics, and other data-driven technologies will drive to technology-empowered change.

Robotic Process Automation (RPA) will Get Mainstreamed
RPAis mainstreamed already for performing repetitive tasks in the business sector. While RPA is recognised as the most fundamental form of Artificial Intelligence, it will proceed to grow because RPA can revolutionise businesses irrespective of their business model and size. We will observe that attended RPA will drive the way, but when coming to the unattended RPA it will also begin growing up in the year 2021. RPA supports to enhance the skills of its current workforce.

Significance of Digital Identity will Increase
Digital identity could considerably support in automating transactions and activities, and to avoid cheating, both in the private sector and public sector. Digital identity can be arrived at through preparing traditional schemes digital or through fully digital means. Blockchain can be a vital technology in promoting digital identity in decentralized and truly trustless environments. With the support from the digital identity, you could quickly check that the individual coming to your residence to check the water boiler is actually the individual sent by the energy or appliance company; governments could properly trace who demands support and whether they should receive it; citizens could gain access to all public transport in a specific region without carrying many cards or tokens– one per transport business or consortium, etc.

Technology Transformation can be Accelerated by Optimizing and Improving existing IT
Majority of mission-critical workloads have not yet shifted to the cloud, and 94% of companies manage several clouds. It isthe right time to begin our tech transformation.Technology transformation over hybrid multi-cloud environments can be complicated and risky. It often includes processes and solutions that are separated, with disparate interfaces and separated management processes. This is the reason why only 20% of workloads have shifted to the cloud. At Adaps Btranse, we understand how to navigate these difficulties and remove the barriers to success. We can support you to optimize and revive technologies with established processes that improve portability and decrease risk.

XaaS will Receive a Great Momentum
XaaS or Everything as a Service is the future’s technology. It will absolutely obtain more momentum in the year 2021 with connecting other futuristic technologies like Big Data, analytics, AI, blockchain, and many more. Also, the multi-cloud theory will gain popularity in the digital transformation services as firms will face onsite, off-side, hybrid, and other demands for collecting and accessing the corporate data during a period. XaaS will reach its ever-changing requirements by delivering robust and customised solutions.

DevOps Plays a Significant Role in Digital Transformation

DevOps plays a vital role in digital transformation that is from recognizing patterns to uncovering the latest revenue streams. Experts say that it is difficult to have one without other.

The Growing Significance of DevOps in Digital Transformation
The COVID-19 crisis has hit the initiatives of digital transformation. With the expedited pace of digital transformation and selection of digital practices, DevOps is also moving from ‘nice-to-have’ to ‘must-to-have’ element in the approach of digital transformation. While offering suggestions to firms that trying to cover this change coming at them so swiftly.

When you think regarding the DevOps implementation in the digital age, it is a cross-functional team that contains not only developers and IT operations, but also the quality experts so that the quality engineers, the quality leaders, and the quality analysts in order to make perfect kind of working model. Also, you must prepare your team that owns the quality as a principal pillar to deliver software.

We have witnessed some teams not own quality. Quality is remarkably important and to assure that you are going to deliver value quickly and usually to the business, you must own the quality. The last thing we can say on this is that you also require to prepare the business to encompass getting value to the delivery of software early and often. So, you require to prepare your business to obtain this value on a regular basis as well.

DevOps Supports Firms to Uncover Patterns
DevOps role in digital transformation is to support firms to understand the specific models and practices that are possible to enhance their performance in the aspect of digital interruption, thus increasing their competing posture. Transforming from a conventional hierarchical, control enterprise to a digital set firm, where authorisation is distributed, autonomy and association are stable, and all are empowered to provide for this you need some serious behavioural reform.

The DevOps strategy helps us to recognize why optimizing the flow from idea to value recognition is not simply about designing a pipeline, and this significantly gives us the frameworks and models to work from a cultural aspect, too.

DevOps Allows Constant Reliable Change
As we observe at largest digital transformations, they are encouraged by several things such as the passion to empower the business to learn, emphasize and move faster. They look to welcome the cloud and to improve their architectures with strategies such as microservices. They seem to reach wider user bases and to attain a more comprehensive scale.

If you do not have culture, process, and discipline that enables you to begin continuously and reliably change, which is what DevOps can support to enable. There is a lot of difficulties that comesimultaneously with cloud and running microservices. If you do not have strong alignment over development and operations, your possibilities of success are restricted. DevOps culture and principles are the fuel for facilitating these various transformation types for most firms.

DevOps Influence on Digital Transformation
DevOps has a notable impact on accelerating customer value by digital transformation. For building a structured model and methodology for producing software with high quality by automation, it is critical to recognize automation holistically– automation of deployments, automation of builds, and automation of monitoring.So in the DevOps world concerning digital transformation accelerating customer value, you should get to have a system that monitors and balances that enable you to get constant feedback.
In the modern digital world, reactiveness and speed are more prominent than control. DevOps is able to create capabilities from a tech perspective and also from an organizational perspective to handle the growing demands in regards to complexity and speed.

Artificial Intelligence and its Impact on IT Industry

Artificial Intelligence (AI)
Artificial Intelligence (AI) has recently got a lot of buzzes and it proceeds to be a trend to follow because it is impacting how we live and work in the early stages itself. Also, other wings of AI have emerged, including Machine
Learning. AI means computer systems built to imitate human intelligence and execute tasks like recognition of speech, images, and decision making. AI can perform all these tasks quicker with more accuracy than humans.

Speech recognition attempts were taking place since the 1950s but did not reach allowing natural speech till the late 1990s. Machine learning (ML) has delivered the majority of speech recognition inventions in this century.
Nowadays, 4 out of 10 use AI services in one form or another that includes streaming services, navigation apps, ride-sharing apps, personal home assistants, smartphone personal assistants, and smart home devices. In
addition to customer use, AI is utilised to predict maintenance, schedule trains, assess business risk, and enhance the energy efficiency, among several other money-saving activities.

Today, the technology of speech recognition is everywhere. Users and technologists alike understand the advantages with voice command, like helping people with learning disabilities, along with lowering paperwork, also
saving time and money which are correlated with the business operations. Artificial intelligence has already started to facilitate the abilities of voice command.

Impact of AI on the IT Industry

High-Level Cyber Security with AI
In spite of the efforts, there are always bugs that try to escape from the testing iterations. Using AI can we examine the software systems and resolve the loopholes and restricting unauthorised access from users.
The AI can also map the association among the IPs, threats, and malicious files to screen them from reaching into the software system. Cognitive AI development can alert the authorities when any violations occur in the real-time. It can strengthen authorities through improving their cyber wing and by decreasing crime.

Enhanced Productivity with AI
Artificial Intelligence utilises a series of algorithms, which can be implemented directly to support programmers when it comes to writing better code and reducing software bugs. AI has been developed to deliver recommendations for coding purposes that improve efficiency, improve productivity, and deliver clear, bug-free code for developers. Through judging the code structure, AI can provide valuable recommendations, which can enhance productivity and support to cut downtime throughout the production stage.

Automating Processes with AI
The advantage of automation is that nearly every piece of work can be performed without human involvement. Through the practice of deep learning applications, companies can go a long way in automating the processes involved in the backend, which is cost-effective and lessen human intervention. AI-enabled systems progressed over time as the algorithms set to improve productivity and realise from mistakes.

IT industry is the Biggest AI Beneficiary
Organisations in the IT industry are the biggest beneficiaries of AI’s capabilities. A recent study reports that approximately 34 to 44% of global firms are using AI to resolve employee technical support problems, automate internal system improvements, and assure that employees only use technology from authorised vendors.

Agile Testing, Myths & Truth

Drill down to Agile testing

‘We are into Agile already’ – This is a natural business statement used by most of the testing organizations nowadays who claim to deliver faster and quicker by inculcating agile methodologies.

Just by Delivering faster does not mean that the business is into Agile process. Business needs to understand that Agile not only means delivering quicker and faster, but it also defines the way of testing during Software development life cycle which helps in improving the overall software product life cycle. Testing plays a very vital role in SDLC. Traditional testing methodologies take a step by step process and progress with the stages of the development cycle in a waterfall model. A happy business case could support waterfall model efficiently but when the business demand keeps changing in an iterative mode, it gives a light to a testing approach called as Agile testing. Let us take a drill down to Agile and its way of Testing.

What is Agile?

Agile is a round robin software testing approach followed during software development cycle in an iterative mode. As a part of Agile methodology, teams are engaged to work in parallel to capture software bugs in an early stage and also to reduce the testing time-lines by delivering faster and in a shorter span of time thus benefiting the business.

While there are many benefits of implementing Agile within an organization, there are also many myths associated with transforming the project to Agile. Let’s have a reality check to some of the myths on Agile methodologies.

Top 5 Myths on Agile and it’s Reality check –

  • Myth #1 – Agile and Scrum are the same

Reality- When an Agile consultant is asked about Agile, Scrum is the first word which is used to pitch Agile methodologies. But the reality is that Scrum is one of the ways to approach Agile. Scrum is a framework to manage project whereas Agile is a principle which unites all the processes and strategies together to fasten delivery.

They say Agile is scrum. But that’s not right, Agile can never be scrum but yes Scrum can be a part of Agile.

  • Myth #2- Agile means no documentation at all

Reality– Agile definitely involves documentation which might not be lengthy in pages, but it definitely needs short user stories and acceptance criteria while designing the business cases. The documentation is Agile is followed and tracked right from open state to the closure of the project. Its short user stories help in collaborating more effectively with the people associated with the Project. So, no documentation in Agile stands as just a myth.

  • Myth #3- No Project planning required in Agile

Reality- Any Project without Planning turns out to be the failure of all times. Planning is everything while driving a Project towards delivery. In waterfall model, planning is done only once a year which is followed throughout till that project is driven to closure, whereas in Agile the Planning is open for refinement at every stage of the testing life cycle in order to incorporate amendments and keep the plan more flexible. This helps in meeting the customer demands and expectations in an iterative and incremental mode.

  • Myth #4- Agile is only used for Software development

Reality- Agile is not a restricted principle that it can be only use in software development companies. Agile aims in transforming every business into a well-developed strategic company by incorporating all its strategies and processes into bits and pieces at every mode of a product life cycle. Agile has nothing to do with software development, although software consultants were the first to use this principle therefore the myth is followed. Agile methodologies are built only to deliver specific results which can be used in any kind of businesses across the globe.

  • Myth #5- Agile gives immediate benefits to the business

Reality- Agile works in an incremental form. Your business may seem to have a fall down at the initial stage as you will be breaking some of the old processes and traditional way of working. But Agile will assure to give you sure shot results in a longer period. It will ensure that your business needs are met timely and it will help you in raising your business to altogether the next level.

There are quite some myths about Agile which takes it to the level of Chaos, but above mentioned were the top 5 myths which every traditional business tends to believe. Reality check to these myths was a must.

The truth about Agile is that well executed Agile projects brings a lot of profit to the business and aims in delivery quality output and deliverables. Agile is much more to actually what we think it is.

Our support to get you into Agile

Be Agile and Go agile is the mantra Adapsbtranse recommends to every Business.

Adapsbtranse is leading organisation who has the best of testing team expertise that can help your business adopt Agile testing using some of the best continuous test automation frameworks and integration tools.

We have scaled Agile with best of our technologies stack like HP UFT, JIRA, SOAP UI, Zephier, TFS and many more. These technologies have proven to be the best leading tools to fasten delivery and reduce business cost of the customer. Our Agile testing automaton frameworks have a leverage to support global delivery model to speed up the development and execution process.

If you want to get your business into Agile, reach out to us for more information on Agile and its way of testing.

How Continuous Automation help to Deliver Business Value?

DevOps is neither a tool/technology nor a framework. It is a software development strategy which bridges the gap between development and Operations team of the company. There are lots of conflicts between Development and operations team for instance the software works in Developers system but don’t work well in production environment. Similarly Developer wants Agility but operations team wants stability. There are many such conflicts which give rise to a concept called as DevOps which helps in resolving these problems.

Continuous Automation and DevOps

DevOps can be implemented and comprehended only with the help of Continuous Automation. Continuous Automation plays an important role in implementing DevOps at various stages of application life cycle. Continuous Automation is a practice to automate an application  at every stage of software development and testing life cycle. It helps in building, integrating , deploying software changes at a faster pace maintaining the consistency and security of the application. It integrates automation of infrastructure and applications, and helps in managing the version control of the software product. It allows  to test a particular application under multiple test environments and conditions thereby helping to manage the software product efficiently. With the traditional testing approaches , it becomes difficult to drive the business in continuous delivery mode. Automation at every and early stages of testing life cycle ensures validations of whether software meets business demands and expectations and clears every quality gate in the delivery pipelines. There are lots of benefits delivered through continuous automation in terms of speed, efficiency and business risk to the customer.

Lets have a closer look on how incorporating Continuous Automation helps in adding value to DevOps at every stage in application management life cycle

  • Continuous Development

Software Project Planning plays a very important role in DevOps methodology. Project Planning is done on the basis of software requirements and its business needs. Once the project planning is completed, development and implementation of the code is then kicked off. Developers develop the code on the existing code and keep amending the code based on the continuous feedback and various operational methods using various automations tools and technologies as per the application needs and demands.

  • Continuous Integration

The continuous integration is a process where the developed code is merged into a single central repository in a continuous format. This helps in maintaining a single version of the copy across development and operations team. Developer merges the code with help of continuous integration tools like Jenkins, Maven, Git/gerrit. Once the code is merged in the repository it triggers an automatic compilation, builds and executes the code. This helps the developer in detecting the broken code at the early stage.

  • Continuous Testing

Continuous testing means undisrupted testing during integration phase. Once the build is deployed on the server, regression testing is conducted with the help of automated tools like selenium, UFT  and other automation tools to check the impact of the code. Automation batches are kicked off automatically through the CI/CD tools and the summary results are then generated in the report logs. Continuous testing helps in achieving shorter time to market.

  • Continuous Monitoring

This is an operational phase of DevOps, where the user actions of the customers are recorded and trend analysis is carried out to improve the efficiency and capabilities of the software application.

Various monitoring methods are performed under this stage like shift left testing, web services testing, early defect detection, micro services testing and many others through automation to eliminate errors at an early stage.

  • Continuous Feedback

Continuous feedback of the application is provided to the developer with the help of customer’s surveys, feedbacks and other ways through which application can be improvised. These feedbacks aim in delivering the best of product to the customer. Feedbacks are in an iterative mode so that continuous development on the flaws of the application is worked upon by the developers and tested by the testers.

Conclusion:

User needs are changing rapidly , and meeting the business demands seems more and more tougher everyday . The best way to achieve this is to drive the assets directly from the initial phase itself. This is only possible with the help of continuous automation in DevOps.

DevOps is a best way for software development. It definitely eradicates the gap between development and operation teams and engages more iterative way of testing. DevOps will capture the market in the growing time and will evolve as the best practice to develop dynamic applications and overcome all challenges.

DevOps offerings in Adapsbtranse

As the scope of development of the applications keeps increasing, the need for DevOps to reduce time to market will keep increasing as well. Adapsbtranse focuses and helps in delivering a quality product to the customer by using high end technologies which helps in collaborating effectively with developers and Operations team. We have wide range of frameworks, tools and technologies like-

-Cucumber framework, Apache, Maven, Jenkins, SOAP UI, ALM and others which will help in transforming your business to DevOps.

We value and understand the need to move faster and Go Digital. We will help you in accelerating your business and increase your ROI.

If DevOps is your need then hold on to this page and collaborate with us for end to end implementation of DevOps.