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Leverage the product analytics tool from Mixpanel to have digital experience in 2023Product analytics tool is flourishing in the global tech market for their effective user interaction in software applications. Applications are for smart devices such as web and mobile devices to offer meaningful insights into onboarding, retention, and many more. It helps to automatically capture all kinds of interactions without any event setup. The global product analytics tool market size is expected to hit US$25.3 billion in 2026 with a CAGR of 21.3%. Here is an exclusive interview with Scott Pugh, Regional VP and General Manager APAC of
Kindly brief us about the company, its specialisation and the services that your company offers.Mixpanel is a product analytics company to help companies understand how their users engage with their digital products (i.e. websites and apps). Given the rapid rate of digitization, especially in the last two years, product analytics is becoming mission-critical for companies to manage and grow their digital properties. Companies really need to measure and understand key metrics like conversion, user engagement, and user retention. This is only possible if they understand how users are actually interacting with their digital products and that’s where a product analytics tool like Mixpanel comes in. The company also understands that the digital world is fast-paced, and time to insight is critical. Users can get the incredible depth of analysis in a self-serve fashion with a lightning-fast UI built on a proprietary database with products. The team wants to help customers get important insights to their teams quickly so they can take action on the insights.
With what mission and objectives, was the company set up? Kindly mention some of the major challenges the company has faced till now.The mission is to help the world learn from its data. When the company was first formed in 2009, the world was only starting to go digital and Mixpanel’s pioneering event-based tracking solution gave budding digital products the ability to understand user behaviour within their products. Fast forward to today, it is now in an environment where digital products are no longer just nice to have— they’re essential for any company that seeks to stay relevant and connected to their customers. This development has really supported Mixpanel’s growth as a business as more and more organisations start to recognize that product analytics is essential to building better digital experiences. There was a time when the team had also built new products to address adjacent market needs. But over time, it realized that this was taking away focus from the core product and features that were most meaningful to customers. The decision was to refocus on core analytics capabilities. The team was committed to pushing product analytics to new heights and now has over 6,000 paying customers. The team has also used Mixpanel for themselves to help understand users better. For example, it looked into the data to determine the user path or funnel that helps to maximise the rate of new user activation within products and growing to love it. This helped to optimize the path for new user activation and make informed decisions and led to a host of UX improvements. The NPS scores triple as a result of this strategy.
What is your biggest USP that differentiates the company from competitors?When it comes to understanding user behaviour and driving product innovation and better digital experiences, companies need to answer questions like:
Who are my power users? Do they behave differently from other users?
What makes some users convert and not others?
Do different groups of users retain differently? Do users who use a specific product feature retain more than those who don’t?
Did the new product feature cause the desired change in user behaviour and lead to the business outcomes that we wanted?
These questions are really hard to answer without a tool like Mixpanel, that’s made for analysing user behaviour. It has seen many people trying to do this with alternatives like marketing analytics tools and it doesn’t work well because those tools were made for answering other types of questions like where users are coming from and bounce rates, etc. If one looks at the movement to democratize data and companies wanting to put insights in the hands of more if not all of their employees, one will then appreciate just how important good UI and UX would be. If users don’t want to use the tool and hate using it, then data democratisation cannot take off. Customers regularly share on social media about how they love UI and I hear the same feedback in my conversations with them. Combined with the ease of use the team provides, I think the team is perfect for helping companies get user behaviour insights to every team so they can make better decisions.
Please brief us about the products/services/solutions you provide to your customers and how do they get value out of itCustomers use Mixpanel to understand how their users are engaging with their digital products. This helps them to make the right decisions from product pricing, promotions, onboarding flows, product feature development, marketing budget investment, and more. Another great way to use product analytics is to help determine product-market fit. Passion Factory, creators of a popular South Korean health and wellness app, use Mixpanel to track the conversion rates of different chatbot dialogue options in their app. The chatbot is an integral part of how they drive user engagement. By identifying the best performing dialogues and keeping them, then replacing poor performing options with new ones, they were able to optimise the user experience to drive more engagement. The chatbot optimization and other data-driven product decisions helped them to drive a more than 250% increase in their four-week user retention rate within a year, validating product-market-fit.
How do you see the company and the industry in the future ahead?The big investment for companies from a data perspective is moving to a first-party data strategy and having a central source of truth to manage that data. Companies are moving to a modern data stack strategy where they will invest in a data lake and/or data warehouse as a central source of truth and a tool like DBT to transform, test and document their data. From there they can send their data to Mixpanel for analysis using ingestion APIs or Reverse
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Exclusive Interview With A Dev Team Member
First of all congrats for the job you did so far, but I think you already know that half of the world is supporting you!
Thanks! Me and my wife read your blog, and after you wrote about the Dev Team, we thought it would be a good idea to find you. Your blog is the first hungarian language blog or newsportal we communicate to directly.
Special thanks for that. Let’s start with who the members of the Dev Team (no names of course) are, and how you organize your work since you are living in different countries, continents.
Members of the Dev Team are software, electronics and cryptographics professionals from all over the world. The members of the team – or much more, the core – are from Hungary, France, Belgium, England, Russia, Israel, Ukraine and the USA. We work in a way, that we distribute our work files among us, and with team work, we put the ideas together. The average age is about 30 years old. Most of us don’t know each others name and never met each other.
How many are you?
Everyone has a full time job – and of course this has influence on the Dev Team’s work, but usually there are 15 active members working on the job at the same time.
How do you organize, where does the idea come from to hack the iPhone, and why did you set it up?
We are high tech enthusiasts and hackers… hackers in a good way. We like to crack things and see how they work. Most of us have worked with UNIX and OS X for a long time. Few of us knew the others from there, and other professionals have joined later, those whose work we appreciate a lot.
Do you get any threats or “feedback” from Apple? Did you have any contact with the company?
Apple never made contact with us. We make sure we never break the law when we release a new software. PwnageTool and QuickPwn are very complicated, because these softwares remove the necessary parts from Apple’s firmware. We NEVER release pirated softwares.
How much time do you spend on the crack, and other iPhone-related works?
We are working on it 24 hours a day. While one of us are working on it, others are sleeping, and we continually switch. IRC is running in the background all the time, even when we are working onour private jobs, so we have worked on the iPhone thousands of hours. I have to mention, that we spend a lot of money on special hardware and reverse engineering softwares, also from our own money.
Do you get any donation, do you make any profit out of the huge work you made anyway?
We finance everything with our own money. Most of the team has a good job that pays good money in the IT field. The Dev Team is our hobby and although it is very time consuming, yet it still is a hobby. We didn’t take money from anyone!
How many people cracked their iPhones with your program? Do you have any idea how much iPhone users freed their phones?
We have more than hundred thousand recurrent PwnageTool and QuickPwn users. It is hard to estimate how many exactly, but a lot.
Why it is so hard to unlock the iPhone 3G? What is the main difference between 2G and 3G that has prevented the unlock so far?
Apple and Infineon made a very serious work and made almost impossible to unlock the iPhone 3G. They learned from what we did with 2G and made the 3G much more safer.
How far are you from suceeding with the unlock?
This is secret of course.
How deep was the 2.2 baseband update? If you want to make a sim-unlock on this as well, do you have to start the job from scratch? So, if someone accidently updated the baseband, does he have to give up, or does he still have a chance to unlock his phone?
At the moment the exploits we used to run our codes on 2.1 and older basebands has been removed from 2.2. 2.2 closed the security breach we used to control the baseband as we wanted and at the moment 2.2 baseband is bad.
What do you mean “bad”?
In 2.2 baseband there is no such an exploit we can use, so it is bad :-).
What do you think about the sofware and hardware of the iPhone 3G compared to other smartphones?
The iPhone OS is based on UNIX/Mach operating system, and both UNIX and Mach is a result of many years of developement. G1 is using Linux, which has a similar story. Fortunately nowadays mobile processors are powerful enough to use UNIX.
What kind of deficiency does the iPhone OS have, and in which direction would you develop it, if it depended on you?
It would need to be more open.
Why and for who do you do your work?
First of all for myself, for us, and for the people who prefer an unlocked phone. We bought a flat in Budapest with my wife, and the agent does not come to our home every week to check if we had painted the walls red, does he? The situation is similar with the IPhone and other devices we buy as well.
What do you do on week days?
We work and play. We have a very special Hungarian Vizsla (deerhound), he keeps us busy all the time.
Why did you choose a pineapple as your logo?
Apple/Pinapple, Pwn/Own, PwnApple (Pwning Apple)
Exclusive Interview With Brett Hurt, Ceo, And Co
Building data assets to derive actionable insights has become an essential part of business planning. Having a huge amount of data oftentimes turns it into a liability for there is ample chance for data scientists to lose sight of a critical insight when the big data is organized haphazardly. On the other hand, a data catalog can help businesses discover data assets that were lying dormant. Data.world is a cloud-native enterprise data catalog company known for the best data practices in the industry, delivering result-centric insights. Analytics Insight has engaged in an exclusive interview with Brett Hurt, CEO, and Co-Founder at data.world.
1. Kindly brief us about the company, its specialization, and the services that your company offers.Enterprises are facing a trillion-dollar data problem. A recent study from NewVantage Partners found that 99% of Fortune 1000 companies planned to invest in big data and AI initiatives last year, but only 24% of respondents believe their companies are actually data-driven. My co-founders and I saw this first-hand in the market as well when we founded data.world in 2023 – for all the talk about data being critical for businesses, the most important data and analyses were typically buried in silos.
At data.world, we believe that business leaders need to view their data supply chain like their actual supply chain – incredibly valuable and essential to the operation of their business. Implementing this mindset across a business requires the right technologies. We offer a data catalog for the modern data stack, enabling both data producers and consumers to easily structure, govern, and analyze the data that powers their business. We’re also unique in the space because we have been a Certified B Corporation ever since our launch and are committed to building the most meaningful, collaborative, and abundant data resource in the world to help maximize data’s societal problem-solving utility.
2. Tell us how your company is contributing to the IoT/AI/Big Data Analytics/Cloud Computing industry of the nation and how the company is benefiting clients.More traditional data catalogs allow enterprises to centralize all their data into one place, creating a single point of reference for those using it. But for today’s modern data stack – and the pace of innovation surrounding it – the traditional model doesn’t go far enough. Many enterprises are wasting money on their data initiatives because they use outdated ways of thinking about data. Companies that utilize artificial intelligence and big data analytics – from those in the Fortune 500 to startups – require agile data governance, where data is easily accessible, understandable, and usable for everyone within a company. Our company data.world gives enterprises this edge. By providing fast data access, a clear context for the data, and a single platform to enhance data analysis, our customers can multiply the value of their data and use it to drive their products.
3. Kindly share your point of view on the current scenario of Big Data Analytics and its future.Recessions, while painful for businesses and the society at large, can be powerful engines for creating more efficient businesses. I have written recently about my belief that big data analytics will play a major part in that trend as we see increasing inflation and recession indicators.
4. How can C-suite executives leverage data to deliver business value to their organizations?When thinking about the realities of leveraging data to deliver real value for your enterprise, looking to who I call the “knowledge superheroes” can help. Take, for example, Airbnb’s founder and CEO Brian Chesky, who turned his company’s pandemic challenges into a better business model, driven by data. He turned a company with revenues falling 80 percent overnight into one of 2023’s biggest IPOs months later.
Data catalogs and knowledge graphs can create the same type of transformative change for all companies, and every executive needs to start by getting their data house in order and equipping themselves with the right tools for their modern data stack to get that done. Doing so is critical for building a successful business model today both because of how fast technology is evolving and renewed economic uncertainty. In my recently published book, The Entrepreneur’s Essentials, I outline the five critical ingredients for building startups into big companies, and their business model is #1. In today’s market, that means investing in the modern data stack that helps your data producers and consumers in the short- and long-term.
5. The industry is seeing the rising importance of Big Data Analytics and AI. How do you see these emerging technologies impact the business sector?Companies are rightly looking to big data analytics to drive a new wave of business efficiency and resilience by empowering teams to find, understand, trust, and use data needed to address critical business questions. This information can be used to answer questions like, “Where in my organization can I make cuts or reallocate?” and “What projects can I postpone for six months?”
For example, over the next few months, you might need to put a critical program on hold or unfortunately let go of a percentage of your workforce. If you are leveraging a knowledge graph-powered data catalog, all information associated with the project, including team members, their skill sets, and their relationship to the project and respective data, can be cataloged and understood. Institutional knowledge is retained and connected to the business, so that it can be easily accessed when it’s time to rehire, retrain, retrench, or shift back into growth mode. We saw this happen with one of our earliest customers a few years ago when many people turned over. They were easily able to keep their data and analysis work going due to how well it had already been centralized and documented.
6. Where are we going from here?We’re sitting in a much different economic environment than we were even a month or two ago, and businesses across industries need to be preparing proactively for the inflationary and recessionary pressures that are here now and lie ahead. Having led two prior businesses through the dot-com bubble and the Great Recession, I’m optimistic that this time will be different for two reasons: data literacy and agile governance. Since the last recession, the ability to confidently use data to inform problem-solving has improved dramatically. Now, when enterprises have the right tools and processes in place, they can have a much higher level of trust and confidence in the outcome of data-backed decision-making.
My main recommendation to enterprises is to think about data as simply the facts of your business – your customers, your partners, your staff, and your supply chain. Mastery of those facts and the analysis we can pull from them has the potential to shield companies from the worst of the bumpy economic landscape that may lie just around the corner. This time around, tech and business leaders alike have the opportunity to optimize our businesses in a way that was not even possible during the last recession.
Exclusive Interview With Julius Černiauskas, Ceo Of Oxylabs
Businesses use automation software to visit various pages online and download the publicly available data in them. It is then processed to create various business intelligence insights. Oxylabs is a premium proxy and public web data acquisition solution provider, enabling companies of all sizes to utilize the power of big data. Analytics Insight has engaged in an exclusive interview with Julius Černiauskas, CEO of
Kindly brief us about the company, its specialization, and the services that your company offers.Oxylabs is a premium proxy and public web data acquisition solution provider, enabling companies of all sizes to utilize the power of big data. In simple terms, we provide all the necessary tools and solutions for businesses looking to extract publicly available data on a large scale. A significant part of our daily processes is to support web scraping. Businesses use automation software to visit various pages online and download the publicly available data in them. It is then processed to create various business intelligence insights. Our product portfolio includes both complete out-of-the-box solutions such as the Scraper APIs and supporting infrastructure such as proxies. With the former, our clients only have to send requests to our endpoints, and they get the data sent back to them. With proxies, they have to develop automation software themselves as we only provide the know-how and the supporting blocks.
Kindly mention some of the major challenges the company has faced till now.Providing web scraping solutions is always fraught with challenges. One part of the equation is that the industry is relatively new. Being a pioneer is an amazing feeling, but it makes challenges so much more difficult as no one can help you out. You have to figure out how to solve issues all on your own. Being a front-runner means creating the pace and practices. It means a lot of other companies are looking up to us and following the models we create. Another part is the technical complexity of the process. We pride ourselves on helping clients achieve an uninterrupted flow of data. Maintaining infrastructure, creating scraping code, and everything else is extremely resource-intensive. With the added novelty of the industry, we are always facing avant-garde challenges. Finally, web scraping hasn’t established itself in the public consciousness yet. There’s scarcely any legislation across the world and the overall perception can be seen as somewhat negative. While our legal team has been doing tremendous work keeping us on the right side of the law, they can’t change global perception. Yet, at the same time, web scraping is becoming an essential part of digital businesses.
How do you see the company and the industry in the future ahead?Another aspect of not being established in the public consciousness is that there’s little awareness of the possibilities. As we are the leader of ethical solutions and tools in the industry, we are working towards bringing ethical web scraping out of the darkness and turning it into something that is used for the common good. We have developed partnerships with universities, NGOs, and other organizations by giving them access to our solutions or
How is your company helping customers deliver relevant business outcomes through the adoption of the company’s technology innovations?Innovation is an essential part of Oxylabs. We invest heavily in R&D, primarily in the field of artificial intelligence and machine learning, which sets us apart from our competitors. As I’ve mentioned before, web scraping is a technically complicated process, involving many different parts that can be optimized almost to no end. A part of such optimizations is parsing. Generally, when you retrieve data from the web, it’s messy and unreadable. Parsers, and other automated software, make the same documents easier to understand and process. Unfortunately, writing them is extremely costly and time-consuming. We have invested a lot of time in innovating our field through machine learning and now we have an industry-leading Adaptive Parser. It removes the requirement of writing parsers for eCommerce product pages, allowing us to significantly cut costs and provide higher quality data to our clients.
AI is projected to be the next market. How is AI contributing to the making of your products and services?AI is at the forefront of our innovation push. We have established an AI/ML Advisory Board with 5 leading business (e.g., from Stripe) and academia (e.g. from MIT, NASA) experts with whom we maintain constant collaboration. They help us in driving the progress of AI in web scraping further than we could do ourselves. We believe AI will play a significant role in the coming years by making parts of web scraping more accessible than ever before. Web scraping can be split into two large chunks: the discovery phase and the collection phase. The discovery phase is accepting a task from an interested party. A business may be interested in the prices of specific countries within a set region. I see AI aiding significantly in the discovery phase by either allowing vague queries to be easily acted upon or by enabling better finding processes. Secondly, the collection phase is, as we already see, greatly enhanced by the development of machine learning models. We can take out the most costly processes and completely automate them through the use of artificial intelligence. While there may be doubts about AI helping the discovery phase, I have a resolute belief that it will tremendously change the face of data collection.
How can businesses efficiently extract the value from data, without increasing cost and complexity?A large part of optimizing data practices is narrowing down collection practices. There’s enough data to fulfill any goal and to support any hypothesis, and it’s surprisingly easy to over-collect information. Most of the software we use in daily operations such as tracking tools, CRMs, etc., provide some sort of data collection feature. As a result, there’s plenty of data to go around at all times. What businesses should do is create clear goals for the data they already hold. I prefer to think of data as something that should have intention. Asking oneself “why are we collecting that data” is a surefire way to get down to all the necessary details. If you have to find a complicated or long-winded explanation on why it is necessary, maybe it isn’t all that after all.
What are some of the challenges faced by the industry today?Web scraping remains a process employed by a select few while it can be of tremendous benefit to all. At Oxylabs, we’re pushing for ethical web scraping to be recognized as a common good and aim to make it accessible to non-developers.
Businesses use automation software to visit various pages online and download the publicly available data in them. It is then processed to create various business intelligence insights. Oxylabs is a premium proxy and public web data acquisition solution provider, enabling companies of all sizes to utilize the power of big data. Analytics Insight has engaged in an exclusive interview with Julius Černiauskas, CEO of Oxylabs Oxylabs is a premium proxy and public web data acquisition solution provider, enabling companies of all sizes to utilize the power of big data. In simple terms, we provide all the necessary tools and solutions for businesses looking to extract publicly available data on a large scale. A significant part of our daily processes is to support web scraping. Businesses use automation software to visit various pages online and download the publicly available data in them. It is then processed to create various business intelligence insights. Our product portfolio includes both complete out-of-the-box solutions such as the Scraper APIs and supporting infrastructure such as proxies. With the former, our clients only have to send requests to our endpoints, and they get the data sent back to them. With proxies, they have to develop automation software themselves as we only provide the know-how and the supporting blocks.Providing web scraping solutions is always fraught with challenges. One part of the equation is that the industry is relatively new. Being a pioneer is an amazing feeling, but it makes challenges so much more difficult as no one can help you out. You have to figure out how to solve issues all on your own. Being a front-runner means creating the pace and practices. It means a lot of other companies are looking up to us and following the models we create. Another part is the technical complexity of the process. We pride ourselves on helping clients achieve an uninterrupted flow of data. Maintaining infrastructure, creating scraping code, and everything else is extremely resource-intensive. With the added novelty of the industry, we are always facing avant-garde challenges. Finally, web scraping hasn’t established itself in the public consciousness yet. There’s scarcely any legislation across the world and the overall perception can be seen as somewhat negative. While our legal team has been doing tremendous work keeping us on the right side of the law, they can’t change global perception. Yet, at the same time, web scraping is becoming an essential part of digital businesses.Another aspect of not being established in the public consciousness is that there’s little awareness of the possibilities. As we are the leader of ethical solutions and tools in the industry, we are working towards bringing ethical web scraping out of the darkness and turning it into something that is used for the common good. We have developed partnerships with universities, NGOs, and other organizations by giving them access to our solutions or otherwise supporting their goals . We help them by providing tools, sharing technical expertise, creating tools to tackle specific problems, and much more regularly. One of our most successful projects has been developing an AI-driven scraper that identifies harmful and illegal content on the internet, aiding the Lithuanian government institutions in their work. We see web scraping becoming something not only businesses use to further profit incentives, but something that works for the common good of all. We’ve been working on other initiatives that would push web scraping further into the public consciousness. Oxylabs hosts an annual conference, OxyCon, and we do a lot to share our knowledge on the legal and technical side of things with the outside world.Innovation is an essential part of Oxylabs. We invest heavily in R&D, primarily in the field of artificial intelligence and machine learning, which sets us apart from our competitors. As I’ve mentioned before, web scraping is a technically complicated process, involving many different parts that can be optimized almost to no end. A part of such optimizations is parsing. Generally, when you retrieve data from the web, it’s messy and unreadable. Parsers, and other automated software, make the same documents easier to understand and process. Unfortunately, writing them is extremely costly and time-consuming. We have invested a lot of time in innovating our field through machine learning and now we have an industry-leading Adaptive Parser. It removes the requirement of writing parsers for eCommerce product pages, allowing us to significantly cut costs and provide higher quality data to our chúng tôi is at the forefront of our innovation push. We have established an AI/ML Advisory Board with 5 leading business (e.g., from Stripe) and academia (e.g. from MIT, NASA) experts with whom we maintain constant collaboration. They help us in driving the progress of AI in web scraping further than we could do ourselves. We believe AI will play a significant role in the coming years by making parts of web scraping more accessible than ever before. Web scraping can be split into two large chunks: the discovery phase and the collection phase. The discovery phase is accepting a task from an interested party. A business may be interested in the prices of specific countries within a set region. I see AI aiding significantly in the discovery phase by either allowing vague queries to be easily acted upon or by enabling better finding processes. Secondly, the collection phase is, as we already see, greatly enhanced by the development of machine learning models. We can take out the most costly processes and completely automate them through the use of artificial intelligence. While there may be doubts about AI helping the discovery phase, I have a resolute belief that it will tremendously change the face of data collection.A large part of optimizing data practices is narrowing down collection practices. There’s enough data to fulfill any goal and to support any hypothesis, and it’s surprisingly easy to over-collect information. Most of the software we use in daily operations such as tracking tools, CRMs, etc., provide some sort of data collection feature. As a result, there’s plenty of data to go around at all times. What businesses should do is create clear goals for the data they already hold. I prefer to think of data as something that should have intention. Asking oneself “why are we collecting that data” is a surefire way to get down to all the necessary details. If you have to find a complicated or long-winded explanation on why it is necessary, maybe it isn’t all that after chúng tôi scraping remains a process employed by a select few while it can be of tremendous benefit to all. At Oxylabs, we’re pushing for ethical web scraping to be recognized as a common good and aim to make it accessible to non-developers. As such, the two challenges I see most pressing is public legitimacy and accessibility. Legitimacy has been fully achieved in the business world, but it has to spread further as web scraping can do much greater things. I believe complete public legitimacy will be achieved over time through developing partnerships with government institutions and academia. Accessibility is on us – we strive to innovate in making web scraping easier to use and more intuitive.
Exclusive Interview With Arvinder Pal Singh, Ceo And Co
Digital transformation has been changing the landscape of many companies across the globe with the help of disruptive technologies. These technologies are enabling companies to obtain a significant foothold in the existing industries which is essential for generating new business models and services. Here is an exclusive interview with Arvinder Pal Singh, who is the CEO and Co-Founder of Enquero, which is one of the Genpact Companies to elaborate more on this front.
What are the key trends driving the growth in data analytics?As we are seeing massive jumps these days with regard to customer expectations, tech innovations, and the way business models are evolving, we can only expect to keep up with these changes provided we are able to focus on building connectivity of relevant data. Exploring avenues of connecting KPIs from various departments, such as marketing, sales, supply chain, and finance will help in addressing customer needs better. Sharing and interlinking of insights across departments within an organization can help transform lagging indicators into leading ones. This upcoming trend of connected data to connected analytics for generating connected insights will set the tone for identifying and evaluating the success parameters of our businesses in the days to come.
How does your company’s strategy facilitate the transformation of an enterprise? The industry is seeing the rising importance of big data analytics and AI. How do you see these emerging technologies impacting the business sector?Basically, I feel that both big data analytics and AI can together present opportunities for business innovation and growth. And the benefits of it include a better understanding of market dynamics, identification of new revenue channels, customer-tailored products, and enhancing operational efficiencies. With deeper insights and accurate predictions from AI-driven systems, businesses would be ready to manage and respond to upcoming challenges.
How are disruptive technologies like the cloud impacting today’s innovation?With rapid cloud adoption, businesses are experiencing improvement in time-to-market, and process efficiencies, while the reduction in operational costs, IT spending, and maintenance costs. Cloud enables anywhere, anytime app deployment with standardized functionalities and easy options for scaling, quality control, and improved security.
How do C-suite executives leverage data to deliver business value to their organizations?I believe data is that one common language that brings everybody in an organization to a common point of agreement and makes consensus building much more objective-driven rather than being forced upon. Leaders of today must evaluate what problems to address with the power of data for structuring a sustainable future. Data will help business strategists decide how to measure success and respond to unprecedented situations. Connected data-driven insights will help management identify gap drivers, link strategy-process-system intelligently, and deliver well-rounded decisions to enable corporate direction within and outside a business ecosystem.
What is your biggest USP that differentiates the company from competitors? What are some of the challenges faced by the industry today?I think the biggest challenge the industry is facing today is the lack of the right talent. The rate at which technology is evolving is immense. Adapting to this change is nearly impossible if today’s talent models continue to focus on just training and not working towards enabling self-learning and development techniques. The entire academia-employee-employer value chain needs reimagining to shape the workforce of tomorrow.
Where are we going from here into the future with these digital technologies?Exclusive Interview With Nidhi Jain, Founder & Ceo, Karexpert
The recent disruptive technologies such as artificial intelligence, big data as well as computer vision are revolutionizing the healthcare system across the world. It involves digital care programs to enhance the efficiency of healthcare delivery with personalized care. The combination of AI and big data is creating an intersection between technology and healthcare for the utmost caring of different types of patients in all kinds of hospitals or clinics. It has created a huge scope for telemedicine and telehealth as well, especially in the COVID-19 pandemic. Here is an exclusive interview with Nidhi Jain, Founder, and CEO of KareXpert where she explains how India’s first-ever SaaS-based integrated digital healthcare platform is focused on digitally connecting multiple kinds of hospitals to make healthcare accessible and affordable to the Indian society.
– A brief about KareXpert – Please highlight the funding you received from Reliance JioKareXpert received funding from Reliance Jio in 2023, for the development of the core technologies and healthcare stack. KareXpert developed the entire stack with No-coding architecture for microservices, databases, and the front end. The system of interaction, the system of intelligence, and the system of records are its prime building blocks. The healthcare stack is ready with commercial offerings in the market now.
– What type of services KareXpert provides? – How KareXpert is different from the other players/competitors in the industry?Competition has taken the product or point solution approach that is largely siloed, while KareXpert has taken a platform-based approach connecting the hospital and all departments with golden workflows where patient engagement is taken care of at every step. KareXpert also connects hospitals to the healthcare ecosystem such as third-party software systems, medical equipment, and patient aggregators platforms bringing a complete B2B2C offering to the hospitals as a one-stop solution.
– How is COVID inclined towards your business and market?COVID-19 has created a great need for hospitals to think about their IT at a holistic level rather than a point solution, move to floud, enable mobile health, and have 24×7 support available remotely. KareXpert’s transformative platform-based approach coupled with cloud-native, mobile-first, AI-ready approach was envisioned many years back. The pandemic has helped us by making our sales process easy as customers themselves are looking for platform-based solutions with cloud-based solutions. We have many marquee customers with whom we have already implemented and are soon to go live.
– What kind of hospitals are you planning to cater to?For us, hospital size doesn’t matter, as we are on an elastic cloud with a SaaS-based commercial model. We have segmented the entire Indian hospital market into six segments (corporate, large, medium, small, nursing home, and eye hospitals) with different silver, gold, platinum, and titanium packages serving all kinds of hospitals from 1500 beds to 10 beds. KareXpert’s No-Coding Platform approach coupled with DevOps/CICD agile software development brings Change Request (CR) at the speed of business requirements.
– Highlight the challenges you face when you reach out to a hospitalSometimes, understanding the right decision-maker is challenging in the hospital and some of the stakeholders are not available online so directly connecting them is an issue, and some are afraid of migrations as it’s a mammoth project wherein projects have been developed and integrated over the years with no documentation. To mitigate these risks, KareXpert has designed and developed a pending patent ZTP (Zero Touch Provisioning) approach where an entire hospital of any size can be created in less than 30min. This used to take three months.
– Current Industry ScenarioIndian Healthcare IT is in its infancy stage with mostly operating as a manual process with lots of inefficiencies. According to analysts, the Indian healthcare IT market will be touching 5% of $200Bn USD i.e., ~$10Bn USD with 30%+ CAGR in three year-time. This exponential growth is due to the low digitization of the Indian healthcare market. 95% of Indian hospitals don’t use EMR/EHR with Excel being used for their day-to-day work rather than any health technology platform. 90% of medical equipment is not connected to any system that has continuous data loss as there is no data lake conceptualization for AI-readiness.
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