How Can Analytic Innovations Be Delivered with Existing IT Standards?

| April 7, 2017

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Hitachi Vantara

Hitachi Vantara, a wholly owned subsidiary of Hitachi, Ltd., helps data-driven leaders find and use the value in their data to innovate intelligently and reach outcomes that matter for business and society. We combine technology, intellectual property and industry knowledge to deliver data-managing solutions that help enterprises improve their customers’ experiences, develop new revenue streams, and lower the costs of business. Only Hitachi Vantara elevates your innovation advantage by combining IT, operational technology (OT) and domain expertise. We work with organizations everywhere to drive data to meaningful outcomes.

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AI Adoption: an advanced digital transformation process

Article | May 17, 2021

Common view is that AI software adoption is 'on its way' and it will soon replace many jobs (example self-driving cars with drivers etc.) and the majority of companies are starting to embrace the efficiencies that AI brings now. Being a practitioner of AI software development and being involved in many projects in my company AI Technologies, I always found my direct experience in the field in contrast with what the media generally portraits about AI adoption. In this article I want to give my view on how AI projects affect the work dynamics into clients work processes and compare that with the studies available on the impact of AI and new technologies on work. This should help the reader, especially if he is an executive, to set the right expectations and mentality when he is assessing the potential investment into a new AI project and if his company is ready for it. To start with, any software development project, including AI, can be summarized into 3 stages: proof of concept (POC) when the prototype has been built, product development when the software is actually engineered at scale, live support/continuous improvements. It occurs often that projects in AI will not go pass the POC stage and this is often due to 1) not right IT/data infrastructure in place 2) not specialist people have been hired to handle the new software or digital transformation process has not been planned yet. Regarding point 2, the most difficult issue is around hiring data scientists or data/machine learning engineers because many companies struggle with that. In fact, in a March 2021 O’Reilly survey of enterprise AI adoption, it has been found that “the most significant barrier to AI adoption is the lack of skilled people and the difficulty of hiring.” And in 2019 software it has been estimated that there were around 144,000 AI- related job openings, but only around 26,000 developers and specialists seeking work. Of course hiring an internal data scientist, it is not the only problem in restructuring the workforce. Often a corporation has to be able to re-train entire teams to be able to fully benefit from a new AI software. I can give an example. As many readers know a sales process involves 3 stages: lead generation, q&a call/mails with potential clients and deal closing. Now, a couple of years ago AI Technologies had been engaged to automatize the q&a call stage and we build a ai bot to manage the 'standard questions' a potential client may ask (without getting into the details, using AI and technically word3vec encoding, it is very possible to automate mails/chatbot for 'standardized questions' like 'how much it cost?' 'how long is the warranty for' etc.). Using this new internal solution, it meant the team responsible for the q&a would have been retrained either to increase the number of leads or the number of closing. The company simply decided to not embark into the transformation process required to benefit the new AI adoption. This example, in various forms, it is actually quite common: companies unless they are really innovative prefer to continue with their corroborated internal procedures unless some competitors threat their profitability. This bring to the fact that actually AI is not an out of the shelves solution which can be plugged in with no effort. As the moment a POC is under development it should be a good norm to plan a digital transformation process within the company. Also it is worth mentioning that, it is unlikely that the workforce has to be dismissed or made redundant as many expected following AI adoption. Just following the example above, what the AI bot does actually is to get over the repetitive tasks (q&a) so people can do more creative work engaging more clients (lead generation) or convincing to buy ( deal closing). Of course, it means that some people have to be retrained but also means that with the same people, you can close/generate more sales. It is a misconception to think that AI solutions will make human work redundant , we just need to adapt to new jobs. My example resembles a classical example on adoption of ATMs. When ATMs were introduced in 1969, conventional wisdom expected the number of banking locations to shrink, but instead, it actually made it possible to set up many more of them, it became cost-effective. There were under 200,000 bank tellers in 1970, but over 400,000 a decade later. The other common problem to face when companies want to embrace AI adoption (point 1), it is their current infrastructure: databases, servers, and crm systems have to be already in place. To put it simply, any AI system requires data to work with so it naturally sits on top of data infrastructure in day to day business operations. In the last two years AI Technologies has been engaged to work with a large public organization (70,000 employees) to build a solution to automatically detect malicious behavior of its employees manipulating their data. To build the AI software we had also designed a system to stream data from each employee terminal into a central database for processing. This infrastructure was not present at the beginning of the project since before the need for malicious detection was arised, the organization never really realized the necessity to gather certain data: a simple login and logout time was all the needed to monitor the activity of their employees (which company folder/file they accessed etc. was not important). This is a common situation and most of the companies' infrastructure are usually not ready to be used directly with AI solutions: their current infrastructure was simply designed with other objectives in mind. For sake of completeness, most companies decide to invest their internal resources in other areas of the business rather than crm or expensive data structures. There is no blame on this choice, at the end any business has to be profitable and investing in infrastructure is not always easy to quantify the return of investment. If anything, this article should have given an idea of the major pitfalls approaching AI projects which can be summarized as follows: • AI solutions are not out of the shelves , ready made software that can be immediately put in use: they often require new skilled hires within the client organization and potentially a plan how to re-utilized part of the workforce. • It is often a myth that AI solutions will necessarily replace the employees although it is possible that they have to be retrained. • Any AI project works on data and infrastructure which are necessary to benefit the new solutions. Before embarking on AI projects an organization has to either budget in a new infrastructure or at the very least an upgrade of the one in use. In essence, due to the implication on both employees and infrastructure, AI adoption should be considered as a digital transformation process more than a software development project. After the overwhelming hype of attention of the recent years, I would expect that in the next 2-3 years more companies will start to realize what AI projects really are and how to best use them.

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Top 5 Event Technology Trends to Watch in 2021

Article | July 8, 2021

A successful event pays for all the hard work done by the company and the event management team. But along with excellent attendance, more things cater to the success of the event. The audience needs to have a memorable experience and zero hassles throughout the event. The technology used in the event enhances its experience. Therefore, technology trends in event management play a vital role in the success of any event, plus it also makes the process of event organization relatively smooth and orderly. Events are no longer just a gathering of people, presentations, speeches, or visuals of entertainment. Instead, there are more of an intriguing and personal experience. Event technology trends have changed the face of events for the audience as well as the organizers. For example, bar codes have replaced paper tickets to mark entry at events. This is a petite example of the use of technology. AI, RFID, automation, gamification, wearables, project mapping, etc., are some of the event technology trends that have amplified the present event experiences. Let us look at the five major event technology trends in 2021. Event Technology Trends Facial Recognition Facial recognition is a prominent security feature that Apple has used. It is a success in identifying the phone owner by intimately studying the iris and facial features. This technology trend is widely used in events and is quite a breakthrough. A scanner is placed at the event gate, wherein the faces are identified for entry access. This experience can further be personalized by generating voice notes with the person’s name. The bottleneck of crowding at the entry is avoided with the use of this trend. There are endless possibilities that this AI feature can offer. In the upcoming world, it is necessary to adapt to contactless techniques. Hence, facial recognition is undoubtedly going to gain momentum as a smooth and faster check-in method. AR and VR Artificial Reality (AR) and VR (Virtual Reality) have become prominent in marketing ideas. As a result, these event technology trends will play a prominent role in enhancing an event experience. An AR and VR can provide the attendees with a plethora of experiences. Despite being confined to their homes, the audience can virtually visit the event area and have a 360-degree exposure. With the application of augmented reality technology for an event, you can wow your audiences by crafting stories in an entertaining way. This way of storytelling will make sure that your audience listens and experiences the account. E3 held its conference by totally adopting AR and VR technology. This conference was a hit as it provided the attendees with a real-time view of the virtual reality world that E3 was promoting. Event Automation Event technology trends are evolving by leaps and bounds. Event automation is making it possible to plan an event and execute it with minimum manpower-handling and resources. This enhances the event experience and guarantees minimal errors. From designing the venue in 3D to contactless entries, from personalized experience to tracking behavioral patterns, everything is made possible through this event planning technology. With the emerge of 5G, event experiences will be mesmerizing and involving. AR, VR, live streaming, chatbots will be seamlessly integrated and automated with the event's theme. Skipping the manual labor and shifting to automation provide incredible ROI and attendee experience. In addition, implementing 5G will assure that there are no event technology issues from planning to execution of the event. Live Streaming Apple, Google, and Facebook have already proved the success of live streaming events. As a result, live streaming an event has become a necessity in the Covid-19 world. This technology has various benefits. With the implementation of live streaming, a person can attend the event despite different geographical locations (which helps in attaining a global footprint). In addition, online streaming is more engaging and increases the chances of the person attending your events physically. Live streaming should be available on physical venues. If the event is spread out in a larger place, the audience can attend their favorite event by live streaming. The audience will not miss the session even if they are far from that particular area. This makes the event a grand success. Live streaming technology in the hybrid event creates a scenario that enables all the interested people to come together and enjoy the event. Although, hybrid events are not a trend, they are the future! Also, live streaming is the ideal solution for events with a tighter budget. Gamification Gamified events see a 44% increase in audience engagement. Gamification is the best way to make the event interactive for the attendees. You can gain a lot of information when the attendees make their choices in the interactive games. This data-gathering process will help you in making your events more personalized for the future. Rewards, coupons, and free food can be used as motivators for the attendees. Make your event unimaginably successful by organizing quizzes, treasure hunts, and some games relating to your brand. All you have to do is set up a gamification corner or ask to download the app for a pleasing experience. The Advantages of Incorporating Event Technology Trends ● It’s safe. You have access to every place and person who is a part of your event. So, you can keep a lookout for any odd behaviors happening at the event. ● Enhanced guest experience Your guests will have a magnificent experience as there are easy check-ins, attendance from anywhere, interactive games, personalization, and much more. ● Future-ready If you embrace the events technology trends today, you will be way ahead of the curve. Your audience will be awaiting your events online and offline. Embracing technology trends promises the best outputs and gains for the organizer and the attendees. Wrapping Up Adapting the latest event technology trends is sure to keep your audiences hooked to your brand. Project management tools, AI, and chatbots are meant for personalization of the events and make the task of event organizing simple. Check out all the various event technology, digital tools, and software available for event organization and keep yourself ahead of the race. Educate yourself about which event technology ideas are the best for your conference, meeting, or event and implement them accordingly. Apart from giving your audience an event to remember, you will find yourself saving a lot of time that goes into event planning. The pandemic has proved very challenging for the event industry. Thus, the above five event technology trends can be used to streamline the event planning processes. After all, increasing the attendance, providing a pleasing experience, and building brand awareness are all that is needed for the success of an event! Frequently Asked Questions How is the technology used during an event? Event organizers use technology to study the behavior of the attendees, collect data based on their actions, and then provide them with the best user experience. AI, chatbots, live streaming, and gamification are examples of technologies used during an event. How is technology changing the events industry? The use of technology in event planning has led to more personalization. The real-time data used to enhance the audience experience is a commendable use of technology. Technology has led to an increase in audience attendance and a remarkable decrease in the costs of organizing an event. What are Event technology tools? AR, VR, AI, Chatbots, Event Automation, Event Mobile Apps, and all the technology used in an event are event technology tools. In addition, there are tools available to manage an event right from planning, execution to asking for feedback. { "@context": "https://schema.org", "@type": "FAQPage", "mainEntity": [{ "@type": "Question", "name": "How is the technology used during an event?", "acceptedAnswer": { "@type": "Answer", "text": "Event organizers use technology to study the behavior of the attendees, collect data based on their actions, and then provide them with the best user experience. AI, chatbots, live streaming, and gamification are examples of technologies used during an event." } },{ "@type": "Question", "name": "How is technology changing the events industry?", "acceptedAnswer": { "@type": "Answer", "text": "The use of technology in event planning has led to more personalization. The real-time data used to enhance the audience experience is a commendable use of technology. Technology has led to an increase in audience attendance and a remarkable decrease in the costs of organizing an event." } },{ "@type": "Question", "name": "What are Event technology tools?", "acceptedAnswer": { "@type": "Answer", "text": "AR, VR, AI, Chatbots, Event Automation, Event Mobile Apps, and all the technology used in an event are event technology tools. In addition, there are tools available to manage an event right from planning, execution to asking for feedback." } }] }

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The 6 Biggest Challenges to AI Marketing Success

Article | July 8, 2021

More and more businesses are utilizing modern-day opportunities that Artificial Intelligence (AI) brings to the digital world. Perhaps, it is the most necessary step for the companies to stay competitive in 2021 and beyond. With the rise of technology, AI-powered marketing platforms are becoming more common and simpler to use. However, this does not mean that they do not have any challenges. A survey conducted by Teradata, a data analytics firm, reports that around 80% of enterprise-level organizations have already embraced some form of AI. Out of them, approximately 32% of businesses use AI algorithms for marketing purposes. However, more than 90% of these companies have already anticipated significant barriers to adopt and integrate AI. In this article, we shed light on the six biggest challenges in AI marketing. It will help you act and avoid common problems if you encounter such roadblocks when integrating AI into your marketing strategy. Here are some highlights of this article: ● Many popular media sources have created hype around AI. Therefore, people, in general, don’t trust it. ● There isn’t enough skilled workforce to fill AI-related positions in organizations. ● AI software needs high-quality data. Unfortunately, maintaining such data quality is not that easy. ● AI software needs significant investment. ● Many small businesses lack IT infrastructure resources. Cloud services help them overcome this problem. As you can now understand, most challenges in AI marketing revolve around business alignment, data, or people. While every organization varies and will face the AI adoption process differently, there are a few common challenges in AI marketing you should be aware of. So, without further ado, let’s take a look at the most common AI challenges that digital marketers face. Lack of Knowledge of AI Systems When it's about total AI implementation, your company’s management must have a deeper understanding of the role of AI in Digital Marketing, the latest AI trends, data challenges, and all other essential aspects. However, many marketers lack a proper understanding of the use of AI technologies in marketing. On top of this, unfortunately, AI comes with a variety of fears and myths. While some people think they need an in-house data science team for complete AI adoption, others believe in those sci-fi fantasies showing how smart robots can end humanity. Insufficient knowledge of AI is one of the biggest challenges in AI marketing. It hinders the AI implementation in several ways and ultimately delays the success. How to get rid of this? First things first — start by acquiring knowledge. It might sound a bit demotivating, but we do not mean you have to be a data scientist for this. You can look at other giants in the industry, carefully analyze how they are deploying AI into their business, and act accordingly. Next, know more about the current AI technologies for marketing — you can either DIY or get help from an expert. Once you have adequate knowledge about it, you know what to expect from AI and what not. Challenges in Integration Deployment and integration of new technology requires skills. Integrating Artificial Intelligence into your business is not an easy task. It is a complicated job and requires proper knowledge. You first have to set up interfaces and other elements to address all your business needs. Such steps may require complex coding. Developers must consider feeding the data into the system, labeling, data storage, data infrastructure needs, and much more while setting up the elements. Then comes the model training and testing part. It is necessary for the following reasons: ● To check the effectiveness of your AI ● Develop a feedback loop for constant improvement ● Data sampling for reducing the stored data and run models even faster The biggest challenge here is — how to confirm if it's working correctly? And, is it worth the money you are investing? Arguably, the only and the most effective way to overcome this hurdle is to work closely with your vendor to ensure that everyone is well aware of the process. Plus, there should not be any limitations in the vendor’s expertise. They should be capable of guiding you beyond building the AI models. When you implement Artificial Intelligence with the right strategy, you indirectly reduce the risk of failure. And, once you successfully implement AI into your system, you will still have to educate your marketers to use it efficiently. In this way, your people can understand how to interpret the results they receive by proper implementation and effective use of the AI model. Poor Data Quality or Lack of Data High-quality data is essential for Artificial Intelligence. Any AI system will come up with poor results if you provide it with insufficient or poor-quality data. As the Big Data world is evolving every day, businesses are gathering vast amounts of data. However, this data is not always up to the mark. It's either insufficient or not good enough to drive a profitable AI marketing strategy. Such data-related challenges in AI marketing prevent companies from capitalizing on Big Data. For this reason, as a business, you should always make sure the data you get is clean and rich in quality. Otherwise, you will experience unsatisfactory results from the AI, and it will negatively influence the overall success of your AI-powered marketing campaigns. Budget Constraints for AI Implementation Many companies lack the necessary budget for implementing AI into the system. Even though AI has the power to provide impressive Returns of Investment (ROI), hefty investments are still one of the biggest challenges in AI marketing, especially for smaller and mid-size companies where the budgets are already stretched. AI-powered platforms come with high-performance hardware and complex software. And, the deployment and maintenance of such components are costly. Such budgeting challenges in AI marketing can limit the opportunities for businesses to utilize AI technology to the fullest. Thankfully, this is now becoming a thing of the past as many affordable AI vendors are coming ahead for the rescue. With them, you do not have to invest in developing in-house solutions. Moreover, they allow you to implement AI tech in a relatively cheaper and faster way. Privacy and Regulations Artificial intelligence is still new to this world, and it's growing at an incredible pace. Chances are that the rules and regulations surrounding AI will change and tighten up over the coming days. The data collection and use of data policies already impact businesses that collect and use data from the customers based in the European Union and drive their Artificial Intelligence systems. The EU implemented GDPR in 2018, and it has made the data collection, and data usage rules even stricter for companies. Ultimately, companies now have to be extra careful while collecting and using customer data. Furthermore, several businesses are restricted from storing the data offsite for regulatory purposes. This means that they can no longer utilize cloud-based AI marketing services. Constantly Changing Marketing Landscape AI is a new marketing tool and can bring disruption to traditional marketing operations. For this reason, marketers evaluate how AI can create new jobs and, at the same time, replace older jobs. One survey suggests that AI marketing tools are more likely to replace the jobs of around 6 out of 10 marketing analysts and marketing specialists over the coming years. Overcoming The Challenges in AI Marketing Yes, such challenges in AI marketing can sometimes slow down your campaigns and affect the outcomes of your AI-driven software. But fortunately, there are a variety of alternative solutions. You need to consider the following steps to rule out the common challenges in AI marketing we discussed earlier. ● Develop a target oriented marketing strategy ● Get the money before you roll out AI in marketing ● Train your marketers ● Recruit the right talent Developing business cases, recruiting talented marketers, measuring the ROI, and getting the required investment — probably, none of these steps sound interesting. But, when it is about the reality check of your AI marketing strategies, they are absolute methods that can open the door to actual Artificial Intelligence payoffs. In the end, every company's responsibility is to make sure that they are using the AI system responsibly so that they can benefit their customers in the best way possible. Frequently Asked Questions How does AI affect marketing? AI helps marketers to spot the latest internet trends and predict them for the future. Such trends are necessary to learn the current marketing facts and eventually help with significant tasks such as budget allocation and setting up the target audience. Plus, AI effectively reduces the money and time usually spent by companies on digital advertising. Simultaneously, it leads businesses towards smarter and more targeted advertising campaigns. As a result, many companies have implemented AI into their digital marketing strategies as it can increase sales and save money at the same time. On a bigger scale, AI has an impact on global trends, sustainability, and scalability. Even government issues, major public concerns, and major cities around the globe have seen positive effects of AI. AI can make the world a better place if used in the right way! How is AI used in digital marketing? Companies are utilizing some stand-out developments for improving the customer experience with the proper use of AI. For example: ● Image recognition technology ● Predictive and targeted content ● Content creation ● Chatbots With these, AI enhances customer support, and provides more relevant and targeted content to the customers. Why is artificial intelligence critical in marketing? With the correct use of Artificial intelligence, businesses can collect, analyze and store a large amount of data. As a result, AI is the best way to learn the latest marketing trends and incorporate them into your marketing strategy. In general, Artificial Intelligence has the power to help your company reach potential customers and provide them with easy access to make purchases. { "@context": "https://schema.org", "@type": "FAQPage", "mainEntity": [{ "@type": "Question", "name": "How does AI affect marketing?", "acceptedAnswer": { "@type": "Answer", "text": "AI helps marketers to spot the latest internet trends and predict them for the future. Such trends are necessary to learn the current marketing facts and eventually help with significant tasks such as budget allocation and setting up the target audience. Plus, AI effectively reduces the money and time usually spent by companies on digital advertising. Simultaneously, it leads businesses towards smarter and more targeted advertising campaigns. As a result, many companies have implemented AI into their digital marketing strategies as it can increase sales and save money at the same time. On a bigger scale, AI has an impact on global trends, sustainability, and scalability. Even government issues, major public concerns, and major cities around the globe have seen positive effects of AI. AI can make the world a better place if used in the right way!" } },{ "@type": "Question", "name": "How is AI used in digital marketing?", "acceptedAnswer": { "@type": "Answer", "text": "Companies are utilizing some stand-out developments for improving the customer experience with the proper use of AI. For example: ● Image recognition technology ● Predictive and targeted content ● Content creation ● Chatbots With these, AI enhances customer support and provides more relevant and targeted content to the customers." } },{ "@type": "Question", "name": "Why is artificial intelligence critical in marketing?", "acceptedAnswer": { "@type": "Answer", "text": "With the correct use of Artificial intelligence, businesses can collect, analyze and store a large amount of data. As a result, AI is the best way to learn the latest marketing trends and incorporate them into your marketing strategy. In general, Artificial Intelligence has the power to help your company reach potential customers and provide them with easy access to make purchases." } }] }

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MAKING ARTIFICIAL INTELLIGENCE SMARTER LIKE HUMAN BRAIN

Article | March 11, 2020

The latest advancements in Artificial Intelligence have been much tremendous and inspiring. It has become a part of everyday life for almost all consumers. In a large range of domains, the technology has transformed the way humans work and live. From smart home devices like Alexa, Siri, among others to large scale data security and fraud detection, all are inspired by and relied on AI. Despite this, there is still a large gap between current AI systems and human-like intelligence. Over time, the human brain has developed and advanced in order to respond to survival instincts, harness intellectual curiosity, and achieve demands of nature. While the human brain finds innovative ways to exceed its physical capabilities, human scientific pursuit amplified by the amalgamation of mathematics, algorithms, computational methods, and statistical models.

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Spotlight

Hitachi Vantara

Hitachi Vantara, a wholly owned subsidiary of Hitachi, Ltd., helps data-driven leaders find and use the value in their data to innovate intelligently and reach outcomes that matter for business and society. We combine technology, intellectual property and industry knowledge to deliver data-managing solutions that help enterprises improve their customers’ experiences, develop new revenue streams, and lower the costs of business. Only Hitachi Vantara elevates your innovation advantage by combining IT, operational technology (OT) and domain expertise. We work with organizations everywhere to drive data to meaningful outcomes.

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