It’s that time of year
again. With 2020 (finally, mercifully!) drawing to its close, we’ve tapped our team of Teradata experts to chime in on their technology and business predictions for 2021 – with a special focus on how COVID-19 will impact business’ digital transformation in the year(s) to come.
Take a look at their predictions and let us know if you think we’re close to the mark. You can also share your own with us on our social channels
@Teradata.
COVID-19 and its Impact on Business
"As companies look to eventually return in some form to the office, we'll see investments in AI rise across the board as companies look to AI to boost safety and compliance measures. AI-driven algorithms can scour meeting invites, email traffic, business travel and GPS data from employer-issued computers and cell phones to give businesses advance warnings of certain danger zones or to quickly halt a potential outbreak at a location. These technology-supported measures ensure that once employees return to the office, they are working in the safest possible environment." –
Hillary Ashton, Chief Product Officer
"Given the massive social and economic disruption wrought by COVID-19, the biggest challenge for businesses in 2021 is managing the continuing uncertainty around the economic impact of a sustained COVID-19 presence. No doubt there is a vaccine on hand but there are a lot of questions yet unresolved about the vaccine’s efficacy among medium-sized to large populations and the delivery of vaccines in short order through a highly scaled distribution network. With this level of uncertainty, business revenues and customer engagement are likely impacted, and the latter can have the effect of causing long term damage. So, the challenge for businesses is simply how to navigate the rough H1 of 2021 and come out on the other side with a viable business model that can sustain the 2020-2021 losses." –
Sri Raghavan, Director of Data Science and Advanced Analytics
Data Analytics in Business
"2020 was brutal for some firms, rewarding for others, and challenging for all. As we enter 2021, laggards have an existential imperative to reinvent themselves digitally, leading firms struggle to keep pace with demands. All of these enterprises need to capitalize on 100% data integration with predictable costs, reliable performance and real-time visibility." –
Bonnie Holub, Managing Partner, Practice Lead, Data Science, Americas
"[The biggest change to the data analytics industry in 2021 will be] a new focus on scenario analysis and simulation technologies, as a way to think through business redesigns. Additionally, more solution builders will emerge as core AI stacks, like Nvidias and Intel’s AI stack, are utilized on top of public cloud providers. The jockeying for position in the hype cycle will continue, but just as the blush is wearing off on full-on AI (a la the “magic sauce” quote from Chris Mims’ WSJ article), Quantum Computing will illegitimately emerge as the next hyped technology, which will not be ready for prime time. Other ExaScale ready technologies can fill this gap needed for applications to solve STEM problems." –
Cheryl Wiebe, Practice Director, Cross-Industry Solution Consulting
“Likely gone are the days of piecemeal analytics and reporting solutions that are likely fulfilling niche business use cases. This is unsustainable. Companies cannot have highly departmentalized analytics implementations that have the effect of localized problem solving and the larger business not seeing the full benefit. This current situation will change into one where analytics will be done on all data that the company has access to, with the capability of these analytics be implemented in a collaborative manner by a variety of interest groups with different skills sets (e.g., data science, lines of business leaders) and with a full-on focus towards operationalizing analytics insights in near real time. In other words, no more piecemeal and no more just science experimentation." --
Sri Raghavan, Director of Data Science and Advanced Analytics
AI & Industry
"We will see widespread implementation of edge computing within the health vertical. Edge-based AI has the potential to deliver new innovative modes of care delivery and can play an important role in situations such as predicting and minimizing downtime for life-saving medical equipment like cat scans. Critical applications can even be applied to patient health data analyses, diagnoses and outcomes." –
Hillary Ashton, Chief Product Officer
"COVID-19 has transformed the retail sector, forcing stores to completely rethink how they engage with customers in order to better protect both them and their employees. Although edge-based AI was already being deployed in these setting through methods such as video surveillance, managing inventory, understanding footfall and more, the technology is now being leveraged in instances such as reinforcing social distancing and recalibrating the layout of store floors to ensure safety. In 2021, we'll see the retail industry continue to increase its investments in edge computing and AI to adapt to new customer preferences." –
Hillary Ashton, Chief Product Officer
"[Technologies to come in 2021 will be] the incorporation of Vision AI, NLP (chatbot), and other Task AI into enterprise analytics, merging real world sensory data with enterprise data for more powerful insights on machine, device, and human behavior. Today, these technologies are seen as ends in themselves. I see the world recognizing these sorts of deep learning applications are just ways to extend the capability of the human to sense, record, and send structured observations to a wider, multi-domain ecosystem of data that create insights on a vast array of data from many sources inside and outside the corporate network. And it goes without saying, all this will be done on the cloud FIRST, and then hardened (at the edge) only as needed for performance. Gaming engines will come out as being big in the realm of generating all the data behind simulated scenarios. Math at Exascale will be huge as we start to tackle some of the big problems in climate change (cloud formation modeling), bio-pharmaceutical, petrochemical (explosion modeling), and gaming, warfighting/targeting." --
Cheryl Wiebe, Practice Director, Cross-Industry Solution Consulting
"AI will move fully into the mainstream. As it is, in 2020, it has been very prominent in industry conversations but now AI as an application in our day to day lives is going to be more prolific and diverse in its application range. Two, Vehicle Automation with smart cars and driverless vehicles are going to be more ubiquitous than before although as a mainstream adoption it still has a long way to go particularly in the form of reaching a comfort level among the larger population of potential users. Three, 5G connectivity is getting more popular and all the network technology today will be focused on delivering this capability for mass use. There are more, but I thought I’d keep it to the top 3 in the interest of brevity." --
Sri Raghavan, Director of Data Science and Advanced Analytics
Acceleration to the Cloud
"In 2020, with the fury of digitalization brought on by lockdowns and other restrictions related to the global pandemic, many firms found that they needed hybrid solutions combining both cloud and traditional on-premise assets. Moreover, this hybrid structure required dynamic resource allocation and workload management and commensurate security, data governance, and master data management capabilities integrated with scalable analytics. In 2021 this cloud/hybrid journey will accelerate." --
Bonnie Holub, Managing Partner, Practice Lead, Data Science, Americas
"According to Forbes, a conservative estimate of cloud investment as a percentage of budgets in 2021 among enterprises in the USA is 32%. This is a significant increase over 2020. Now, not all investments are equal. I still do not think analytics in the cloud is going to take precedence over other applications although its share of cloud implementation is likely going to double in 2021. The core areas of cloud application in order of my prediction are: Storage and archive Disaster recovery and loss of data prevention Content Delivery IoT connectivity Analytics and operationalization." --
Sri Raghavan, Director of Data Science and Advanced Analytics