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Here’s what a tech-enabled world will look like for future pandemic phases

15 minutes read

The COVID-19 pandemic or what may be more suitably described as a black swan event that disrupted the general mechanism of daily life and businesses globally has also led to life in the new normal. This paradigm shift relies on automated services, contactless payments, digital healthcare including the rise of mental health apps, Artificial Intelligence and Augmented Reality-led innovations, e-customer support, video conferencing for remote work possibilities, amongst others. 

The World Robotics 2020 Industrial Robots report, published in September 2020, shows a record of 2.7 million industrial robots operating in factories around the world – an increase of 12%. Sales of new robots remain on a high level with 373,000 units shipped globally in 2019. This is 12% less compared to 2018, but still, the 3rd highest sales volume ever recorded.

Researchers from the University of Palermo programmed SoftBank’s Pepper robot to voice its “thinking process” while carrying out a series of tasks, including running restaurant operations, thus giving it a human touch with a scope of emotional intelligence. 

“If you were able to hear what the robots are thinking, then the robot might be more trustworthy,” co-author Antonio Chella explained in a press release, describing first author Arianna Pipitone’s idea that launched the study at the University of Palermo.

“The robots will be easier to understand for laypeople, and you don’t need to be a technician or engineer. In a sense, we can communicate and collaborate with the robot better,” Chella continued.

Amid the pandemic, a NASSCOM report suggests that the technology industry has grown by 2.3 percent despite COVID-19, and India has emerged as the third-largest tech startup globally. 

In their Strategic Review 2021 report titled ‘New World: The Future is Virtual’, NASSCOM said that India’s technology industry contributes around 8 percent relative share to the national GDP, with 52 percent relative share in services exports, and 50 percent share in total FDI (based on FDI inflows from April to September 2020), as reported by YourStory. 

“The technology industry has weathered past crises and found novel ways to emerge stronger each time. In fact, tech companies have led the way on a variety of strategies other industries are now using to cope in this crisis — from remote working to a globally dispersed supply chain to managing through disruption. This crisis might well spark further creativity and innovation,” says PwC in a report titled ‘COVID-19 and the technology industry.’ 

What may be termed as a seismic shift in consumer behavior, owing to the long spate of lockdown and people increasingly staying home over the last many months, here are some of the noteworthy changes we’ve noticed thus far: 

Eating out, ordering in, and the behavioral shift

The pandemic amounted to huge losses to the hospitality and service industry globally when lockdowns were imposed. While most countries began easing restrictions as the first coronavirus wave plateaued, there were also plenty of innovations that came to light during this time. From quirky social distancing measures such as noodle hats that ensured 3ft distance from the next customer at a cafe in Europe to mannequins filling empty tables so diners wouldn’t feel alone and robots managing restaurant operations in Japan, the year 2020 has also given rise to the best alternatives as most people stay home. 

Additionally, the year was also one with a surge in food deliveries, while restaurants and QSRs ensured that customers regained trust in the hygiene and packaging techniques followed by them amid this time. With introductions like voice-based instructions within food delivery apps, no-contact deliveries, and special instructions possible, food and essential delivery services have seen a significant upward trend. 

“Health and social schedules are only two of the most common worries that consumers express about the ongoing crisis. There are still many more who worry about the overall economy and their personal finances, however, and others who feel no fear at all,” reads this report by pymnts.com released in early May 2021. 

Virtual Shopping meets Augmented Reality Experiences

Luxury fashion brand Gucci is expanding its presence on Roblox, a metaverse and gaming platform immensely popular with pre-teens, with a virtual two-week art installation. Visitors here can enter through a lobby in which their virtual avatars can view, try on and purchase digital Gucci items.

Image Courtesy: blog.roblox.com 

ALSO READ: Augmented Reality: A solution to the timeless insurance concerns

“Of course, it’s no surprise that luxury fashion brands want to position themselves at the center of an industry that made $175 billion in 2020, one with an increasing number of women. A 2020 report from the Entertainment Software Association found that women account for 41 percent of all gamers in the United States. Esports are also infiltrating popular culture, with an audience that’s predicted to reach 729 million in 2021, according to research from Newzoo,” reads an article by The Wired titled Luxury Fashion Brands Turn to Gaming to Attract New Buyers

In the year 2020, Ralph Lauren collaborated with Snapchat, thus revealing a quirky side to the luxury fashion house by letting younger customers try on the brand’s wear in various avatars. 

On the social media front, Snap announced the latest (fourth) generation of its Spectacles, a ‘60s-style design in black. These AR-capable Spectacles arrive shortly ahead of Facebook’s upcoming smart glasses, which will be a collaborative effort between the social media giant and Ray-Ban. These glasses are said to rely heavily on other forms of input as they won’t be released with built-in displays. Apple, too, is rumored to be working on augmented reality glasses, says a report by TechCrunch.

The German decor lighting app, Luminaire, which lets you try out light fixtures at a space of your choice, uses AR to bring a store-like experience closer to home. Its functioning is nearly akin to IKEA’s app that too, via AR, allows consumers to try out furniture before placing an order for the physical addition to their homes or offices. Fashion giants Burberry and Dior experimented with similar technologies for the handbags and sunglasses collections, respectively. Lipstick sales that saw a dip last year because of mask fashion taking over are back with a bang (almost) but multi-brand store Sephora had introduced their AR innovation which allowed consumers to try on lipsticks on their face (instead of the age-old try-on method). 

Instagram, previously only a photo-sharing app is now a revolutionary space for brands to connect with their consumers. The best part could probably be the addition of the shopping tag within the app so you can buy what you like almost instantly instead of waiting for it to hit the stores or looking for the same product on an e-commerce site. 

Remote Work, The Rise of Ed-Tech and more

Video conferencing is now an integral part of every professional’s life at work, even with family members or pets accidentally popping into your screens. What had begun with a month of proposed work from home has gone on for over a year and so, is a defining moment of the new normal. 

Zoom, Google Meet, Windows Meeting Room, are some of the most widely used apps for work calls, webinars, online sessions, and have also helped bridge the gap between teachers and their students in the recently-concluded academic year. Ed-Tech, hence, is being touted to be one of the fastest growing industries aided by the pandemic-led lockdowns. 

“Although EdTech is an emerging market that was steadily gaining pace, COVID-19 gave it the extra momentum, making way for the sector’s massive expansion. India’s EdTech market is all set to increase by 3.7 times in the upcoming five years, growing from US$ 2.8 billion (in 2020) to US$ 10.4 billion by 2025),” said UpGrad on their official blog. 

In this year’s edition of Google I/O, we also met the proposed 3D conferencing service titled Project Starlight, which will let you ‘see’ the person on the other side of the screen just like they were sitting across from you in person. 

E-consultation

The COVID-19 pandemic and the subsequent lockdown was also a year of spiked cases of anxiety, depression, and other mental health-related issues. For any physical ailments (non-COVID-related primarily), apps came to the rescue for online consultations and diagnosis. 

AI facilitated the rise and growth of emotionally intelligent apps such as Wysa or meditation-led apps such as Headspace and Calm. 

Take a look at a short conversation I had with Wysa to help me understand how she could walk with me through a stressful day. There are options to listen to music that helps relieve stress and in more stressful situations, seek professional help through the app. 

Contactless payments, Banking services, and more
Even though net banking and mobile banking were already on the rise pre-pandemic, the years 2020 and 2021 have shown a significant change in the way a customer banks and uses other financial services. Seeing this shift, banks including the State Bank of India changed their strategy and also introduced ‘at home’ banking that even allows one to open bank accounts at the comfort of their homes instead of the usual rule of visiting the home branch to do the needful. 

AI-led bots also work closely with customer support teams, helping with the first-level customer service and if the need arises, then speak to a human being on the other end of the line. This innovation has been significant in truncated any need for IVR systems, previously employed at contact centers. But that’s not all, you can also use AI to help with queries around insurance, whether you need insurance and which one to get that’s best suited to your needs. 

What’s next? 

There’s a high probability of XR and MR-led innovations taking over the market and further altering consumer behavior in terms of their food, recreation, fitness, shopping habits. Imagine a world of drone-led food deliveries and more sympathetic aka emotionally intelligent artificial intelligence that guides you to the right choice. 

Take a look at how the now delayed Tokyo 2020 Olympics were all-set to work closely with robots of different kinds during the games:

Life in the new normal has pushed most industries to innovate beyond their best-known practices were pre-pandemic. Even with a trial and error that may look like growth and substantial change is slow, there’s been a significant behavioral change which gives impetus to a renewed way of approaching business strategies and more. 

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Lake, Lakehouse, or Warehouse? Picking the Perfect Data Playground

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In 1997, the world watched in awe as IBM’s Deep Blue, a machine designed to play chess, defeated world champion Garry Kasparov. This moment wasn’t just a milestone for technology; it was a profound demonstration of data’s potential. Deep Blue analyzed millions of structured moves to anticipate outcomes. But imagine if it had access to unstructured data—Kasparov’s interviews, emotions, and instinctive reactions. Would the game have unfolded differently?

This historic clash mirrors today’s challenge in data architectures: leveraging structured, unstructured, and hybrid data systems to stay ahead. Let’s explore the nuances between Data Warehouses, Data Lakes, and Data Lakehouses—and uncover how they empower organizations to make game-changing decisions.

Deep Blue’s triumph was rooted in its ability to process structured data—moves on the chessboard, sequences of play, and pre-defined rules. Similarly, in the business world, structured data forms the backbone of decision-making. Customer transaction histories, financial ledgers, and inventory records are the “chess moves” of enterprises, neatly organized into rows and columns, ready for analysis. But as businesses grew, so did their need for a system that could not only store this structured data but also transform it into actionable insights efficiently. This need birthed the data warehouse.

Why was Data Warehouse the Best Move on the Board?

Data warehouses act as the strategic command centers for enterprises. By employing a schema-on-write approach, they ensure data is cleaned, validated, and formatted before storage. This guarantees high accuracy and consistency, making them indispensable for industries like finance and healthcare. For instance, global banks rely on data warehouses to calculate real-time risk assessments or detect fraud—a necessity when billions of transactions are processed daily, tools like Amazon Redshift, Snowflake Data Warehouse, and Azure Data Warehouse are vital. Similarly, hospitals use them to streamline patient care by integrating records, billing, and treatment plans into unified dashboards.

The impact is evident: according to a report by Global Market Insights, the global data warehouse market is projected to reach $30.4 billion by 2025, driven by the growing demand for business intelligence and real-time analytics. Yet, much like Deep Blue’s limitations in analyzing Kasparov’s emotional state, data warehouses face challenges when encountering data that doesn’t fit neatly into predefined schemas.

The question remains—what happens when businesses need to explore data outside these structured confines? The next evolution takes us to the flexible and expansive realm of data lakes, designed to embrace unstructured chaos.

The True Depth of Data Lakes 

While structured data lays the foundation for traditional analytics, the modern business environment is far more complex, organizations today recognize the untapped potential in unstructured and semi-structured data. Social media conversations, customer reviews, IoT sensor feeds, audio recordings, and video content—these are the modern equivalents of Kasparov’s instinctive reactions and emotional expressions. They hold valuable insights but exist in forms that defy the rigid schemas of data warehouses.

Data lake is the system designed to embrace this chaos. Unlike warehouses, which demand structure upfront, data lakes operate on a schema-on-read approach, storing raw data in its native format until it’s needed for analysis. This flexibility makes data lakes ideal for capturing unstructured and semi-structured information. For example, Netflix uses data lakes to ingest billions of daily streaming logs, combining semi-structured metadata with unstructured viewing behaviors to deliver hyper-personalized recommendations. Similarly, Tesla stores vast amounts of raw sensor data from its autonomous vehicles in data lakes to train machine learning models.

However, this openness comes with challenges. Without proper governance, data lakes risk devolving into “data swamps,” where valuable insights are buried under poorly cataloged, duplicated, or irrelevant information. Forrester analysts estimate that 60%-73% of enterprise data goes unused for analytics, highlighting the governance gap in traditional lake implementations.

Is the Data Lakehouse the Best of Both Worlds?

This gap gave rise to the data lakehouse, a hybrid approach that marries the flexibility of data lakes with the structure and governance of warehouses. The lakehouse supports both structured and unstructured data, enabling real-time querying for business intelligence (BI) while also accommodating AI/ML workloads. Tools like Databricks Lakehouse and Snowflake Lakehouse integrate features like ACID transactions and unified metadata layers, ensuring data remains clean, compliant, and accessible.

Retailers, for instance, use lakehouses to analyze customer behavior in real time while simultaneously training AI models for predictive recommendations. Streaming services like Disney+ integrate structured subscriber data with unstructured viewing habits, enhancing personalization and engagement. In manufacturing, lakehouses process vast IoT sensor data alongside operational records, predicting maintenance needs and reducing downtime. According to a report by Databricks, organizations implementing lakehouse architectures have achieved up to 40% cost reductions and accelerated insights, proving their value as a future-ready data solution.

As businesses navigate this evolving data ecosystem, the choice between these architectures depends on their unique needs. Below is a comparison table highlighting the key attributes of data warehouses, data lakes, and data lakehouses:

FeatureData WarehouseData LakeData Lakehouse
Data TypeStructuredStructured, Semi-Structured, UnstructuredBoth
Schema ApproachSchema-on-WriteSchema-on-ReadBoth
Query PerformanceOptimized for BISlower; requires specialized toolsHigh performance for both BI and AI
AccessibilityEasy for analysts with SQL toolsRequires technical expertiseAccessible to both analysts and data scientists
Cost EfficiencyHighLowModerate
ScalabilityLimitedHighHigh
GovernanceStrongWeakStrong
Use CasesBI, ComplianceAI/ML, Data ExplorationReal-Time Analytics, Unified Workloads
Best Fit ForFinance, HealthcareMedia, IoT, ResearchRetail, E-commerce, Multi-Industry
Conclusion

The interplay between data warehouses, data lakes, and data lakehouses is a tale of adaptation and convergence. Just as IBM’s Deep Blue showcased the power of structured data but left questions about unstructured insights, businesses today must decide how to harness the vast potential of their data. From tools like Azure Data Lake, Amazon Redshift, and Snowflake Data Warehouse to advanced platforms like Databricks Lakehouse, the possibilities are limitless.

Ultimately, the path forward depends on an organization’s specific goals—whether optimizing BI, exploring AI/ML, or achieving unified analytics. The synergy of data engineering, data analytics, and database activity monitoring ensures that insights are not just generated but are actionable. To accelerate AI transformation journeys for evolving organizations, leveraging cutting-edge platforms like Snowflake combined with deep expertise is crucial.

At Mantra Labs, we specialize in crafting tailored data science and engineering solutions that empower businesses to achieve their analytics goals. Our experience with platforms like Snowflake and our deep domain expertise makes us the ideal partner for driving data-driven innovation and unlocking the next wave of growth for your enterprise.

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