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Order From Chaos: How Big Data Will Change the World

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Order From Chaos: How Big Data Will Change the World

Harnessing the exponential surge in data creates big opportunities.

Thanks to Purefunds Big Data ETF (BDAT) for helping us put this together.

IBM estimates that each day, 2.5 quintillion bytes of data are created or replicated. That’s the equivalent of a million hard drives filling up with data every hour.

The current volume of data created is substantial: it is so much that 90% of the world’s data has been created in the last two years. However, the amount of information today pales in comparison to what our future holds, as the rate at which data is created is accelerating exponentially.

It’s for this reason that The Economist estimates that there will be roughly 7x more data in 2020 than there was in 2014.

Where Does Big Data Come From?

Big data comes from both internal and external sources. Internally, millions of old documents and records are scanned and archived by businesses. Most of the time, no detailed analytics have ever been run on this information. Externally, the public web offers millions of data sets published for public consumption by government, economic, census, and other sources.

There’s also a broad spectrum of data that exists that can be a part of both of these categories: social media posts, documents, emails, business applications, machine log data, media, and sensor data can all be collected, processed, and analyzed. To get a sense of the extent of this information, here’s what is created every hour just from social media and email: 72 hours of video uploaded to Youtube, 4 million search inquiries on Google, 200 million emails sent, 2.5 million shares on Facebook, and 300,000 tweets made.

Big Data = Big Opportunities for Business

With proper analysis, Big Data can lead to new understandings of consumer behaviour, better management decisions, new innovations, and improved risk management. However, there are big challenges in making use of so much information.

  • Too much data creates an information overload.
  • Organizing and storing all of this data can be problematic.
  • Companies don’t know how to use all of this data to create insight.

To organize and make sense of it all, data scientists use the three V’s to describe Big Data.

Volume is the scale at which data is created, and includes the massive amounts of information derived from phones, internet users, machine logs, and internet of things.

Velocity is the analysis of streaming data: for example, modern cars have 100 sensors that monitor different systems in real-time.

Variety is the different forms of data, and it reflects the fact that data comes in all shapes and forms. Finding a way to harmonize multiple types of data can be quite a challenge. Research finds that organizations spend up to 80% of their time modelling and preparing data, rather than actually gaining insight.

Let’s see how companies have been able to use Big Data to create opportunity.

Case Studies of Big Data

Macy’s adjusts pricing in near-real time for 73 million items based on demand and inventory.

American Express developed predictive models that analyze historical transactions and 115 variables to forecast the loyalty of customers. Using this data, they can see if customers may be potentially closing their accounts in the near future. Launching a pilot program in Australia, the company can now identify 24% of accounts in the country that will close in the next four months.

Walmart built a new search engine for their website that includes semantic data relying on text analysis, machine learning, and even synonym mining to create better search results. Online shoppers have been more likely to complete purchases as a result by 10% to 15%, increasing revenue by billions.

Los Angeles and Santa Cruz police departments have used an algorithm that is typically used to predict earthquakes, now using it to look at crime data. The software can predict where crimes are likely to occur down to 500 square feet. In areas the software is being used, there has been a 33% reduction in burglaries and a 21% reduction in violent crimes.

Big Market

Today’s data centers occupy the land to equivalent to almost 6,000 football fields. By 2020, the amount of digital information is expected to increase exponentially to more than 7x of what it is today.

In healthcare alone, Big Data is expected to eventually save $300 billion per year in healthcare analytics. Retailers may increase margins up to 60% through Big Data analytics.

“Information is the oil of the 21st century, and analytics is the combusion engine.” – Peter Sondergaard, Gartner Research.

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Animation: How Tech is Eating the Brand World

Changing consumer expectations have created a harsh environment for traditional brands to operate in—will tech companies make them obsolete?

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How Technology is Eating the Brand World

Building a brand with an imperishable competitive edge can be difficult.

Technology companies however, are redefining what that edge means. By hastily responding to emerging consumer needs and leveraging the power of brand, these companies can continuously create meaningful solutions for real problems with scale.

Today’s animated chart highlights the most valuable brands in 2019 versus 2001, according to the annual “Best Global Brands” ranking by Interbrand. It illustrates the degree to which technology companies have been able to scale into massive brands over a short time frame, supplanting some of the best known companies in the world.

What is Brand Value, and How is it Measured?

Interbrand has created and consistently used a robust formula to measure brand value. Brand value is the Net Present Value (NPV) or the present value of the earnings that a brand is forecasted to generate in the future.

The formula evaluates brands based on their financial forecast, brand role, and brand strength. The full methodology can be found here.

Tech Reigns Supreme

In 2001, the cumulative brand value was $988 billion. Today, that value stands at $2.1 trillion and represents an average CAGR of 4.4%. Over the years, global tech giants have swiftly climbed the ranks, and now represent a significant amount of the total brand value.

In fact, with a combined brand value of almost $700 billion, tech companies account for half of the top 10 most valuable brands in the world. Perhaps unsurprisingly, Apple holds the title for the world’s most valuable brand in 2019—for the seventh year running.

Only 31 brands from the 2001 ranking remain on the Best Global Brands list today, including Disney, Nike, and Gucci. Coca-Cola and Microsoft are the few who have remained in the top 10.

Below is the full list of the world’s most valuable brands:

RankBrandBrand Value ($B)1-Yr Value ChangeIndustry
#1Apple$234B9%Technology
#2Google$168B8%Technology
#3Amazon$125B24%Technology
#4Microsoft$108B17%Technology
#5Coca-Cola$63B-4%Beverages
#6Samsung$61B2%Technology
#7Toyota$56B5%Automotive
#8Mercedes Benz$51B4%Automotive
#9McDonald’s$45B4%Restaurants
#10Disney$44B11%Entertainment
#11BMW$41B1%Automotive
#12IBM$40B-6%Business Services
#13Intel40B-7%Technology
#14Facebook$40B-12%Technology
#15Cisco$35B3%Business Services
#16Nike$32B7%Retail
#17Louis Vuitton$32B14%Retail
#18Oracle$26B1%Business Services
#19General Electric$25B22%Diversified
#20SAP$25B10%Business Services
#21Honda$24B3%Automotive
#22Chanel$22B11%Retail
#23American Express$22B13%Technology
#24Pepsi$20B-1%Beverages
#25J.P Morgan$19B8%Finance
#26Ikea$18B5%Retail
#27UPS$18B7%Logistics
#28Hermes$18B9%Retail
#29Zara$17B-3%Retail
#30H&M$16B-3%Retail
#31Accenture$16B14%Business Services
#32Budweiser$16B3%Alcohol
#33Gucci$16B23%Retail
#34Pampers$16B-5%FMCG
#35Ford$14B2%Automotive
#36Hyundai$14B5%Automotive
#37Gillette$14B-18%FMCG
#38Nescafe$14B4%Beverages
#39Adobe$13B20%Technology
#40Volkswagen$13B6%Automotive
#41Citi$13B10%Financial Services
#42Audi$13B4%Automotive
#43Allianz$12B12%Insurance
#44ebay$12B-8%
#45Adidas$12B11%Fashion
#46Axa$12B6%Insurance
#47HSBC$12B5%Finance
#48Starbucks$12B23%Restaurants
#49Philips$12B-4%Electronics
#50Porsche$12B9%Automotive
#51L’oreal$11B4%FMCG
#52Nissan$11B-6%Automotive
#53Goldman Sachs$11B-4%Finance
#54Hewlett Packard$11B4%Technology
#55Visa$11B19%Technology
#56Sony$10B13%Technology
#57Kelloggs$10B-2%FMCG
#58Siemens$10B1%Technology
#59Danone$10B4%FMCG
#60Nestle$9B7%Beverages
#61Canon$9B-9%Technology
#62Mastercard$9B25%Technology
#63Dell Technologies$9BNewTechnology
#643M$9B-1%Technology
#65Netflix$9B10%Entertainment
#66Colgate$9B2%FMCG
#67Santander$8B13%Finance
#68Cartier$8B7%Luxury
#69Morgan Stanley$8B-7%Finance
#70Salesforce$8B24%Technology
#71Hewlett Packard Enterprise$8B-3%Technology
#72PayPal$8B15%Technology
#73FedEx$7B2%Logistics
#74Huawei$7B-9%Technology
#75Lego$7B5%FMCG
#76Caterpillar$7B19%Diversified
#77Ferrari$6B12%Automotive
#78Kia$6B-7%Automotive
#79Corona$6B15%Alcohol
#80Jack Daniels$6B13%Alcohol
#81Panasonic$6B-2%Technology
#82Dior$6B16%Fashion
#83DHL$6B2%Logistics
#84John Deere$6B9%Diversified
#85Land Rover$6B-6%Automotive
#86Johnson & Johnson$6B-8%Retail
#87Uber$6BNewTechnology
#88Heineken$5,6264%Alcohol
#89Nintendo$6B18%Entertainment
#90MINI$5B5%Automotive
#91Discovery$5B-4%Entertainment
#92Spotify$5B7%Technology
#93KFC$5B1%Restaurants
#94Tiffany & Co$5B-5%Fashion
#95Hennessy$5B12%Alcohol
#96Burberry$5B4%Fashion
#97Shell$5B-3%Energy
#98LinkedIn$5BNewTechnology
#99Harley Davidson$5B-7%Automotive
#100Prada$5B-1%Fashion

Since 2001—the first year the report featured 100 brands—several tech companies have joined and climbed their way to the top of the list, while 137 notable brands dropped off entirely, including Nokia and MTV.

In an interesting turn of events, Facebook dropped out of the top 10, and into 14th place after a volatile year. The move however, is not surprising. The tech giant has been mired in controversies, ranging from data privacy issues to prioritizing political influence.

Which Brands Are Growing the Fastest?

2019’s fastest growing brands also signals tech domination, with Mastercard, Salesforce and Amazon leading the charge.

The companies in this ranking experienced a significant increase in their brand value year-over-year (YoY).

RankBrandBrand Value ($B)YoY Growth
#1Mastercard$9B25%
#2Salesforce$8B24%
#3Amazon$125B24%
#4Gucci$16B23%
#5Starbucks$12B23%
#6Adobe$13B20%
#7Visa$11B19%
#8Caterpillar$7B19%
#9Nintendo$5B18%
#10Microsoft$109B17%

According to Interbrand, the success of these brands may be attributed to their ability to anticipate rapidly changing customer expectations.

While the relationship between business performance and brand equity has been a widely debated topic for decades, it is clear that customer satisfaction bolsters brand equity, and encourages impressive financial results.

Disrupt, or Be Disrupted

Beyond anticipating changing needs, some of the most successful brands also cater to a younger customer base. This is the most evident in luxury and retail—the two fastest growing sectors for the second consecutive year.

This audience is tech-first in their buying habits and increasingly demand more elevated and shareable experiences. As a result, traditional brands across all sectors are innovating to keep up with this audience, and some are essentially becoming tech companies in the process.

For example, Gucci attributes their success to finding the perfect blend between creativity and technology. The company that once relied on its heritage, now focuses heavily on ecommerce and social media to engage with their Gen Z customers.

Similarly, Walmart recently announced that they are employing virtual reality headsets and machine-learning-powered robots in an attempt to compete with Amazon.

Will traditional companies ultimately become tech companies, or simply get eaten alive?

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A Visual Timeline of AI Predictions in Sci-Fi

AI is shaping the global economy in unprecedented ways, and transforming life as we know it—but science fiction has predicted this all along.

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They say you shouldn’t believe everything you see on the big screen.

However, in the case of science fiction, the human imagination has gotten a few things right—especially when it comes to futuristic forecasts. Today, the artificial intelligence (AI) revolution is transforming everything, but it turns out we had a hunch about it all along.

When AI Comes to Life

Today’s infographic from Noodle.ai takes a look at how some movie and television predictions for AI’s capabilities have taken hold in the real world.

AI Predictions in Science Fiction

Many early “predictions” about future technologies certainly missed the mark—but it seems science fiction was able to accurately forecast a thing or two about AI.

AI Basics: Making Life Better

Artificial intelligence is all about equipping machines with the ability to mimic human decision-making processes. It has a wide range of applications, from basic automation to advanced machine learning models.

AI has proliferated into virtually every aspect of life, and in the graphic, it’s clear that several sci-fi-turned-real inventions are aimed at making things more convenient for us humans.

Sci Fi PredictionAI in Reality
1962: The Jetsons cartoon shows video calls on a tv screen, and a robot maid.2002: iRobot Roomba is the first robotic vacuum.
2018: Facebook Portal is a video-calling smart display.
2019: Moley robotic kitchen is able to prep meals from scratch and clean up afterwards.
1966: Star Trek inspired several tech innovations that have become commonplace.Examples include: Bluetooth headsets, voice assistants, cellphones, and automatic sliding doors.
1989: Back to the Future features smart glasses for television and phone calls, and a smart watch which can precisely predict weather.2012: The Dark Sky app provides custom alerts on the weather to the minute.
2013: Google Glass is able to make calls, send texts, display photos, and provide directions.
2015: Apple Watch comes enabled with WiFi, Bluetooth, a GPS, and even a heart sensor.
1999: Smart House showcases a fully automated house that is able to respond to verbal requests, cook and clean, and control thermostat settings.2019: A HGTV contest lets people win a WiFi connected smart house, complete with voice-enabled thermostat and security systems.

Of course, these have had varying degrees of success. While Google Glass didn’t initially resonate with the wider public, the augmented reality smart glasses have now proved useful in businesses such as manufacturing.

Elsewhere, sci-fi-inspired advances in industries like healthtech are providing a new lease of life for many patients—and continuously reinventing the frontier of what we think is possible.

Sci-Fi Helps Us Push Boundaries

One monumental event in AI history occurred in 1997, when IBM’s Deep Blue beat a chess master at his own game. This event shook the world when we realized what AI could truly be capable of—even though sci-fi had in fact anticipated it 20 years prior.

But as the graphic shows, not all is rosy in science fiction’s likeness of AI. It’s often depicted as something to fear, and certain predictions have proved to be eerily accurate.

Sci Fi PredictionAI in Reality
1977: K9, a robotic dog in Doctor Who, beats its master at a chess game.1997: IBM’s Deep Blue computer beats a Russian chess master, Garry Kasparov.
1984: Skynet from Terminator, a self-aware AI program, attempts to extinguish humanity.2019: The U.S. Army creates an autonomous system to “acquire, identify, and target threats” (ATLAS AI).
2011: AI monitors surveillance cameras and predicts future criminals in Person of Interest.2018: The National Data Analytics Solution (NDAS)

While not all of these are causes for alarm, they clearly demonstrate that sci-fi has the capacity to influence the breakthrough technology we could end up seeing a few years down the line. However, turning reel to real can raise some curious dilemmas.

Rights for Robots?

Last year, the European Parliament debated an interesting question: do robots qualify as people?

The resolution considered granting “personhood” to sophisticated, autonomous robots. However, over 150 AI experts strongly warned against this proposal, arguing it would “blur the relation between man and machine” in a way that is too unethical.

Nevertheless, this thought experiment proves that artificial intelligence is matching our wildest imagined predictions for it.

AI is whatever hasn’t been done yet.

—Tesler’s Theorem

As we move ever closer towards a world where AI is inextricably linked with the everyday, how else could science fiction shape our expectations of the future?

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