Big Data. A technology buzzword that you have probably heard of more than once and may or may not be sick of hearing about.
In this article, you’ll discover what Big Data really is, and what sets it apart from regular data. Included below is a list of Big Data startups in Europe that you should be keeping an eye on, as well as an analysis of the market.
So, what exactly is big data and why is it causing such a fuss?
Depending on the source, the definition of big data is varied.
The common and go to definition comes from Gartner’s who, in 2001, defined big data as “high-volume, high-velocity and/or high-variety information assets that demand cost-effective, innovative forms of information processing that enable enhanced insight, decision making, and process automation.”
In simpler terms, it is the gathering of large unstructured data sets. That could be the newsfeed of your LinkedIn, the news articles that you click on, the videos you watch.
That data is analyzed to identify trends and patterns using computational methods and structuring it improves our understanding of customer wants and needs.
And our ability to work with the unlabeled and unstructured mess that it Big Data dramatically shifted in 2012 when, for the first time, humans discovered how to work with deep learning neural networks.
Prior to this date, deep learning was considered an impossible task that, in theory, made sense, but in practice, was useless. It wasn’t until it was used in a study of the worlds largest data set of images that its potential was realized.
This threw AI into the forefront and made it possible to work with Big Data (in this case, machine learning would not work as it is in need of structured data and supervision).
[Related article – The Best AI Startups in Europe]
Every click, scroll, movie watched, item purchased…you name it, that data is stored somewhere. Even by reading this article you are leaving a digital trail behind you. And it is ALL unstructured.
With the rise of the internet, the amount of unstructured and semi-structured data has increased and it is hella difficult to analyze, let alone gain valuable insights from.
Healthcare is just one sector greatly benefitting from this. For example, according to Google they created an algorithm that can detect with 99 percent accuracy, metastatic breast cancer.
Unsurprisingly not all Big Data is used for the common good. There is resistance to the use of our data. And our lack of trust does not come as a surprise.
Take the Cambridge Analytica scandal where over 87 million Facebook users personal data was used without consent. One such example was the use of this information to support voters that were considered “persuadable” to vote to leave the EU.
Did that help the situation? Absolutely not. If anything, it made us more skeptical then ever.
The friction is noticeable and we are not used to our data being handled. Even if the new intelligence and data is used to create better experiences and service from customers.
“Companies need to treat data like a valuable asset or raw material,” – Ray Eitel-Porter, managing director at Accenture Analytics
We’re creatures of habit. And the data we produce every day is telling. But as skeptical as we are, there is something positive that can come from the data we create.
There is much to learn and we have only scratched the surface. Our reluctance is not helped by the fact that we are yet to fully understand what to do with these masses of data.
And it has given rise to a whole new breed of startup.
The company provides solutions that help operate unstructured text data. Natural Language Understanding (NLU) solutions are offered based on brain-inspired Semantic Folding technology.
The company specializes in software development and consulting in scalable and Big Data processing systems. Among their offered services the following can be found: software development, technology consulting, MongoDB, managed services, corporate training, and CTO as a service.
Opinum specializes in environmental and energy data administration. They have developed a platform, Opisense, which makes it possible to save time and resources used by consumers.
Koola uses a Smart CRM platform to connect car dealerships and its clients by using Ai and machine learning in order to increase customer satisfaction and the revenues of the dealership.
IndigoVerge owns the company that provides service for Original Equipment Manufacturers (OEMs). They aim to help their customers achieve their goals in business by blending IoT based results in their products and services.
A data platform for businesses that makes maps accessible even when offline. The goal is to create advanced technologies that are not complicated to use, showing the gains of GIS globally.
An analytics platform that helps companies automate data-handling processes. The goal is to save time for companies so that they put their customers first.
An innovative AI startup that connects corporations, enterprises, accelerators and investors with agile early-stage startups for collaboration and partnerships.
An educational software used to learn a language with a “smart algorithm that tracks the progress and mistakes of users”.
Beemray integrates location data, product automation and customer experience, all in real-time. They collect your digital touch points, create segments that are behavioral based, discover broad UI for customers and make the audience litigable.
The company´s mission is to make it easier for businesses and people to operate with fraud detection and claim automation.
An innovative tool, Leverton helps to manage corporate documentation. They generate relevant insights from disorganized data found in legal and corporate documents.
A helpful tool for retail businesses who want to secure their data. A management app in order to control their everyday transactions including shifts, suppliers, customers.
Used for video ads based on biometric data of users and an affecting insight from the aimed audience. This tool is helpful for advertisers and all types of businesses.
Based on business data analytics, perfect for your business’ optimization. Their platform applies Ai in order to get valuable insights to bring decision support to the whole management team.
Boxever is a personalization platform that uses data and AI to make every single customer interaction – whether on a website, smartphone or in person – smarter.
Operating in the Ai industry, this company is based on Natural Language Interaction. Based on their Ai, users of Askdata ask questions using Natural Language and receive data in an easy and understandable way.
A data visualisation software lab that proposes data visualisation software through visual interfaces.
A personal esports training lab. Their main focus is on Gaming Data and AI. They help with the analysis of data making it possible to enhance the user experience. Their platform applies the computer’s intelligence of the gaming data.
The main focus of this platform is omnichannel technology. It gives a deeper knowledge of the people visiting the business by providing a higher level of customer satisfaction.
This is a great tool to organize your company. Here you can get in touch with all your customers, projects and ideas in the same place.
An innovative technology company that aids in the development of software. The GitLab platofrm offers a single application for the entire Development Operations lifecycle, meaning that all can contribute to the development of software.
Mindfulness and experience is the main concept of the company, which helps you communicate with all your business partners using an idea management software.
A management tool based on online media monitoring helps find trendy and innovative ideas for your business. It gives you the opportunity to connect with your target market in a simpler way.
Wizdee are enthusiasts in democratising access to data. Using everyday language to seek data from numerous sources.
TPS Engage wants to make Digital out-of-home (DOOH) more innovative and user-friendly. They provide hourly based deals. This platform is suitable for a wide range of advertisers and networks.
Retail Rocket has the goal of offering consumer-based online shopping support service to thousands of stores. They offer website and email personalization.
Price2Spy is a price monitoring tool. It is useful for corporations to monitor their competitor’s pricing strategies. There is no need to set up or acquire software, they take care of everything.
YesElf provides easy-to-follow steps of tools and software used by departments to simplify the onboarding process. No need for personal training, they use Ai to analyze the user.
Event Registry is a real-time analysis tool that uses Ai to find information on global events mentioned in articles and blogs.
How to control your finances? Users of Fintonic self manage their expenses and income with a platform that is mobile-centric. Currently, it is available in Spain and Chile.
A technical tool for health care companies. Health systems from different countries can together find a solution to improve their service in different sectors. Ivbar has developed a platform called ERA Vision that is able to manage healthcare depending on the value of the treated person.
WealthArc is a FinTech SaaS platform designed for external asset management companies. The solution leverages the latest technologies to enhance client experience, increase efficiency and win new clients. At its core, WealthArc uses innovative banking APIs to provide seamless, real-time integration with custodian banks. Powered by technological advancements, such as cloud computing, artificial intelligence and big data, WealthArc helps wealth managers in harnessing that technology and taking full advantage of automation, data integration and digital processes.
Use this consumer insights platform to get to know your customers. They have developed an Ai engine platform that characterizes the users based on their common interest or differences and in this case advertisers get a deeper insight and understanding of the consumers.
Through this sourcing tool you can search for any vacancies and find the perfect employee for your company. This platform can be used by HR agents and people that are seeking a job.
This enterprise-wide platform improves the cyber security of your business data. The platform is a risk-based aspect of your exposures, dangers but also your assets.
We’re rapidly increasing the sources of where our data comes from. In part, it is attributed to the impact of IoT.
For example, we’re gathering data from the clothing we wear, from the purchases we make in store, to the extensive digital trails we leave behind on a daily basis and somehow this information needs to be connected.
Even if you haven’t told them, Google has a complex ad profile on almost everyone. They know where you live, how old you are, where you travel, who you contact, the searches you make, the online purchases you make through a Google platform, and your live location. The list goes on.
https://twitter.com/Medium/status/1102163665883746310?ref_src=twsrc%5Etfw” target=”_blank” rel=”noopener noreferrer
The storage required to handle this amount of data is so large that it is hosted and processed on the cloud. And boy oh boy is the cloud computing (the access to computing services over the internet) industry benefiting from this newly formed business.
69% of businesses use cloud technology for data storage and backup
One thing remains the same across industries. They want actionable insights from data. But how do you make sense of this data and ensure that you are guaranteed to receive accurate results?
One example shows how big data can be used to predict accurate human behavior. The National Academy of Sciences in collaboration with Cambridge University discovered that the “private traits and attributes” of humans could be predicted with high accuracy “from digital records”.
Using Facebook likes, a personality test, and a data set of 58,000 volunteers the study was able to determine sexual orientation, religious beliefs, sex, age, and ethnicity.
One example showed that if you liked a “Hello Kitty” page, you were more likely to show higher traits of openness, and less likely to be agreeable and emotionally stable. Freaky.
As creepy as this seems, it goes to show that data can be used to determine a number of factors that are incredibly valuable to large corporations.
Big Data is affecting a number of industries. For one, it will provide a 360 view of the customer within organizations through a variety of internal and external sources used internally to help departments operate more effectively and efficiently.
It is also useful in fraud prevention, for example, it can determine potentially fraudulent activity within sectors like banking.
Monitoring of social media whether we like it or not has become a place for finding real insight into customers. It’s where we go to voice their opinions, and companies are beginning to create tools for analyzing and monitoring social activity in real-time.
A report from the NewVantage Partners 2018 Big Data Executive Survey found that “97.2% of executives report that their companies are investing in building or launching big data and AI initiatives”. The industry is also expected to grow exponentially.
And medicine, transportation, banking, retail, and construction will continue to become defined by the huge and ever-expanding entity that is Big Data.
The amount of data we produce on a daily basis is truly mind-blowing. And by 2020, it’s expected that we will produce 1.7 megabytes (MB) of data every second.
In 2014, the total accumulation of data worldwide stood at 4.4 zettabytes (ZB). According to data scientists, it is expected to double every year.
Initially, they had expected the number to increase to 40 ZB by 2020. That’s 40 trillion gigabytes (GB).
They later increased the number to 44ZB to take into consideration the influence of IoT.
Let’s put that into perspective.
One GB = 1 hour on Netflix in high resolution.
That’s 5,022,831,050 years spent watching Netflix.
That’s practically an eternity spent binging.
Because of the constant development of the computer learning industry, it is now possible to do something with the masses of data. And it will continue to affect many industries and aspects of our lives.
From deep learning models that can detect cancer at the same level as trained professionals, self-driving cars, to algorithms that can mimic your voice.
The possibilities are immense. And they come with concerns. The dominant AI players are dependent on the ongoing collection of user data. They are in need of this data to build their machine learning models.
And there is a lack of transparency over the data that is being used to train decision-making algorithms. Are they relevant and so they leading to accurate predictions? With regulations like the GDPR, Europeans hold the right to access data held on them and amend the information, but do we?
There will always a margin of error in data sets. Sometimes this can lead to skewed results. Take Google as an example. In 2018, researchers at Cornell University determined that by setting your gender to female, you’d be less likely to see job ads for high paying jobs.
The House of Commons is looking to control the issues of algorithmic bias, working to maintain the AI market to make sure that the control of data is not monopolized by large organizations.
In the future, we can expect to see more personal interactions and deeper learning. We will also see a trend where companies and government will look to find more efficient and fairer methods of gaining insights from data, according to Wired Magazines annual trend report.
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