Future of the Big Data and the Top 7 Successful Companies Which Already Use It

Updated 09 Mar 2023

10 Min




Older people sit down and ask, 'What is it?' but the boy asks, 'What can I do with it?'  - Steve Jobs was right. The new things we get every day have to be applied to real life otherwise they are pointless. This research we want to dedicate to the most successful Big Data startups and how to make money with Big Data. We also need to get acquainted with the trends in Big Data analytics to have all the insights while launching your own startup using Big Data. First of all, let's see what the numbers tell us about a future of BD.

What is the future of Big Data

The majority of modern companies all over the globe have already realized that the data they hold is a valuable strategic resource. According to the EIU research, about 60% of all organizations they surveyed already use data to generate profit. More than 80% uses data to improve their goods and services.

The Statista, reliable analytical portal, estimated that the revenue from Big Data and analytics market will reach $40 billion in 2018, $57 billion in 2020 and $92 billion in 2026.

big data analytics projects revenue

Revenue from Big Data companies

Statista also calculated the revenue by the type of Big Data startups. The revenue from services, hardware and software.

big data startup companies - revenue

Big Data revenue in 2013-2026

It all shows that data is a tool which can be turned into money. Big Data big money. At the same time, lots of company leaders admitted that they face difficulties processing such amount of information. They also state that these issues concern the effectiveness and security of data processing. As we know, organisations which built their business around customers data have to provide the highest level of this information protection. If users feel their data is being used improperly or has no appropriate protection, they will change a vendor immediately.

It brings us to an idea that the giant data flow and it's proper processing is becoming an essential factor for the modern businesses. And this need leads to the development of new systems tools and approaches, which we call Big Data startups.

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Some entrepreneurs have already taken advantage of this need and launched their businesses based on BD analysis. We will share these startups with you to prove that Big Data analytics projects are not only highly required but very profitable and successful as well.

Top 7 best Big Data startups

To tell you the truth, there are so many companies successfully using Big Data and so many amazing Big Data startups that it was very difficult to choose only 7. However, we wanted to show you only the most successful and the most interesting ones. Let's get started.

top big data startups

Big Data startup companies

1. Looker

Looker is a Big Data analytics software company established in 2011. It provides software solutions which help different organizations with Big Data management. With this solutions, the process of data collection and processing become much easier. Moreover, the software improves data sharing among all departments.

The great advantage of this program is that even a non-professional person with no technical background can work with it rather successfully. It all led to a fact that now the company is more than 170 million dollar entity. Looker can also boast about it's cooperation with such big dogs as Amazon and Sony.

2. Reonomy

Reonomy was established in 2013. The company is one of the leaders in Big Data analytics engaged in reals estate business. It collects data from all the possible sources and analyses it and incredibly fast. The main trick is in the speed. Working with CRE markets is often a slow and painful process. The information changes every second and Reonomy offers a great solution to change the experience of real estate business. The startup gathered more than $14 mln investments. Among the sponsor-companies are the Softbank Capital, Bain Capital Ventures and Fintech Collective.

3. Knewton

Knewton is an educational startup which was created in 2008. It offers PaaS solution which is based on the need for personalized education. The program applies Big Data approach and analyses all materials which a student used. After data processing, the system can offer those materials which a user can easily learn or those tasks which a student has to work on better. It offers such content which leads a student the best and the most efficient way for improvement. Today, more than 10 million students use it all over the world. The company has lots of supporters who invested over $150 mln in it.

4. Social Data Collective

Social Data Collective is extraordinary Big Data startup company, which said out loud something that everyone has already known - data is actually money. It is a kind of currency you can convert to something real. That is exactly what the company does. They offer common people a prize (services and goods from their partners) for their personal information. The company explained it with the fact that we never get anything for our information but the companies always pay to the third parties for it. Why can't you simply sell it? And don't think that the company needs your passwords or addresses. No. Here you can share your browsing history, list of apps you use, financial transactions history and wearables or IoT devices you like. The system is simple, the more you share the more you earn. They call it personal data monetization.

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5. Signals Analytics

Signals Analytics is the company, which was founded in 2009 offers businesses a solution which can guide them and actually tell them what to do.

The idea of a startup belongs to two military men, who value data and understand how little signs can influence the outcome of a situation. That is why they decided to apply AI to process all the company's data to predict the most plausible result of one action or another. The solution helps answer critical questions, analyses data and guides business owners in difficult situations. It is worth mentioning that such companies as Nike and Nestle already tested the system. They also helped the startup collect $30 million of investments.

6. DataRobot

DataRobot is a company, established in 2012, which deals with Machine Learning tasks. It's founders established an automated ML platform based on data science. The platform can be used to build very precise predictive models which allow business owners to save money on predictive analytics. The tool is so powerful that it raised $120 million in funding.

7. Gluent

The Gluent startup offers to process data in a brand new way. They call it 'hybrid data'. The idea is to upload data to Hadoop but to keep it accessible. Yet, the company was established in 2015 it already has lots of fans in the IT sphere. One of the biggest is Gartner company.

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Tips how to start a Big Data project

These examples demonstrate how promising the Big Data startups are. However, as any startups, there are lots of pitfalls and issues you need to deal with if you want your big idea to become viral. Below, you will find some do's and don'ts which concern specifically Big Data projects to help you answer a question how to start Big Data company and make everything right.

how to start a big data project

How to start a Big Data company

Start small

If you want to create a vast system with multiple features and tonnes of information to process, you should understand how hard it would be. Besides, you may also need to think thoroughly about the funding of such a startup because it would need lots of it. That's why, we offer you to start with a small project, an MVP, perhaps even with one feature. What it gives you? First of all, you can launch it faster because the development will dure less. Second of all, it is much easier to attract investors and persuade them to give you money. And the last but not the least, if something goes wrong, it is much easier to rebuild it or change it's purpose than if it was a big project.


It is a relatively new area for startups which isn't very occupied by competitors. It means that you have a freedom of choice to make your startup as you want it to be. Earlier, we showed that Big Data startups can be launched for any sphere. Choose the one you like but remember, your product has to solve some real issues of the sphere, otherwise, it will be useless.

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Process data wisely

If you want to start a Big Data company, you should know that all Big Data startups use a 3-steps model. First, they collect data, then they process it and third, they make conclusions (use reports to improve business). The most important stage and the most valuable one is the third. Data has to work for you, it has to improve your (or someone else's) business. Making charts and tables is not enough. Advanced analytics teaches us to apply data and get benefit from it.

Combine machine and human approach

This tip can save you lots of money. It seems to us that only machine can process such amount of data. But it is not quite right. If the data you get from a program is structured, a highly experienced person can process it even faster than a machine. Artificial Intelligence programs are expensive, they require lots of time and efforts to be taught and even after that you can get faulty data due to incorrect processing. A knowledgeable person knows what metrics to pay attention to and which one to ignore. That's why for some operations people is a good and much cheaper alternative to a machine.

Find the team

It is truly one of the most difficult tasks when you get started in Big Data analytics. For many reasons, you should look for people with very strong prying sense. Curious people are always willing to learn new things and ask lots of questions. And it is many times more valuable than some technical skills.

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Find the right tools

Choosing one for your team you need to be pragmatic about your startup future. If the tool is not powerful enough and can't process the continuously growing amount of data, you will fail. On the other hand, paying for an instrument which will work at a half of it's capacity is not a reasonable approach. You can start with a middle-size system. It is a nice move especially if you choose a scalable solution.

Sometimes it takes lots of courage to try. And the statistical figures don't help. We know that only one of ten startups will survive, or even fewer. But if you are armed with knowledge and, what is more important, with a nice Big Data startup idea, you can change the world. Don't think for too long, because someone else can take your place in the Big Data world. Write us, share your idea and let's create something Big!

Frequently Asked Questions
How companies use big data?

Big data helps companies to organize arrays of information and extract new possibilities that were hidden under before.

How big data helps companies?

Big data helps companies to launch efficient marketing strategies, find new audience, detect ineffective processes, and more. To cut the long story short, big data can increase your revenue and improve customer experience.

How do big data companies make money?

The main source of income for big data companies is the distribution of insights. Businesses experience are in a great need of data for marketing and internal processes. That's why insights, delivered by third-parties, are highly valued by companies.

How do companies collect big data?

The most obvious way is to gather information directly from customers. Businesses can ask customers about the quality of service and overall impression. Another way is to indirectly track clients' actions on the app or website.

What companies use big data?
  • Amazon
  • Coca-Cola
  • Netflix
  • PepsiCo
  • John Deere
  • and more
What is a big data company?

A big data company is a vendor that extracts useful data from loads of information and sells it to other companies.

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About author

Evgeniy Altynpara is a CTO and member of the Forbes Councils’ community of tech professionals. He is an expert in software development and technological entrepreneurship and has 10+years of experience in digital transformation consulting in Healthcare, FinTech, Supply Chain and Logistics

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