4 big data start-ups on the rise

4 big data start-ups on the rise

Big data isn’t just the latest tech buzzword, it’s fast becoming the foundation for businesses across all industries.

With every keyword you type into Google, every post you like on LinkedIn and every time you use your GPS, data is collected. In fact, its reach is so pervasive that Datafloq suggests that big data ‘will be the driving force of the fourth industrial revolution’.

This is because as cross-functional technology becomes more sophisticated, every byte of this data can deliver new insights into a business by:

  • Improving the efficiency and effectiveness of internal processes
  • Helping businesses better understand their customer's pain points and make better decisions
  • Helping customers to make more informed buying decisions
  • Improving the customer experience

Therefore, how we find, interpret and analyse this data becomes increasingly important because when the technology is optimised, the value of data increases exponentially.

However, while big data provides businesses with insights and value, it doesn’t come without its challenges.

Data is not a new phenomenon. What is new is the sheer scale, speed and scope of it. As a result, the ways in which businesses can access, streamline and interpret this data has to become more sophisticated if they want to gain truly valuable insights for their operations.

Enter the problem-solvers. Start-ups who understand the challenges big data presents have created a way for companies to comprehensively harness their data.

Today we’re looking at 4 start-ups who are set to make waves in the next few years.


When CEO and founder of Import, David White sat down with his team he started with the question:

if knowledge is power, how do you get more knowledge than your competitors?

What they found was the web was the fountain of knowledge for businesses, yet gaining access to the raw data, and then knowing how to use it was proving to be an insanely difficult and time-consuming enterprise. Businesses had two options: Spend their day writing code (the hard way) or; Laboriously copying and pasting elements (the mind-numbingly tedious way).

Therefore Mr White and his team wanted to creates something that would ‘allow the flow of data within companies to be smooth and quick, without having to rely solely on the IT department.’

Fast-forward several years and Import has developed an app that anyone can use (no coding experience needed) to scrape their data and to easily turn it into a comprehensive table (or API) in under a minute.

Depending on your need, you can use the app to build your own data set, or Import can build a customised one for you.

In the next few years, they are focused on improving the reach of the business into the education, news and wearable technology markets. The real value of Import lies in understanding that the insights that data brings should be universally accessible. As Mr White states: ‘Companies and individuals that truly understand the potential of data, extracting and using its predictive value, are set to be the big winners over the next five years.’


Businesses don’t just want to access sophisticated data-sets, they want them quickly. Yet given the staggering amounts of data we need to access daily, the process can be very slow. Enter Confluent, the team that founded and built Apache Kafka at LinkedIn. This team has a formidable pedigree. As Forbes states, these are the people ‘who invented the way ‘Twitter manages its tweet analytics, the movie recommendations at Netflix and the surge pricing at Uber all keep running.’ Confluent is the sister idea of Kafka. It’s a service designed to help businesses get access to the enterprise data streams in real-time.

What this does is treat data streams as ‘a type of nervous system.’ It not only means that companies can be immediately responsive to trends and alter elements such as pricing, but the  process itself allows the system to become a little bit smarter each time. This enables customers to make decisions about their business with accurate, real-time data.

3. DataGravity

While speed and scale are two key factors in effectively harnessing your data, we should add another ‘s’ word into the mix: storage. Traditionally data storage has been expensive, especially for medium-sized companies.

DataGravity realised that there was a need for data-stores themselves, rather than only company networks, that needed to be secured. In the past it offered a number of capabilities, including ‘a data-aware storage platform.’ it has recently scaled back their hardware operations in order to focus their energy on their software. As company CEO, Paula long stated:

‘Customers want all of their data to be data-aware, no matter where it lives. Using DataGravity, customers have experienced their data from the storage lens. They see a 360-degree view of their data, and the people interacting with the data over time. This provides the ability to not only gain insights, but also to protect and recover data regardless of security threats, whether they’re physical or virtual.’

However, moving away from a segment, shouldn’t be seen as a diminishing business, rather being discerning and careful. As Long acknowledged: ‘start-ups  that have a tendency to focus on growth at all costs do not cut it in the enterprise tech world.’

4. Domo

In the last few years business intelligence software has meant that accessing and visualising data analytics has become so clean and intuitive that tableau terms it ‘the common language.’

Seeing data in a clear way in real-time can empower business to make proactive and considered decisions about their businesses. Domo is one such company that seeks to make data analytics democratic.

The idea for their business began with highly respected, highly frustrated executives who felt locked out of their own business data. ‘Domosapiens’ (as they call themselves) focus their considerable energies on business owners, stressed execs and thought leaders, who need to be able to access the right data at the right time, collating many disparate data sources. The idea has energised the business world, attracting a whopping $200 million in Series D funding.

What we can learn from these big data start-ups

As these companies demonstrate, big data can equal big money. In fact, the big data, analytics, and sales market was worth $125 billion in 2015 and is expected to reach $189 billion by 2019. The best news is that there’s no shortage of demand for big data start-ups.In fact there will always be space for the team that can be innovative and agile.

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