1. Google

Unsurprisingly, Google stands at the top of this list with their widely ambitious plans to integrate, innovate and expand more than ever before.

Competing with companies like Apple and Microsoft, Google is attempting to join other services and use the data they collect and manage to their advantage. Only time will tell if any of these projects stick around or fade away, but one thing is for certain, the odds are in Google’s favour.

That being said, the company has been under intense scrutiny since 2013, and this scrutiny has amplified since the Cambridge Analytica scandal and people’s revived urgency to protect the data. Google has to think its way around being “invasive” and optimising their services through the data they acquire from their users.

2. CenturyLink

Having announced their new BDaaS option for companies without the resources but the desire to acquire the power of big data, CenturyLink has been making the rounds as a reliable big data company.

CenturyLink offers Data-to-Decisions workshops, a team of experts constantly ensuring efficiency with each customer’s unique business and a guarantee of high-level operating.

CenturyLink was actually founded in 1930, having always known and anticipated the direction of technology to lead to big data. The firm has worked with companies such as AT&T and Verizon previously, having moved from telecommunications to further providing data services to residential, business, governmental and wholesale customers.

3. MapD Technologies

A company that calls itself the “extreme analytics platform”, MapD Technologies’ purpose is to use SQL to return query results hundreds of times faster than CPU-based solutions.

Offering a range of solutions such as operational analytics, geospatial analytics, data science, big data research and custom applications, the company aims to make their limits the limits of their customers’ imaginations.

4. ShareThis

ShareThis is an all-in-one widget that gives people the opportunity to share any content on the web with their friends, which can be done through email, AIM or text message. Toolbar versions exist for FireFox, Mozilla Application Suite and Internet Explorer, giving the company a wide range of places to collect data from and understand what kind of content is prioritised or engaged with when shared.

The firm has special ties to the University of Illinois at Urbana-Champaign, as its founder, David E. Goldberg, is a professor there, thus owning an exclusive license with the university for Goldberg’s patent applications in the area of genetic algorithms and machine learning, all for the purposes of information discovery and learning from sharing behaviour.

5. Dataiku

This computer software company based in New York City develops collaborative data science software for big data. The company was founded in Paris five years ago, its 4 co-founders, Florian Douetteau, Clément Stenac, Marc Batty and Thomas Cabrol, all had met while working at the search engine company Exalead.

During its first two years the company relied on its own capital, until they were found by Serena Capital and Alven Capital, able to raise $3.6 million from both of them by January 2015. Its free edition and enterprise versions with additional features give big data companies opportunity to understand perceptions of software in ways they never could before.

In 2017 they were made members of the Gartner Magic Quadrant for Data Science Platforms, being described as “visionary”.

6. Conductrics

Conductrics was born at an industry conference back in 2008. Seeing a window to create an optimisation-obsessed platform, they were able to find themselves of at the centre of several companies’ optimisation strategies, delivering decision-making to them at scale and reducing IT debts all around.

Using interpretable AI, Conductrics have recognised that machine learning and its vast range of benefits will not sell if the insights cannot be understood by the people who need them. This has meant applying audience decision trees, showing which audiences their ML algorithms have discovered as the most informative and why.

7. StreamSets

Their slogan is “Air Traffic Control for Your Data”. StreamSets believe in the philosophy of conquering what is referred to as a “dataflow chaos”. Dataflow chaos is the amalgamation of big data sources, multi-cloud architectures and real-time applications, generating dimensions of nuance and complexity that become harder and harder to keep up with.

The selling point of their company is the promise to each client that no chaos is unconquerable, that IT departments can be sold the tools to understand and dominate their own data whirlwinds and use them, in turn, for profit and growth in their company.

This is understand through three models: Data Sprawl, Data Drift and Data Urgency. The first refers to the well-structure model of transactional databases feeding a a data warehouse, and how this gives way to “data sprawl”. The second is a model of awareness, understanding how data changes and becomes more or less relevant through tools that help notify people better of these transformations within data. The third refers to the rise of immediate reactions to data. In the same way FedEx revolutionised their approach through same day delivery, data urgency is the push to find ways of using data within minutes or seconds of collecting it.

8. Looker

Looker is a company trying to provide data analytics for all. They are focused and devoted to not just selling their tools and services to the highest bidder, but to make data analytics the “new normal”, enhancing the customer experience with regard to every company or service they require or interact with.

Their guarantees are to deploy data analytics in days, not months, leverage data faster using today’s powerful databases, address unique problems with custom metrics and allow teams to find answers to their own questions.

What makes Looker so successful is that their model is built on constructing autonomy rather than dependency on them.

9. SQream

“Faster BI dashboards and Data Science models” is the promise and model of SQream. The company are popular for their 4 day “lift and shift” challenge, helping companies get from the ground up to begin their own data analytics process as independently as possible.

Company co-founder and CEO, Ami Gal, talked about his inspiration behind starting the big data company: “I’ve been working on high computing performance challenges for more than 20 years. CPU-based computing has always been limited, expensive and complex in scale. I’ve always been fascinated by the option of scaling with GPUs as they offer so many cores and parallel computing capabilities.

Before SQream, I tried to accomplish high-compute with GPUs a few times without succeeding. When the opportunity to establish a GPU database company came along, it was clear to me that I had to go for it, and turn years of brainstorming into actions and reality.”

10. Reltio

Reltio offers a self-learning data platform that relieves you of huge tasks and challenges like organising data, recommending actions and measuring and improving along the way. Their MDM Summit happens to be today in London, so anyone interested should go see data come to life with Reltio.

Much like Salesforce, Reltio prides itself in covering all the bases, be it in mergers and acquisitions, compliance, cloud MDM, retail, media and entertainment, customer 360 or key account management.

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