In the distant past, the professionals we refer to today as data scientists were primordial creatures who pieced together business intelligence from green and white striped dot-matrix outputs, deep in the basements of office buildings, to solve relatively esoteric actuarial problems.

Fast forward -today's data scientist or business analyst lives in a world of exponential data growth, sourced from all manner of sensors, computational devices, and repositories, and has the audience and ability to drive direct ROI on lines of business.

This new world, while dynamic and replete with potential, is not without its challenges. In our byzantine reality of on-prem, cloud, and hybrid deployments, operationalizing data requires the modern data scientist or analyst to navigate variances in data location, structure, technology, and access times.

What is the opportunity?

Cisco invests in cutting-edge technology companies to gain insight into new markets & offer our customers visibility into best-in-class tech innovations and go-to-market opportunities.

We focus on partnering with companies and teams that solve problems for the customers we work with on a daily basis. These types of problems are representative of the challenges faced by many practitioners in the market.

Within the data and analytics segment, the practical themes of data simplification, immediacy of access, and self-service seek to address common questions, such as:

"How do I unify my 'islands' of isolated data -e.g., unstructured / structured data, Hadoop data lakes, and data in the public cloud?"

"How do I access it quickly, in a relatively uniform representation, and funnel it into business intelligence?"

"How do I do all of this, without needing to call IT to set it all up?"

Why we like Dremio

Enter Dremio -an extremely exciting new company with serious open source software chops that takes a platform approach towards the data science fragmentation problem. They call their solution a Data-as-a-Service Platform.

Dremio offers a full-stack tool that simplifies the process of connecting, preparing, and querying data at accelerated speeds. They reduce the number of tools necessary to manage business intelligence and big data projects, enable broad collaboration between various data-centric stakeholders, and empower the data scientist and business analyst to accomplish this without the need to engage with IT. At the same time, Dremio allows companies to secure and govern data across different systems, which is critical given the breadth of systems it connects to, as well as the range of analytical use cases it supports.

Dremio is also synonymous with Apache Arrow, which provides the core data building block for heterogeneous data infrastructures and tools, including Spark, Python, R, BI, RDBMS, NoSQL, and file systems. Arrow is now the de-facto standard for in-memory analytics, with more than 150,000 downloads a month and adoption across a diverse range of projects.

The Company also recently launched The Gandiva Initiative for Apache Arrow, an execution kernel based on LLVM, which provides massive performance improvements for processing data in-memory.

How did we decide to invest?

At Cisco Investments, we take a multi-pronged approach towards identifying startups to partner with. Our first step is to develop a bottom up / holistic view of a specific domain (data and analytics, in this case). Our second step is to develop a forward-looking thesis about how the market will evolve, and where we could add value as investors (on the company's board, as a syndicate partner, and as a strategic partner). Our third step is to meet the best teams and companies, and ultimately make a decision.

In the case of Dremio, we benefited from having known Tomer Shiran from his days at MapR, and the company's other investors, from prior investments. Our team had spent a fair amount of time researching companies that offered solutions to the pain points of broader data management, and Apache Arrow, founded by Jacques Nadeau, came up repeatedly both in conversation in the market, and in regular conversations we have internally with our engineering teams at Cisco (as an aside -an incredible resource for our investment team, as we seek to identify emerging technology trends).

Dremio was in stealth mode when we first met with them, and the Dremio product was early but clearly promising. We were aligned with their vision for the product and company, had great chemistry with Tomer, Jacques and the rest of the team, and felt that we were well positioned to help the company with its growth plans.

They are well beyond stealth mode now -Dremio has added customers in more than 80 countries, spanning over a dozen industries from financial services and health care to retail and technology. Leading organizations including Daimler, Fred Hutch, Idio.ai, Intel, OVH, Royal Caribbean, TransUnion, and UBS employ the company's Data-as-a-Service platform to operationalize their data and unlock ROI from their stores of information.

They are a passionate group of entrepreneurs with an energy that's nothing short of contagious.

What does the future look like?

Our brave new, data-oriented world, is evolving at a dizzying pace. The need for a federated approach towards data management is paramount. We expect to see a continued need in the market for smart tools that will ultimately lead to the democratization of data science.

Cisco Investments supports the digital transformation of the enterprise, both of our own, and of our partners'. We have been committed to investing in leading data & analytics companies, such as MapR, Moogsoft, and Paxata, for years. Our investment in Dremio strengthens that commitment. The rapid adoption of Apache Arrow and Dremio in the short time since their product launch confirms market support for their forward-looking value proposition.

We are proud to be in the position to drive go-to-market partnerships between our customers and our portfolio companies and to broaden our startups' addressable market audience.

For data scientists and BI professionals -the era of reading dot-matrix outputs in basements is in the past, and the future is rosy.

About the Author: Noah Yago leads the development and execution of investment strategy for big data & analytics -covering technologies that compile, process, and produce insights from information. He offers close to two decades of experience building companies as a venture capitalist, entrepreneur, and board member and has led investments in Mesosphere, Cyber-Ark, Qlik Technologies, CyOptics, Getaround and many others.