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Finding Value in IoT Data

When companies leave their Internet of Things data untouched, the result is an underperforming asset.
By Tomer Shiran

Data-as-a-Service
Enter data-as-a-service (DaaS). Data-as-a-service platforms address key needs in terms of simplifying access, accelerating analytical processing, securing and masking data, curating datasets, and providing a unified catalog of data across all sources. Rather than moving data into a single repository, DaaS platforms access the data where it is managed, and perform any necessary transformations and integrations of data dynamically.

In addition, DaaS platforms provide a self-service model that enables data consumers to explore, organize, describe and analyze data regardless of its location, size or structure, using their favorite tools such as Tableau, Python, and R. Some data sources may not be optimized for analytical processing and unable to provide efficient access to the information. DaaS platforms provide the ability to optimize the physical access to data that is independent of the schema used to organize and facilitate access.

With this ability, individual datasets can be optimized without changing the way in which data consumers access the data, and without changing the tools they use. These changes can be made over time to address the evolving needs of data consumers. DaaS allows users to tackle this challenge by providing a platform by which business users can easily discover, curate and share data from any source, then analyze with their favorite tools, all without being dependent on IT.

Based on Open Source
In data analytics, the future is open source. Infrastructure based on open source delivers a number of benefits to enterprises, including faster development cycles (building on the work of the community of open-source contributors), more secure and thoroughly reviewed code, and no vendor lock-in.

For example, data infrastructure built on Apache Arrow allows enterprises to leverage the benefits of columnar data structures with in-memory computing, providing dramatic advantages in terms of speed and efficiency. Open source DaaS platforms, such as Dremio, are built on Arrow, as well as number of other open-source projects, which results in extremely robust performance.

Tomer Shiran is the co-founder and CEO of Dremio. Previously he was the VP of product at MapR, where he was responsible for product strategy, roadmaps and new feature development. As a member of the executive team, he helped grow the company from five employees to more than 300 employees and 1,000 enterprise customers. Prior to working at MapR, Tomer held numerous product-management and engineering positions at Microsoft and IBM Research. He holds an MS degree in electrical and computer engineering from Carnegie Mellon University and a BS degree in computer science from Technion—Israel Institute of Technology. Tomer is also the author of five U.S. patents. You can contact him on LinkedIn, at Twitter or via email.

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