QUICK FACTS

HEAD OFFICE

53 Frith Street
London W1D 4SN
United Kingdom

COUNTRIES SUPPORTED

United Kingdom

category

CATEGORIES

Big Data

INDUSTRIES

Market research, Media and entertainment, Retail

PRICING

Subscription

An initial setup fee and then monthly ongoing subscription depending on the amount of data moved.

SIZE OF CUSTOMERS

Large, Small, Medium

 
Founders:
 
Year founded:February, 2011
Funding received: Self-funded
Investors:
 
#Employees:17 employees
Awards won:Phil Harvey & Richard Edwards
 

Overview

DataShaka is an English Big Data startup that addresses the variety problem of Big Data. This means that they can deal with a vast array of different sources, formats, locations and types of data. Bringing it all together in one platform. Ranging from log data, customer data, sales data or external data and combining and unifying it via their DataShaka Unification Platform. They can visualize the insights from all that data through their visualisation tool SmartView.

Their objective is to enable customers to combine data, no matter the source or format, and to provide them with valuable insights to make better decisions. DataShaka tries to make Big Data simple for organisations, removing as much as complexity as possible. Through their unified data platform, they provide customers with a unified view on disparate data sources to find new insights.

It’s a classic SaaS approach, incorporating an initial setup fee and then monthly on-going subscription depending on the amount of data moved. It can be operated independently, or users can plug it in to existing infrastructure.

DataShaka was founded in February 2011 by Phil Harvey, a developer with a background in Artificial Intelligence, and Richard Edwards, a serial entrepreneur. Currently they are still self-funded. They have a patent pending for their core data fabric TCSV and were awarded Best Data Startup at Strata London 2013.

The DataShaka Unification platform unifies data from any source and any format, which is then cleaned, enriched and tested before the data is delivered it into a client’s

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