Data Language is a highly successful technical consultancy that specialises in using data science, knowledge graph and AI digital transformation solutions to solve business-critical challenges. We produce software that creates opportunities and solves problems in the most intelligent way possible.
We have unparalleled expertise in data platform engineering, and machine learning technologies. Our range of off-the-shelf software platforms have been developed to help organisations optimise their core business processes 鈥� using all types of data and media 鈥� to increase efficiency and to support innovation.
In addition, we work with businesses across multiple industries to develop bespoke solutions encompassing sophisticated data infrastructure and frontend interfaces that enable its customers to rapidly innovate.
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How did the company start?
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Data Language was founded in 2014 by my colleagues Julian Everett, Paul Wilton and Silver Oliver. We worked together at the BBC, where they delivered the first large-scale knowledge graph project in UK digital publishing, moving BBC Sport from a classic content-led approach to a data-led product that could support rapid and continuous innovation. I went on to roll this approach across BBC News, and joined Data Language later, in 2017.
We recognised the need for this market-leading expertise in the wider industry and since 2014, Data Language has grown, taking this pragmatic knowledge graph paradigm across sectors, helping organisations in their data-led digital transformations. Digital publishing was the first sector to adopt large scale knowledge graphs to connect and contextualise core business information, and now we are seeing the need across all sectors and all enterprises. We have since launched a product suite that includes data, AI and video tools to support data-led digital transformation.
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听Why is digital transformation important?
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Digital transformation improves the efficiency of a business鈥檚 processes, consistency, and quality. It provides a valuable opportunity for core business functions to move away from manual processes and become automated, enabling leaders to focus on wider business opportunities. Integrating conventional records into a digitised system removes redundancies and provides new revenue and value-producing opportunities, maximising your chances of success in the marketplace.
By placing portable data at the front of a digital transformation strategy, information silos, which hinder cross-organisational collaboration and innovation, can be avoided. These silos 鈥� effectively 鈥渄ata disconnections鈥� 鈥� make it incredibly challenging to rapidly adapt to changing market conditions. By implementing a structured data and technology backbone as part of their digital transformation project, organisations can better manage their knowledge assets.
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How should businesses approach their digital transformation strategy?听
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The first step for all digital transformation initiatives is to establish a shared and living 鈥榤ap鈥� of your organisation鈥檚 core information, data and related pain points. Rather than reinventing the wheel, businesses should identify their strengths and differentiators and where their expertise lies, as this is where you stand the best chance of success. Then they can zero in on how technology can support in delivering these, rather than getting caught up in technology hype and fads.
Involve your employees in this, spend some time and tease the information out. The value locked in their heads is a large part of your core business advantage. This can then inform new project initiatives, and it ensures that employees and partners always have a good view of how your organisation鈥檚 data is connected and what it means. Having this shared understanding also provides a pattern to follow when implementing new digital services.
