Helping businesses leverage data platforms, data science and data engineering to drive value from the data they generate.
Business transformation with data
Data is at the heart of all business, increasingly relying on an ever-growing number of data sources to drive and automate business, the reliability of how data is gathered and integrated often leaves data estates in a mix of new and legacy that interact in an architecture that has developed organically over time, without being engineered to operate reliably at scale.
We have put DataOps at the core of what our data team does. Our experience is helping organisations leverage their data by raising the DataOps culture.
This means that data is truly managed as an asset, that data is registered, catalogued and data flow is monitored and controlled. Exceptions are raised and managed as the impact of bad data and unreliable data management can have balance sheet impacting consequences.
The business of business is data, it is a strategic advantage when leveraged. DataOps is the glue that makes the whole data management work, from collection, to analytics and artificial intelligence. Putting DataOps at the centre of your data strategy is how you profit from your data.
Read our latest report AI: Hype vs Reality which aims to demystify the hype surrounding scaling AI in the Enterprise.
Data Strategy and Architecture
Transformation of business models and delighting customers are top business imperatives. Constructing compelling data strategies and designing the supporting architectures needed to transform organisations using data is hard. Working closely with your business leaders we first understand your organisational goals, and then set out for you the enterprise data collection and exploitation strategies that will move the needle. Our data strategists, engineers and data science experts keep this process grounded in reality – offering expert advice through this process to identify quick wins and to avoid projects that are technically risky with little or no return.
Machine and Deep Learning
Predicting an outcome is no longer science fiction, its data science. Putting machine and deep learning into business as usual has become the cornerstone of building the modern intelligent enterprise. Our data science and engineering team bring a wealth of experience and practical know how, and can help you deliver solutions across prediction, forecasting, optimisation and geospatial projects. We provide a full range of skills from hypothesis generation, experimental design through to feature engineering, model training and automated deployment.
Analytics and Visualisation
Bringing your data to life with compelling visualisation making the complex simple, intuitive and driving action is critical today. Applying analytical techniques to get under the hood of the business problem and tell a comprehensive story based on facts not opinions enables trust. Our analytics and visualisation team are expert data storytellers and know how to drive value from data.
Knowledge Graphs and Graph Analytics
The ability to gather data to create a considered view of the enterprise information landscape becomes more complex as additional data is sourced and generated. Our knowledge graph experts work to develop ontological models of the enterprise, and select the right graph database to solve the business need. We then produce scalable, accurate and rich knowledge graphs that uncover insights never previously found.
The cloud represents the opportunity to truly leverage data at scale. We help our clients navigate the complexity of cloud options, weighing up the benefits and then help deliver the platform on which they can execute their data workloads taking advantage of streaming and batch data. In addition, we securely transform from existing data platforms on premise and deliver the best of both worlds to ensure investments are maximised. Our data engineering and dataops teams rapidly provision data platforms, start the data flowing and industrialise the solutions.
The investments made in databases are the foundation on which business is built and have become critical to business success. However, these investments degrade over time and represent a significant operational risk if they are not maintained and modernised. We accept that not all databases need migrating to modern technologies, migrating to newer versions while maintaining compatibility extends the life of the solutions and maximises value. Our experienced database administrators have years of experience migrating from complex legacy environments onto the latest versions and cloud based equivalents.
To realise the benefits of data led transformation, you must embed your successful data programmes into your production systems in a way that allows you to consistently deliver value over time. Data reliability is increasing in importance as businesses are now totally dependant on the flow of data, knowledge and predictions. The reliability challenge is hard, as it requires you to manage the feeds and flows of data that generate value, even as the quality of the data drifts over time. Our DataOps experts help you automate, instrument, and report on the health of your production data pipelines as they run day in and day out, and can provide you with tools and techniques needed to manage change effectively, whether it arises through data quality exceptions, or through planned upgrades to your system landscape.
Insights from our experts
October 23, 2019
Accelerate Data Science: Why a Graph should be at the heart of your Data Platform
A majority of Data Science takes data about previous customer interactions and uses it to interrogate the current state, predict future activity and confirm hypotheses on changes to implement.
September 25, 2019
Artificial Intelligence: Hype vs Reality Recap
On 11th September we unveiled our Artificial Intelligence: Hype vs Reality report. The event, took a deep dive into the findings of the report and the learnings that can be applied across enterprise when it comes to scaling AI adoption. For those who were unable to join us, here is a quick recap and we hope to see you at future events.
September 11, 2019
Artificial Intelligence: Hype vs Reality
In partnership with YouGov, we commissioned a short survey of over 1,000 senior decision makers, including owners, partners, chairpersons and non-executive directors, working across the public and private sectors. The focus of the study is to lift the veil on boards’ attitudes towards Artificial Intelligence and understand the reality of adoption and awareness at executive level.
May 23, 2019
Scaling AI in the Enterprise Recap
Thanks to those who were able to join us last week for our first AI event with InstaDeep. This, the first of four events, looked at Scaling AI in the Enterprise and helping business leaders to realise the potential of introducing and scaling AI in their businesses. For those who were unable to join us, here is a quick recap and we hope to see you at future events.
May 21, 2019
Busting data lake myths so you can get the most value from yours
Having a data lake reaffirms an organisation’s need to invest more effort in data governance and data quality, helping you to understand the content that resides within it. However, both in our experience, and as revealed by Gartner in their report on data lake failure, if data lakes are misunderstood in the context of a wider data strategy, this can lead many initiatives to flounder.
April 1, 2019
Kickstarting your ModelOps journey
It’s vital to ensure that your AI is kept fit and effective. The first step in doing so is understanding the need to consistently curate your AI models. To do this, you need an effective ModelOps team. AI is evolving quickly and businesses need to ensure that their teams evolve to deliver against business and regulatory needs, whilst empowering their people too.