Data Science - Distil8
Artificial Intelligence and Machine Learning
accelerating artificial intelligence adoption
Ready to take on the next industrial revolution?
Ready to dive into the future with AI and machine learning?
We are a team of industry recognised experts that love helping businesses to unleash the power of Artificial Intelligence (AI) and Machine Learning (ML) to provide high-value business insights. We have helped develop numerous solutions across many industries using the newest technology, ideas, and features.
With years of experience, we know that data is at the heart of what makes AI and machine learning work. Making sure your data is ML-ready is critical to the success of any machine learning solution.
What makes us unique is having the in-house capabilities of cutting-edge Data Engineers and Data Science experts that work collaboratively to deliver a full end-to-end machine learning solution to a business challenge.
We are production Data Scientists. Everything we build is designed to scale with your business. Unfortunately, eighty percent of machine learning projects fail, one of the biggest drivers of failure is inadequate production planning. Far too many machine learning projects are too academic and miss the critical impact on the business. We have developed a framework which puts the business case at the heart of any machine learning problem, everything else extends from there.
Data Science as a service
Data Science can be a challenging field, it is one which has numerous technical and academic complexities. These challenges are often overshadowed by the difficulties of establishing a Data Science capability. Advancing Analytics specialises in Machine Learning & Artificial Intelligence. We offer a flexible solution to meet your Data Science needs. Our Data-Science-as-a-Service, provides you with on-demand access to our highly skilled Data Science team.
3 Week Forecasting challenge
Getting started with our 3-week forecasting challenge could not be simpler. You supply the data, tell us about your unique data domain and we do the rest. We can host the challenge in your environment or in our own, whatever is easier for you. At the end of the 3-weeks you will have deeper insights into your data, a better understanding of how Machine Learning could improve your business and a model which is ready for production.
Machine Learning in Practice
We love to help our customers get started with data science and picking the right first problem is critical to ensuring adoption across the business.
Advancing Analytics have helped several customers to define their machine learning operating model. We focus on people, process, and technology - aligning the skills of the existing teams with the challenges they will face.
Get in touch to explore how we can accelerate adoption of data science.
How we help our customers
Case Study: Real-time hyper-personalisation & recommendation engine
In 2020, free-to-play games generated $87 billion dollars in revenue. When there are thousands of games to play, how do you choose the next best game? This is a problem our customer faced when rebuilding their mobile-gaming incentive application. Advancing Analytics developed and deployed an ensemble of models to understand the games a user is most likely to play then refine based on which they would most likely purchase - all served in less than 200ms.
Case Study: Equipment Demand Forecasting
A UK leading plant hire company approached Advancing Analytics to help them start their Data Science journey. After exploring several use cases, we focused on their key business driver - equipment. Predicting demand of each item in each depot, enabled our customer to make better decisions to optimise the utilisation of their equipment - saving money, optimising repairs and enabled them to make better purchasing decisions.
Get in touch
Advancing Analytics is a Data Engineering and Artificial Intelligence consultancy. We have a proven track record of helping some of the largest companies in the world gain a deeper understanding of their data. 4x Microsoft MVP, 4x Microsoft Gold Partner and Award winning Databricks Partner, Advancing Analytics was created by two Microsoft Most Valuable Professionals (Data Platform and Artificial Intelligence) to give our clients the deepest understanding of the technology roadmap!
We accelerate our clients’ understanding of their data by implementing scalable, future-proof data platforms and guiding them to design bespoke Artificial Intelligence models. This might be to predict an outcome, forecast a KPI, detect an anomaly or influence your customer journey.
We also focus on helping businesses understand what is required to start their AI journey and lay the foundations for success. Get in touch and find out how we can help you unlock hidden value with Advanced Analytics.
Read our Machine Learning research
Fabric wouldn’t be an end-to-end data analytics platform without data science, so in this blog we will explore that data science and machine learning capabilities of Microsoft Fabric and assess where the platform fits in the completive data science landscape.
Explore the world of AI with Azure OpenAI Service, offering secure access to cutting-edge language models like OpenAI GPT, Codex, and DALL-E within the Azure ecosystem. This article delves into the differences between OpenAI and Azure OpenAI, providing valuable insights to help you choose the ideal solution for your data protection and AI implementation needs.
Are you struggling to deploy your machine learning models in the cloud? With so many options available, it can be overwhelming to know where to start. In this blog, we'll explore how Azure's Managed Endpoints can simplify the deployment process and provide a user-friendly interface for deploying and managing machine learning models.
Struggling to choose a machine learning platform for building and deploying models? Check out our blog on 10 reasons why Azure Databricks for machine learning is a great choice.
We are thrilled to announce our partnership with Dataiku, the leading platform for data science and machine learning. Dataiku's Everyday AI platform offers powerful tools, intuitive capabilities and allows for collaboration between code-first data scientists and non-coding colleagues. The platform can also be integrated with Microsoft Azure and Databricks, driving innovation in the field of data science and ML. With Dataiku, we are able to offer our customers access to the latest in data science and ML tools, enabling advanced and sophisticated solutions to meet their business needs.
Knowing your customers inside out is key for any business. But getting a full understanding of what they want and need can be challenging. That's where machine learning (ML) comes in. By using ML-driven customer 360 views, you can get a better understanding of your customer's buying habits, preferences, and needs. This can then be used to make your marketing more personal, and improve the customer experience while increasing sales through cross-selling and upselling.
Learn how to use a classification model on a Kaggle dataset to drive quantifiable business value. This guide covers defining the business problem, cleaning the data, building and tuning the model, and more
Are you having trouble getting value out of your company's unstructured data? Optical character recognition (OCR) could be the answer. OCR technology allows businesses to turn unstructured documents and images into structured data, enabling them to make informed decisions. This technology can be used in various industries, including healthcare, finance, legal, and retail, to streamline processes and gain valuable insights. Discover how OCR can transform your business now.
Customer retention is important for the success of a business and can be improved through the use of machine learning models to predict churn. FLAML is a tool that can help businesses easily build these models. By retaining customers and preventing them from switching to competitors, businesses can increase revenue, save costs, and improve brand loyalty.
MLOps aims to resolve the challenges of getting machine learning models and processes into production for operational use and one of the major challenges is how to manage features, data pipelines and ensure consistency between training and production. This is what Feature Stores were designed to do. This blog will introduce you to the basics of Feature Stores and how they solve one of the largest impediments to machine learning success.
The future of data is AI. However, most companies still face a challenge when it comes to productionising machine learning models. Last week, at the AI and Data summit, Databricks unveiled MLFlow 2.0, a new feature coming soon that features MLflow Pipelines to accelerate the deployment of machine learning models.
Wondering how to create the best marketing strategy to reach out to different customer groups? Do you know which groups of customers are most likely to buy your product? Clustering your customers into segments based on profiles, behaviours and buying patterns is the answer. This article provides a great way to jump-start your clustering project using pre-built code designed by Databricks.
Do you know what the 10 most commonly useful clustering algorithms are? If you wondering what they are, then this article is for you.
This article uses an easy and simple example to explain what clustering is and how it is being used in business to solve problems.
Automated Machine Learning, or AutoML, has gained a lot of popularity. Recently, cloud providers have introduced the capability of AutoML for computer vision tasks. In this article, we explore the concept of AutoML for vision and see how computer vision is revolutionising many industries.
10 ways AI & Machine learning can be used to drive revenue in Insurance & Brokers.
Do you know exactly how many of your customers are leaving? Do you know why your customers are leaving? Are you able to predict which customers will leave the service? This article will show you how to predict churn using Azure Synapse Analytics and Azure Machine Learning.
Feature stores are rapidly gaining popularity in the machine learning environment. Find out what feature stores are all about and the benefits they offer when implemented in a machine learning pipeline.
Watch our examples
WATCH OUR DATA SCIENCE MOMENTS
Listen to our thought leadership
Data Science in Production. Episode 6: The Global AI Bootcamp with Henk Boelman.
Data Science in Production. Episode 5: Data Lakes for Data Science. Creating data lakes to enable better machine learning and data science. Listen to find out how to build the right data lake and not a data swamp"!
Data Science in Production. Episode 4: MLFlow & Databricks with Matei Zaharia
Data Science in Production. Episode 3: Version control for data science
Data Science in Production. Episode 2: Deploying Deep Learning models in to production
Welcome to the first episode of Data Science in Production. In this episode we look at some of the problems in data science and discuss the rise of the machine learning engineer.
This blog discusses an AI-driven system that uses large language models (LLMs) to empower employees by identifying skill gaps and creating personalized learning paths. The system acts as a personal career coach, providing tailored feedback and growth opportunities.