Data science, artificial intelligence and machine learning all buzzwords we are hearing more and more often. Their definitions have been bastardised by marketing departments the world over, however, due to the increase in the data available to organisations, the lower cost and higher availability of processing that data, and genuine advances in the field of artificial intelligence, there are great gains to be had for businesses of all sizes in investing in this area.
Rittman Mead's Insight Lab is a data science service that provides a lightweight starting point to gain insights and understanding of how your data can help you before embarking on a large scale data science project.
Introducing data science into your business will not only require an understanding of relevant tools, processes and technologies, but also an understanding of the underlying data, where it comes from and your business processes. For any analytics work, the first stumbling block is always obtaining, tidying and transforming the source data. With our experience in both data engineering and building machine learning models, we can offer an end-to-end advisory service.
We will advise which metrics and/or data would best impact your business, this is why our initial engagement is centred around understanding your business processes and available data.
One of our business analysts will evaluate your data and work with stakeholders to understand the business needs of your organization.
Next, our analysts define a question that relates to your business objectives and can be answered with the available data.
Our team of expert data engineers prepares, cleans and standardizes your data so it’s ready for statistical modeling.
We use state-of-the-art machine learning algorithms to predict future events, segment customers, suggest next best actions and more.
Finally, we deliver a production-ready model via an API for maximum compatibility with any data architecture. Our model APIs can be hosted on-premises or in the cloud.
Identify key factors that can be used to support process improvement and be better prepared to respond to unforeseen challenges.
Understand user context to deliver impactful interactions at the right moment.
Evaluate your customer base, recognize your best customers, and predict future customer behavior.
Let your data handle simple decisions and eliminate labor-intensive, repetitive, and error prone processes.