Innovation
DigitalFirst is at the forefront of digital innovation, providing leading-edge solutions to enhance customer experiences and unlock new commercial opportunities. We specialise in integrating disruptive technologies and strategies that drive significant efficiency improvements. This enables DigitalFirst to offer a holistic approach to digital transformation, aiming to revolutionise the way organisations interact with technology and data in the digital age.
Customer Platforms
Digital First has worked with clients through the design, specification & procurement and delivery of a range of customer platforms. This includes:
Web, CMS and Authentication
Data Platforms
Digital First provides cutting-edge data services to enable organisations unlock their valuable data assets
Raw Data
We work with you to identify all data sources within an organisation; both those that are clear and obvious, and those that are not. We can work with all types of data from a wide range of modern and legacy application sources.
Data Management
When we have identified and audited your raw data sources, we extract, wrangle and match your data. This will give a single view of your customer data on a new data platform specifically built for this purpose.
Customer Insight
Once the data has been cleaned, the team applies a wide range of analytics and tools to deliver valuable insight. This includes our own in-house developed tools, and a variety of open source machine learning and artificial intelligence services and packages.
Insight Deployment
We use a range of tools to deliver this analysis and insight to our clients and their staff, so that the new data capability can be used across the organisation to deliver benefit. Our clients’ staff receive full training on these packages, we often deploy Tableau, PowerBI or the QlikView products for this purpose; we can also use any existing tools already used by our clients.
How we unlock the value of your data
We work with our clients through a series of stages, from discovery and strategy through to data platform build and delivery of clear results. At each stage the Aelign team of data scientists, engineers and consultants work closely with your teams to ensure ownership and learning for your staff. Each of the four stages to our approach have been carefully designed and refined with our clients to deliver the maximum benefit. All activities are flexed to suit the precise needs of each individual client.
1) Discover
Our first stage enables the Digital First team to get to know your organisation and your data environment and systems. We ensure from the start that all data analytics work will be firmly grounded in the delivery of organisational value and benefit. This stage identifies the precise performance indicators and areas that will be impacted, and delivers a data and information strategy for your organisation.
2) Develop
When we have defined the strategy and objectives, the second stage is the build of the data platform. This can be done on our AWS infrastructure, or within an existing client-environment of your choice. We use our open source tools and algorithms to deliver the analytics and insight required. The presentation, reporting and dashboard tools that we use are entirely the choice of our clients, we have used PowerBI, QlikView and QlikSense, Tableau, Sisense and Ploty.
3) Operationalise
Our second stage is to work with you to ensure that the new data analytics approaches and tools are embedded within all levels of your organisation. During this stage we give your staff access to the new tools and train them on how to get the maximum value and benefits from them. This enables your staff to put the new analysis in to action and begin applying the data insights within their operational roles.
4) Results
Our fourth stage is to work with you to make sure that when staff use the new data platform, the impact on key areas is continually measured. By doing this we can ensure that the objectives identified are delivered. When we continually review and measure, we will identify where and how the data analysis needs to be updated and refined to meet emerging needs and requirements.
