Approachable Analytics: What it is, How to Achieve it and Why You Want to
Approachable Analytics is a hot industry topic, but we see the term confusing people. We want to remove the waffle so it can be understood what it is, how it benefits you and how to achieve it.
In our recent blog, “Modernise Your Analytics to Maximise Returns”, Approachability was identified as one of the key aspects of moving forward your analytical capabilities. Through Amadeus’ services, we aim to make analytics easier and quicker to deliver, through simplifying the process.
Approachable Analytics means you, the analyst, have all the functionality and capability at your fingertips in a single software application. Let's say you have been asked to look some data provided by an ad-hoc system or third party. What are the stages?
- Importing the data
- Organising the data into data sets with suitable structure
- Explore, analyse, visualise and often export results.
Approachability, also known as self-service analytics, is about being able to complete all those tasks without the need to involve other departments, functions or software applications.
SAS of course achieves this breadth of tasks in a single application, increasing customers’ opportunities to innovate their analytics and recognise a competitive advantage. We are seeing businesses encourage data preparation in the database and SAS use being focused on analysis, visualisation and innovation. However, part of innovation comes from being able to take raw data and restructure, derive, explore and investigate patterns and relationships. Whatever the opinions and rhetoric of vendors regarding data lakes and data warehouses they are not the best for innovating with analytics. They are the best tools to store vast volumes of constantly changing data. Delivering the value from that data is best suited to the analytics of SAS. That means providing a level of freedom to take raw data and work with it, whilst operating in a secure, well-governed and audited platform. Once reusable insight or processes are created, if the process can be derived by the database, then those data derivation steps should be re-engineered as part of the data loads, which often belong in the database.
As the analyst using SAS, you have the flexibility to structure and prepare data, visualisation capabilities, statistical and predictive methods readily available in a single, unified software product. That's why Amadeus provides Consultancy and Managed Services for the SAS platform - and only the SAS platform.
To engage Amadeus to render your organisation’s analytics more approachable and further optimise in-house efficiency, contact us today. Remember to share your thoughts and experiences on this topic with us using the hashtag #BeCanDo.