Data Tips #15 – Three different angles in ideation
Today we are looking into Ideation and how to approach it. Throughout the years we have had many different hypes where new technology or new data has become available and has sparked a longing to utilize the new capabilities. In Data & Analytics ideation there are many different ways to approach the ideation, here we […]
Data Tips #14 – How to choose KPIs
In todays Data Tips we are diving into one of the really hard topics, mainly because there is no silver bullet. There are however a few very important points to keep in mind when choosing KPIs and there is a way of handling them that may support you in choosing and handling KPIs. Four important […]
Data Tips #13 – Data Mesh, what is it and why adopt it?
Data Mesh is a concept that was made famous by Zhamak Dehghani, I first came into contact with it from this article: Data monolith to mesh. She later went on to write a good book on the subject. The goal for data mesh is to address the complexities of handling large and diverse amounts of […]
Data Tips #12 – Managing Facts data
Today we will discuss the handling of Facts data. Facts as we have discussed before are business events. Sales, stock movement, orders, clicks, etc. We will use these facts in several ways including (but not limited to): As we can determine from the above scenarios there are very different requirements on the data when it […]
Data Tips #11 – Handling dimensional data
Today we are building on last weeks article that described what dimensional and facts data are and what the characteristics for each are. Today we are focusing on how to handle dimensional data. Dimensional data is descriptive. We use it to give context to the business event that has occurred. We describe the sales event […]
Data Tips #10 – Describing Dimensional data and Facts data
In todays article we will discuss two types of data that are central to analytics. In next weeks article we will discuss how to handle these types of data and why they should be handled in different manners. Stay tuned! Master data (also referred to as Dimensional data) is data that describes a certain information […]
Data Tips #09 – How to scale data & analytics delivery horisontally
The scenario we are working on today is the time when you have succeeded in the first use cases, gained traction in the business until finally a single team or even 2-3 teams in your data & analytics organisation is no longer enough. You need to scale up the organisation in order to handle the […]
Data Tips #08 – Data Models for consuming data
Today I am going back to a very basic but central topic. How do we present data to our analysts and scientists? The data may also in the next step be the basis for a dashboard or other deployed front-end. The underlying data model for any dashboard or analysis should have (at least) the following […]
Data Tips #07 – How to combine sustainable development with innovation
When delivering data & insights it is often tricky to combine predictable and robust development with innovation. First off, for this article let’s just define Sustainable development vs Innovation. One can always argue that there is Innovation in predictable development as well, but in this case we will separate the two in the manner below: […]
Data Tips #06 – Key factors for real self-service analytics
Self-service analytics was the holy grail for analytics a 10 years ago. Since then it has been a bit of a lost art or something taken for granted. At the same time it is vitally important for any datadriven company to make sure that it’s employees have the right information at the right time in […]