Analytics

With all of the data that is collected we need to make sense of it all and this is where analytics comes in.

To make sense of just a relatively small dataset example 6 columns and 100 rows of data in a sheet or .csv file we would need to look closer at each of the keys and values and that is not easy so therefore we would add a graph that show an aggregation of the data which turns the data into a digestible easy to understand format.

Where is the data

Now imagine that you have 100 columns and 10.000 rows of data then it becomes almost impossible to comprehend without any kind of aggregation or graph.

Collected and stored data is typical in many different database tables or from multiple places which then add a new complexity to getting an overview.

Who will use it

Analytics is used in many different departments within a company HR, finance, business development, research and development, executive level, and others. They use this on many different levels from getting a fast and curated picture of how the business is, product manager that sees how users are interacting with a product or feature, and the developers that want to discover the very specific details of a feature to act on what the next steps should be.

For many businesses it’s crucial to be data driven throughout all of its departments. We need to remember that although all of the data collected we need the expert person in its field to validate and curerate data. Data is a supplement to the ongoing development of a product or feature and should be mixed together with the experts, customer gathered insights, social media sentimental collected data, and the business strategy.