We all know projects are extremely complex system that are influenced by extremely large number of factors. Often project failure can be due to hidden causes that can sneak up on project managers. Data holds the key to preventing this, as it allows us to peer into the past and better understand our mistakes.
In many projects, one of the main major issues holding us back is that we lack the quantity of useful data needed to perform in depth project data analytics and the data we do have is limited in scope. Currently, project managers mainly pull from 1st party datasets (Datasets with a direct relationship with the problem), which does provide some insight. However, do many people know of the true power of 3rd party data?
What is Third Party Data?
Third party data is data that sits outside the organisation. Often the data has no direct relationship with problem at hand. A good example would be when a project manager wants to know why there are delays in the a construction project, they may use weather data to provide deeper insight into the condition on site. In doing this project managers can have a holistic view of the project.
Project professionals may find this is interesting, however are there any real world examples of third party data being used? Well the winners of Project:Hack 8 (Challenge 5a) displayed the power of third party by solving this problem. Here cost managers need to understand price trends in key raw construction materials, in order to know when is best to buy them. So the team took data on construction material from the Office of National Statistics and third party data from the London stock exchange, to provide insight into the price of these raw materials. This allows cost managers to make more informed decision, when buying these materials and also it allows data scientists to better machine learning models that make more accurate predictions.
AWS Data Exchange
In the previous example, code had to be developed and deployed to allow for the extraction and integration of the third party data. This process is time consuming and costly.
AWS Data Exchange saves on these cost greatly, as this service provides pre-built data pipelines connecting data subscribers (consumers of data) and providers (producers of data). The service acts as a place where data subscribers can gain easy access to third party data. Meanwhile, for data providers it acts as a market place, where they can sell their data on. This enable through the AWS Data Exchange API.
Project professionals and project data analysts will have access to data from all across the world and across industries. The marketplace offers useful data sets including data on COVID-19 to data from the public sector. These new data source can help expand the scope of project data analytics and thereby allow management to make more informed decisions.
How does this all work? Once sourced, this data can be then stored in Amazon Simple Storage Service (Amazon S3), which is a scalable storage service. This data can be further analysed with AWS analytics and Machine Learning services to provide important insights. So when looking to advance your analytics, think about third party data sets and how they can enrich your data.