Your client has a large dataset that they would like to integrate into an application or website. However, their data is difficult to access, in a strange or non-standard format and the client is not sure how to display the data in a compelling fashion. You’re unsure the best way to get the data, how to store it and how make it available and eventually present it. How do you decide on the best way to do all of this?
In this session we will discuss the who, what, where, when and how of leveraging Drupal as a datastore for large datasets and and walk through three unique case studies each with different data sources, integration methods and front-end presentation.
We will cover:
- Who: Understanding your client and their target audience.
- What: Identifying what the client or target audience ultimately needs to do with this data. Examples of how data can be presented.
- Where: Where is the data coming from? Where does it need to go? Dealing with problematic or poor source data.
- When: Consider the data’s life cycle. How often does it need to be accessed or updated?
- How: Examples of multiple integration methods and how to choose the best approach for your needs.
From this session you will be able to determine which approach is best suited for your use case from information on best practices, pros and cons of implementation options, challenges, wins and lessons learned.