Most of us know that without high quality data we can be left making assumptions that results in bad research, bad decisions, and worse health outcomes. But knowing that we need quality data isn’t enough if we also don’t know what quality looks like.
It can be tough to define quality in a succinct way because the metrics for success are so dependent on who is using the data and what they’re using it for. Because of this, our team works tirelessly to iterate and improve on a number of different dimensions of quality so that we can deliver a wellrounded product.
We’ve put together a thoughtfully organized series on data quality to help you critically examine data and proceed with confidence. Through this part one of our eBook you’ll gain an insight into our philosophy on quality data, explore three of our five dimensions of quality, and walk away with a clear understanding of how to evaluate and improve your own data’s quality.
We’re relentless in our pursuit of high-quality data because we know that good research and confident decisions can’t be done without it.
- Understand how we define and deliver quality data
- Learn what to look for when evaluating data
- Identify ways to improve your data quality
- Explore tangible examples from our knowledgebase