上QQ阅读APP看书，第一时间看更新

Performance

You can bet that pretty much everyone is, or will be, concerned with the topic of performance. Some forms (of performance) are perhaps a bit more quantifiable, such as what is an acceptable response time for an ad hoc query or extract to complete? Or perhaps what are the total number of mouse-clicks or keystrokes required to enter a sales order? Others may be a bit more difficult to answer or address, such as why does it appear that there is a downward trend in the number of repeat customers?

It is the responsibility of the data developer to create and support data designs (even be involved with infrastructure configuration options) that consistently produce swift response times and are easy to understand and use.

One area of performance responsibility that may be confusing is in the area of website performance. For example, if an organization's website is underperforming, is it because certain pages are slow to load or uninteresting and/or irrelevant to the targeted audience or customer? In this example, both a data developer and a data scientist may be directed to address the problem.

These individuals—data developers—would not play a part in survey projects. The data scientist, on the other hand, will not be included in day-to-day transactional (or similar) performance concerns but would be the key responsible person to work with the organization's stakeholders by defining and leading a statistical project in an effort to answer a question such as the one concerning repeat-customer counts.