官术网_书友最值得收藏!

Quality questions

Suppose there are concerns about the quality of the data to be, or being, consumed by the organization. As we eluded to earlier in this chapter, there are different types of data quality concerns such as what we called mechanical issues as well as statistical issues (and there are others).

Current trending examples of the most common statistical quality concerns include duplicate entries and misspellings, misclassification and aggregation, and changing meanings.

If management is questioning the validity of the total sales listed on a daily report or perhaps doesn't trust it because the majority of your customers are not legally able to drive in the United States, the number of the organizations repeat customers are declining, you have a quality issue:

Quality is a concern to both the data developer and the data scientist. A data developer focuses more on timing and formatting (the mechanics of the data), while the data scientist is more interested in the data's statistical quality (with priority given to issues with the data that may potentially impact the reliability of a particular study).

主站蜘蛛池模板: 濉溪县| 永兴县| 亚东县| 桦川县| 华蓥市| 尚志市| 茶陵县| 江达县| 武强县| 汤阴县| 麟游县| 合川市| 古蔺县| 台安县| 云安县| 电白县| 连南| 塔城市| 清镇市| 富宁县| 昌图县| 黑河市| 新邵县| 西乌| 海兴县| 碌曲县| 登封市| 互助| 永丰县| 广昌县| 通许县| 宝丰县| 台安县| 平阴县| 育儿| 招远市| 泸溪县| 丰台区| 称多县| 手机| 辽阳县|