数据分析师应该确保为结果创建一致且标准的注释。
Data analysts should ensure that consistent and standard annotations are created for results.
数据分析师也是这样。
如果没有软件，网络规划设计师和数据分析师又有什么用？
What would all that planning and design by network and data analysts be worth without software?
各机构代理举办CDA数据分析师培训课程。
识别出数据质量标准之后，数据分析师就必须设计执行计划。
From the data quality criteria identified, the data analyst must now design the data execution plan.
数据分析师应该参与这个过程，确保其中包含高水平的数据质量需求。
The data analyst should participate in this process to ensure high-level data quality requirements are included.
这样一来，数据分析师(又称数据达人)就不会成为完成任务的瓶颈了。
Then analysts [a. k. a. data crunchers] aren't a bottleneck to getting things done.
在这样的情况下，数据分析师必须从现有的测试数据或生产数据生成有代表性的数据样本。
In such cases, the data analyst must build representative data samples from existing test data or sample the production data.
他越过同事，职位由原先的数据分析师被提升为高级市场专员，薪水也增加了50%。
He'd catapulted from account executive to his new position as a senior marketing specialist, bypassing colleagues and collecting a 50% raise.
在执行计划中，数据分析师必须确定运行测试所用的数据集，还要确定谁对这些数据集有访问权。
The data analyst must, as part of the execution plan, determine against which data sets the investigation tests can be run and who has access to those data sets.
数据分析师要与业务领域专家和应用程序专家协作，评估哪些数据元素对于数据质量分析比较有意义。
The data analyst works with business domain experts and application experts to assess which elements are more meaningful than others in order to identify how data quality will be analyzed.
来自数据可视化公司Tableau的数据分析师Ross Perez可以让你一目了然。
Ross Perez is a data Analyst at data visualization company Tableau.
过去六个月时间里，我与一个由记者、数据分析师和权威调查人士等构成的小组合作，共同出炉了这份排名报告。
For the past six months, I worked with a team of reporters, data analysts and survey gurus to pull this report together.
进而“人力计算机”这一工作逐渐消失而被诸如数据分析师，程序员，管理人员，和IT员工所取代。
Analysts, programmers, managers, and IT staff have replaced the human "computers" of days gone by.
实际上，如果数据分析师们有好好干活，那么将数据转化成信息才是重点，而不是只生成看上去很简洁的图标或语焉不详的统计资料。
In fact, if data analytics does its job, converting data to information will remain its focus, rather than generating neat looking graphs and obscure statistics.
实际上，如果数据分析师们有好好干活，那么将数据转化成信息才是重点，而不是只生成看上去很简洁的图标或语焉不详的统计资料。
In fact, if data analytics does its job, converting data to information will remain its focus, rather than generating neat looking graphs and obscure statistics.
应用推荐