怎么样用BI工具对数据进行预处理?数据分析的这项技巧你必要把握!
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">在当今数字化时代,数据不仅是企业决策的<span style="color: black;">基本</span>,<span style="color: black;">亦</span>是创新和发展的关键推动力。在面对庞大而<span style="color: black;">繁杂</span>的数据集时,<span style="color: black;">怎样</span>进行<span style="color: black;">有效</span>的预处理<span style="color: black;">作为</span>了数据分析<span style="color: black;">行业</span>中至关重要的一步。</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><img src="https://p3-sign.toutiaoimg.com/tos-cn-i-axegupay5k/8dfa2dfa309143ec9ca1684ba452649d~noop.image?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1723340421&x-signature=V%2BOI4nw6kJj3QtCcTExkyq6eiyQ%3D" style="width: 50%; margin-bottom: 20px;"></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">在进行数据处理和分析的<span style="color: black;">平常</span>工作中,业务<span style="color: black;">广泛</span><span style="color: black;">运用</span>Excel和SQL这两个经典的工具。然而,<span style="color: black;">运用</span>这两个工具进行数据处理,在<span style="color: black;">实质</span>的过程中可能遇到的<span style="color: black;">有些</span>问题:</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">Excel:</p><strong style="color: blue;">限制于数据规模:</strong> Excel在处理大规模数据时可能会变得缓慢且占用<span style="color: black;">海量</span>内存,<span style="color: black;">引起</span>性能下降。这<span style="color: black;">针对</span>处理数百万行的数据集可能是一个挑战。<strong style="color: blue;">手动操作误差:</strong>Excel<span style="color: black;">一般</span><span style="color: black;">必须</span>手动进行数据清理和转换,这<span style="color: black;">增多</span>了人为出错的可能性。公式和数据操作的复制粘贴可能<span style="color: black;">引起</span>错误的结果,<span style="color: black;">尤其</span>是在<span style="color: black;">繁杂</span>的数据处理任务中。<strong style="color: blue;">版本<span style="color: black;">掌控</span>问题:</strong> 在团队协作中,<span style="color: black;">倘若</span>多个人<span style="color: black;">同期</span>编辑Excel文件,容易<span style="color: black;">引起</span>版本冲突,使得数据处理流程难以管理和跟踪。<strong style="color: blue;">有限的自动化能力:</strong> Excel的自动化功能相对有限,<span style="color: black;">尤其</span>是在处理大型、<span style="color: black;">繁杂</span>的数据集时,自动化处理和重复利用的能力相对较弱。<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">SQL:</p><strong style="color: blue;"><span style="color: black;">繁杂</span>的语法:</strong>SQL语法相对<span style="color: black;">繁杂</span>,<span style="color: black;">针对</span>初学者<span style="color: black;">来讲</span>,学习和理解SQL可能<span style="color: black;">必须</span><span style="color: black;">有些</span>时间。写<span style="color: black;">繁杂</span>的<span style="color: black;">查找</span>语句可能容易<span style="color: black;">显现</span>错误,而调试这些错误可能会耗费时间。<strong style="color: blue;">处理字符串操作相对繁琐:</strong> 在SQL中,对字符串的处理相对繁琐,尤其是<span style="color: black;">触及</span>到文本分割、合并和模糊匹配等操作时,可能<span style="color: black;">必须</span>编写<span style="color: black;">繁杂</span>的代码。<strong style="color: blue;">性能问题: </strong><span style="color: black;">针对</span>大规模数据集,<span style="color: black;">有些</span><span style="color: black;">查找</span>可能会<span style="color: black;">引起</span>性能问题,<span style="color: black;">必须</span>优化<span style="color: black;">查找</span>语句<span style="color: black;">或</span><span style="color: black;">运用</span>索引来提<span style="color: black;">有效</span>率。<strong style="color: blue;">难以处理非结构化数据:</strong> SQL更适用于关系型数据库,<span style="color: black;">针对</span>非结构化或半结构化数据的处理相对困难,<span style="color: black;">必须</span>在SQL外引入其他工具。<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">随着数据规模和<span style="color: black;">繁杂</span>性的<span style="color: black;">持续</span><span style="color: black;">增多</span>,以及对实时决策的需求日益迫切,业界<span style="color: black;">逐步</span>转向更为<span style="color: black;">有效</span>、灵活的BI(<span style="color: black;">商场</span>智能)工具。对比于Excel和SQL在处理大规模、<span style="color: black;">繁杂</span>数据时所面临的<span style="color: black;">许多</span>挑战,BI工具以其强大的自动化和直观性,为用户<span style="color: black;">供给</span>了更为<span style="color: black;">有效</span>和<span style="color: black;">方便</span>的数据处理<span style="color: black;">处理</span><span style="color: black;">方法</span>。在这篇<span style="color: black;">文案</span>中,<span style="color: black;">咱们</span>就将深入讲解<span style="color: black;">运用</span>BI工具进行数据预处理的关键技巧,<span style="color: black;">期盼</span>能为<span style="color: black;">已然</span>引入BI工具的企业员工<span style="color: black;">供给</span>数据分析的<span style="color: black;">帮忙</span>与思路!</p>
<h1 style="color: black; text-align: left; margin-bottom: 10px;"><span style="color: black;">第1</span>步:学会<span style="color: black;">怎样</span><span style="color: black;">调节</span>并简化数据结构</h1>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><strong style="color: blue;">1、<span style="color: black;">调节</span>数据结构</strong></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">在进行数据分析之前,<span style="color: black;">常常</span><span style="color: black;">必须</span>对数据结构进行特定的处理,以便更有效地进行后续分析工作。原始数据<span style="color: black;">一般</span>并非直接符合<span style="color: black;">咱们</span>分析的需求,<span style="color: black;">因此呢</span><span style="color: black;">必要</span>进行<span style="color: black;">有些</span>行列转换的操作,以便<span style="color: black;">调节</span>数据的格式和结构,使其适应分析的<span style="color: black;">需求</span>。</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">在FineBI里,<span style="color: black;">咱们</span><span style="color: black;">经过</span>数据编辑内封装的功能<strong style="color: blue;">“拆分行列”和“行列转换,</strong><span style="color: black;">快速</span>、灵活地实现对数据的<span style="color: black;">调节</span>和重组,从而达到快速<span style="color: black;">得到</span>所需分析结果的目的。<span style="color: black;">经过</span>“拆分行列”功能,<span style="color: black;">咱们</span>能够将原始数据<span style="color: black;">根据</span>指定的规则进行拆分,从而分离出所需的信息。而“行列转换”则<span style="color: black;">准许</span><span style="color: black;">咱们</span>在数据集中对行与列进行灵活的转换,以满足<span style="color: black;">区别</span>的分析需求。</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><strong style="color: blue;">原数据结构:字段内容混杂,<span style="color: black;">有害</span>于开展分析</strong></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><img src="https://p3-sign.toutiaoimg.com/tos-cn-i-6w9my0ksvp/d0df11b0d6ad426ea920987ac9da4113~noop.image?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1723340421&x-signature=W2ATeTyMjGMe6Av19jq4yFnNQyo%3D" style="width: 50%; margin-bottom: 20px;"></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><strong style="color: blue;">处理后数据结构:拆分行列并转换后,字段结构简单清晰</strong></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><img src="https://p3-sign.toutiaoimg.com/tos-cn-i-6w9my0ksvp/041963b1f65b49668dbaedabb6bd10e0~noop.image?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1723340421&x-signature=rQht7i2ASiVAFXfJe8kBAf%2BJoYI%3D" style="width: 50%; margin-bottom: 20px;"></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"> <span style="color: black;">示例中<span style="color: black;">说到</span>的数据分析模板分享给<span style="color: black;">大众</span>——</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">https://s.fanruan.com/x3k5k</span>零<span style="color: black;">基本</span>快速上手,还能<span style="color: black;">按照</span>需求进行个性化修改哦</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><strong style="color: blue;">2、处理重复行数据</strong></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">在<span style="color: black;">实质</span>的业务分析过程中,数据质量问题常常<span style="color: black;">作为</span>业务顺利进行分析的最<span style="color: black;">重点</span><span style="color: black;">阻碍</span>。其中,最为<span style="color: black;">平常</span>和棘手的问题之一<span style="color: black;">便是</span>重复行的存在。在处理这些重复行时,<span style="color: black;">咱们</span><span style="color: black;">一般</span>会面临两种<span style="color: black;">重点</span><span style="color: black;">状况</span>,每一种都<span style="color: black;">必须</span>特定的处理方式。</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">首要</span>,是那种删除任意一行都不会对分析结果产生实质性影响的<span style="color: black;">状况</span>,<span style="color: black;">例如</span>数据中存在类似“A、A、A”的重复行,而只需<span style="color: black;">保存</span>其中的一个“A”<span style="color: black;">就可</span>。针对这种<span style="color: black;">状况</span>,FineBI内封装了“删除重复行”功能,能够在业务分析中快速而<span style="color: black;">方便</span>地实现这一操作。<span style="color: black;">经过</span>这个功能,<span style="color: black;">咱们</span>能够<span style="color: black;">容易</span>地剔除冗余的数据,以<span style="color: black;">保证</span>数据集的干净整洁,有利于后续准确的业务分析。</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">其次,还存在另一种<span style="color: black;">状况</span>,即<span style="color: black;">必须</span>有<span style="color: black;">选取</span>地<span style="color: black;">保存</span>特定的一行数据。例如,在系统中同一个客户可能有两行<span style="color: black;">区别</span>的数据记录,而在进行分析时,<span style="color: black;">咱们</span>可能<span style="color: black;">必须</span>有针对性地<span style="color: black;">选取</span><span style="color: black;">保存</span>最新录入的一条数据。在这种“A、B、C”中只需取A的场景下,<span style="color: black;">咱们</span><span style="color: black;">首要</span><span style="color: black;">经过</span>对数据表进行排序,<span style="color: black;">保证</span>最新的数据<span style="color: black;">位置于</span>数据表的顶部,再利用“删除重复行”的<span style="color: black;">规律</span>,只<span style="color: black;">保存</span>最上方的一行数据,从而达到筛选并<span style="color: black;">保存</span>特定行的目的。这一流程既简洁又有效,为业务分析<span style="color: black;">供给</span>了灵活而可控的数据清洗手段。而表头下拉菜单对字段内容进行统计的功能,<span style="color: black;">亦</span>让<span style="color: black;">检测</span>重复行变得更加简单。</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><img src="https://p3-sign.toutiaoimg.com/tos-cn-i-6w9my0ksvp/4e8db5a291ff4dcb8e536d099c6a35df~noop.image?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1723340421&x-signature=EzQNDeblSlWZEl3qXgH3KD11qAI%3D" style="width: 50%; margin-bottom: 20px;"></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">功能封装,<span style="color: black;">选取</span>去重字段快速去重</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><img src="https://p3-sign.toutiaoimg.com/tos-cn-i-6w9my0ksvp/9e9e5b7667f0438fb661a240dc7c90e4~noop.image?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1723340421&x-signature=VbHdfLDiNieBbgUCHv6tb0G6pMc%3D" style="width: 50%; margin-bottom: 20px;"></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><strong style="color: blue;">3、对null值的处理</strong></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">在各种业务场景中,处理null值是一种不可避免的挑战,而<span style="color: black;">区别</span>的业务场景<span style="color: black;">常常</span><span style="color: black;">必须</span>采用截然<span style="color: black;">区别</span>的处理策略。</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">当面临大规模数据集时,<span style="color: black;">倘若</span>null值的<span style="color: black;">显现</span>相对较少,而这些空值并不会对总和或平均值等计算产生<span style="color: black;">明显</span>波动,<span style="color: black;">那样</span><span style="color: black;">咱们</span><span style="color: black;">一般</span><span style="color: black;">能够</span>直接忽略这些null值。这种处理方式在数据量庞大的<span style="color: black;">状况</span>下能够有效减少对计算结果的影响。</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">另一方面,<span style="color: black;">针对</span><span style="color: black;">哪些</span>在处理中<span style="color: black;">期盼</span>将null值视为脏数据,从而整行剔除的<span style="color: black;">状况</span>,<span style="color: black;">咱们</span><span style="color: black;">能够</span>借助表头的快捷过滤功能<span style="color: black;">快速</span>排除这些空值。这种<span style="color: black;">办法</span><span style="color: black;">经过</span><span style="color: black;">运用</span>表头的筛选工具,能够方便地将<span style="color: black;">包括</span>null值的整行数据剔除,从而<span style="color: black;">保证</span>数据的整洁性和准确性。</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><img src="https://p3-sign.toutiaoimg.com/tos-cn-i-6w9my0ksvp/8f8adaad4d4746d38ea34553ebc55a27~noop.image?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1723340421&x-signature=6NEhiOlbTY05PHEPZdv88rBGoF0%3D" style="width: 50%; margin-bottom: 20px;"></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">以上都是简单的场景处理,而在<span style="color: black;">实质</span>业务中,可能会遇到null值存在业务含义的<span style="color: black;">状况</span>。</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">例如示例中的数据,这位<span style="color: black;">朋友</span>英语成绩为空的<span style="color: black;">原由</span>可能是他本身就因病没参加考试,此时既<span style="color: black;">不可</span>放着不管,<span style="color: black;">亦</span><span style="color: black;">不可</span>直接删去他的这一行数据。</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">针对</span>这种<span style="color: black;">状况</span>,<span style="color: black;">咱们</span>要做的是针对某一类特殊<span style="color: black;">状况</span>打上对应的标签,以便在后续的分析中,有<span style="color: black;">选取</span>地过滤。在FineBI中,<span style="color: black;">能够</span>用<strong style="color: blue;">“新增公式列”</strong><span style="color: black;">或</span>更方便的<strong style="color: blue;">“<span style="color: black;">要求</span>标签列”</strong>来实现。</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><img src="https://p3-sign.toutiaoimg.com/tos-cn-i-6w9my0ksvp/cad3025bff204a6687bec41d466925d9~noop.image?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1723340421&x-signature=9KFUdUxZWTcsjKFWqJK1eQWt5QY%3D" style="width: 50%; margin-bottom: 20px;"></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">对存在空值成绩的<span style="color: black;">朋友</span>打上缺考标签</p>
<h1 style="color: black; text-align: left; margin-bottom: 10px;">第二步:学会<span style="color: black;">怎样</span>对多张表进行合并分析</h1>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">多表合并分析<span style="color: black;">指的是</span>在数据分析过程中,将来自多个<span style="color: black;">区别</span>数据表的信息合并在<span style="color: black;">一块</span>进行综合分析的<span style="color: black;">办法</span>。在<span style="color: black;">实质</span>业务或<span style="color: black;">科研</span>中,数据<span style="color: black;">一般</span>分布在多个表格中,而多表合并分析的目的是为了获取更全面、更综合的信息,从而得出更深刻的结论。</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">这个过程<span style="color: black;">一般</span><span style="color: black;">包含</span>以下几个<span style="color: black;">过程</span>:</p><strong style="color: blue;">数据连接(Joining):</strong> 多表合并分析的<span style="color: black;">第1</span>步是<span style="color: black;">经过</span>某种<span style="color: black;">相关</span>关系将多个表格中的数据连接起来。这<span style="color: black;">一般</span><span style="color: black;">必须</span><span style="color: black;">经过</span>共享的关键字段(例如,客户ID、<span style="color: black;">制品</span>编号等)来<span style="color: black;">创立</span>连接,以<span style="color: black;">保证</span>正确<span style="color: black;">相关</span><span style="color: black;">关联</span>数据。<strong style="color: blue;">数据合并(Merging): </strong>一旦连接<span style="color: black;">创立</span>,接下来的<span style="color: black;">过程</span>是将<span style="color: black;">关联</span>表格的数据合并成一个更大的数据集。这<span style="color: black;">能够</span><span style="color: black;">经过</span><span style="color: black;">区别</span>的合并<span style="color: black;">办法</span>实现,例如内连接、左连接、右连接或外连接,取决于分析者对数据的需求。<strong style="color: blue;">数据分析(Analysis): </strong>合并后的数据集<span style="color: black;">能够</span>用于更深入的分析,例如生成统计指标、<span style="color: black;">创立</span>模型、进行趋势分析等。<span style="color: black;">因为</span>数据来自多个源头,多表合并分析有助于<span style="color: black;">得到</span>更全局的视角,使得分析结果更加全面和有说服力。<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><strong style="color: blue;"><span style="color: black;">实质</span>业务中,<span style="color: black;">咱们</span>所<span style="color: black;">必须</span>的数据<span style="color: black;">常常</span>来自于多张表。在分析前,<span style="color: black;">另一</span>一个大<span style="color: black;">困难</span><span style="color: black;">便是</span>,<span style="color: black;">怎样</span>合并这些表。</strong><span style="color: black;">咱们</span>为刚上手BI的业务人员,归纳了以下两种合并的场景。</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">咱们</span><span style="color: black;">首要</span>想象合并后表的状态,一种是<strong style="color: blue;">表格上下扩展</strong>,分析的字段并<span style="color: black;">无</span><span style="color: black;">增多</span>,<span style="color: black;">然则</span>行数变多了。此时<span style="color: black;">能够</span><span style="color: black;">运用</span><strong style="color: blue;">“上下合并”</strong>快速完成表的拼接。</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><img src="https://p3-sign.toutiaoimg.com/tos-cn-i-6w9my0ksvp/13f2234feca74b969f29fe675864fa83~noop.image?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1723340421&x-signature=HCVQ922C3PQSndJ5PIzw%2FkVxxVU%3D" style="width: 50%; margin-bottom: 20px;"></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">表格上下扩展,分析的字段并<span style="color: black;">无</span><span style="color: black;">增多</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">另一种<span style="color: black;">繁杂</span>的<span style="color: black;">状况</span>是合并后的<strong style="color: blue;">表格是横向扩展</strong>的,即分析的字段变多了。</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">在讨论<span style="color: black;">上下</span>合并前,<span style="color: black;">咱们</span>不妨先<span style="color: black;">瞧瞧</span><strong style="color: blue;">“其他表添加列”</strong>。</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">亦</span>许你对这个名字摸不着头脑,<span style="color: black;">然则</span>肯定<strong style="color: blue;">不会对Excel的Vlookup、Sumif感到陌生</strong>。</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">没错,这个功能<span style="color: black;">能够</span>将其他表的指标字段进行聚合后合并(Sumif)或是<span style="color: black;">查找</span>对应的维度匹配到这张表中(Vlookup)。</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><img src="https://p3-sign.toutiaoimg.com/tos-cn-i-6w9my0ksvp/1a3dbeef7e104474ad3d5bf152f9366a~noop.image?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1723340421&x-signature=3k9qI6zPFy0eermeCEg5OhTF384%3D" style="width: 50%; margin-bottom: 20px;"></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">成绩<span style="color: black;">按照</span><span style="color: black;">需求</span>求和后<span style="color: black;">做为</span>一个新的字段,依据“姓名”合并到本表中</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">而对SQL老练的玩家<span style="color: black;">来讲</span>,left join、right join…..可能更加亲切,此时<span style="color: black;">能够</span><span style="color: black;">选取</span>BI数据编辑中的<strong style="color: blue;">“<span style="color: black;">上下</span>合并”</strong>功能,与SQL的<span style="color: black;">规律</span>一致,且比SQL的操作更加<span style="color: black;">方便</span>,并不<span style="color: black;">必须</span>代码来实现,有<span style="color: black;">基本</span>的<span style="color: black;">伴侣</span><span style="color: black;">能够</span><span style="color: black;">火速</span>上手。</p>
<h1 style="color: black; text-align: left; margin-bottom: 10px;">第三步:学会新增计算及分析指标</h1>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">在简化数据结构、并将多表进行合并处理后,<span style="color: black;">咱们</span><span style="color: black;">必须</span>停下来,审视一下自己所分析的问题,以及对应这个问题所<span style="color: black;">必须</span>的指标<span style="color: black;">是不是</span><span style="color: black;">已然</span>在表中了。</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">通常</span><span style="color: black;">来讲</span>,事情可能<span style="color: black;">无</span>这么顺利,当然这<span style="color: black;">亦</span>在常理之中,<span style="color: black;">例如</span>在零售行业的分析中,<span style="color: black;">常常</span><span style="color: black;">必须</span><span style="color: black;">咱们</span>自己计算毛利率、增长率等指标。</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">在<span style="color: black;">起始</span>分析前,<span style="color: black;">咱们</span><span style="color: black;">能够</span>将这些计算指标增添到数据表中。怎么做呢?</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">首要</span>是最令人<span style="color: black;">熟练</span>的<strong style="color: blue;">“新增公式列”</strong>,这个功能和Excel中写公式<span style="color: black;">同样</span>,只<span style="color: black;">必须</span>输入对应的公式就能产生对应的字段。接着是<span style="color: black;">有些</span>常用计算的封装功能,<strong style="color: blue;">“新增汇总列”</strong><span style="color: black;">能够</span><span style="color: black;">帮忙</span><span style="color: black;">咱们</span>进行简单的聚合计算。</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">选取</span>对应的分组以及计算方式,对指标进行计算</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">而<strong style="color: blue;">“<span style="color: black;">要求</span>标签列”</strong>这个功能则<span style="color: black;">处理</span>了众多分析师<span style="color: black;">平常</span>最头疼的<strong style="color: blue;">IF嵌套问题</strong>,不<span style="color: black;">必须</span>写嵌套了七八层的IF公式,只需<span style="color: black;">经过</span>鼠标配置<span style="color: black;">区别</span>的<span style="color: black;">要求</span>,就<span style="color: black;">能够</span>对数据赋予<span style="color: black;">区别</span>的标签(值)。</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><img src="https://p3-sign.toutiaoimg.com/tos-cn-i-6w9my0ksvp/dc1300230080472390d198bb1725cf43~noop.image?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1723340421&x-signature=%2BV9Wg2%2BmGoMYfdYYLdoIYVLfOuI%3D" style="width: 50%; margin-bottom: 20px;"></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">经过</span>添加特定<span style="color: black;">要求</span>筛选数据并赋予对应的标签</p>
<h1 style="color: black; text-align: left; margin-bottom: 10px;">第四步:学会对数据进行校验</h1>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">刚接触BI的<span style="color: black;">伴侣</span>遇到最大的问题不仅在于<span style="color: black;">不睬</span>解BI许多功能的计算<span style="color: black;">规律</span>,更在于由此产生的对数据处理结果的不信任。“我这么做,出来的结果是对的吗?”是新手<span style="color: black;">伴侣</span>最常问自己的一个问题。为了方便用户进行校验,数据编辑界面<span style="color: black;">亦</span>内置了<span style="color: black;">非常多</span>便利的功能。</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><strong style="color: blue;">1、表头数据校验</strong></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">选中字段后,<span style="color: black;">能够</span>在左下角快速<span style="color: black;">得到</span>平均值、总和、记录数等数据,<span style="color: black;">咱们</span><span style="color: black;">能够</span><span style="color: black;">经过</span>对<span style="color: black;">熟练</span>的数据进行校验,结合经验来判断<span style="color: black;">是不是</span>正确。</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><img src="https://p3-sign.toutiaoimg.com/tos-cn-i-6w9my0ksvp/0d8fb402ee174e21bbe4cbe123843b5b~noop.image?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1723340421&x-signature=npd%2Bj8wnAgn0WfdG%2BrPuF14svGM%3D" style="width: 50%; margin-bottom: 20px;"></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">数学成绩字段校验得出平均分85.92,符合班级历史平均水平</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><strong style="color: blue;">2、<span style="color: black;">过程</span>区关键<span style="color: black;">过程</span>取消应用</strong></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">BI<span style="color: black;">能够</span>在处理<span style="color: black;">过程</span>间<span style="color: black;">插进</span>新的<span style="color: black;">过程</span>,<span style="color: black;">同期</span><span style="color: black;">亦</span><span style="color: black;">能够</span>设置某些<span style="color: black;">过程</span>暂时取消生效。</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">利用这一点,<span style="color: black;">咱们</span><span style="color: black;">能够</span><span style="color: black;">经过</span>过滤出部分关键数据,并取消应用<span style="color: black;">有些</span>疑惑的关键<span style="color: black;">过程</span>来进行试错。就如同刚学数学时习惯性的多次验算<span style="color: black;">同样</span>,虽然对老玩家略显繁琐,但的确是最令新手<span style="color: black;">安心</span>的定心丸。</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><img src="https://p3-sign.toutiaoimg.com/tos-cn-i-6w9my0ksvp/74733d1ed36d4bc8abe621b9a927dafb~noop.image?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1723340421&x-signature=IHfU5Yj%2B8z6nQMRgnUb%2FSrY%2FZA4%3D" style="width: 50%; margin-bottom: 20px;"></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">经过</span>表头快速过滤出少部分数据进行“抽样检测”</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><img src="https://p9-sign.toutiaoimg.com/tos-cn-i-6w9my0ksvp/7478c12ac1e64aec8a2a48758782aa47~noop.image?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1723340421&x-signature=DU4TjAmMcOBXj%2FGyAO%2FuUyA97SU%3D" style="width: 50%; margin-bottom: 20px;"></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">灵活运用<span style="color: black;">过程</span>区的小技巧<span style="color: black;">帮忙</span>自己快速<span style="color: black;">检测</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><img src="https://p3-sign.toutiaoimg.com/tos-cn-i-6w9my0ksvp/af72a7babd3542d4a45d20e8e6991369~noop.image?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1723340421&x-signature=7tf6tSKRUkGeBaY3w3%2FyRqCf4ec%3D" style="width: 50%; margin-bottom: 20px;"></p>
<h1 style="color: black; text-align: left; margin-bottom: 10px;">结语</h1>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">综上所述,BI工具为数据预处理<span style="color: black;">供给</span>了强大而灵活的平台,<span style="color: black;">经过</span><span style="color: black;">把握</span>其中的技巧,<span style="color: black;">咱们</span>能够更加<span style="color: black;">有效</span>地应对<span style="color: black;">繁杂</span>的数据情境,为业务决策<span style="color: black;">供给</span>更有力的支持。在这个数据驱动的时代,深谙数据预处理之道,将<span style="color: black;">作为</span>每位数据分析专业人士<span style="color: black;">必要</span>具备的重要技能。不仅能够<span style="color: black;">提高</span>分析效率,更能够<span style="color: black;">保证</span><span style="color: black;">咱们</span>从数据中挖掘出准确、深刻的见解,为业务的成功铺平道路。</p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><img src="https://p3-sign.toutiaoimg.com/tos-cn-i-6w9my0ksvp/3b375f9bd3dc46548d0ca51038ae4bea~noop.image?_iz=58558&from=article.pc_detail&lk3s=953192f4&x-expires=1723340421&x-signature=zWrW%2BSb6WHUu4HcwfTfwAJ4QoyY%3D" style="width: 50%; margin-bottom: 20px;"></p>
你的见解独到,让我受益匪浅,非常感谢。 “沙发”(SF,第一个回帖的人) 楼主发的这篇帖子,我觉得非常有道理。
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