2024年数据分析师还有前途吗？知乎大神是这么回答的。
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><strong style="color: blue;"><span style="color: black;">“数据分析师还有前途吗？”</span></strong><span style="color: black;">这个问题真的是年年都有人问。在各个自<span style="color: black;">媒介</span>平台搜一下“数据分析师”，关注这个问题的人<span style="color: black;">非常多</span>。</span></span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">简单说一下，数据分析入行难度不高，这行的<strong style="color: blue;">底薪</strong><strong style="color: blue;">确实会稍好些，</strong>至于3-5年后的前途，就得看入行后怎么成长了。<span style="color: black;">哪些</span>说数据分析师天花板低，是<span style="color: black;">由于</span><span style="color: black;">她们</span><span style="color: black;">基本</span><span style="color: black;">无</span>去深入<span style="color: black;">认识</span>业务，<span style="color: black;">亦</span><span style="color: black;">无</span>深入地学技术。对于<span style="color: black;">奋斗</span>成长的人<span style="color: black;">来讲</span>，数据分析<span style="color: black;">专家</span>的这个天花板是非常高的，年薪50w都很普通。<span style="color: black;">因此</span>说，2024年还是要学数据分析的。</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><span style="color: black;">倘若</span>你是数据分析小白<span style="color: black;">或</span>刚好想学习数据分析，<span style="color: black;">能够</span>看下面的学习路线图。</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><img src="https://q4.itc.cn/q_70/images03/20240619/847bf7c4162841e0a99615e650278da6.gif" 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;"><span style="color: black;">怎样</span>学数据分析？</strong></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">数据分析的入门知识，大体分为以下这些内容，只要拿出你大学时啃高数的状态，每周夯实一个<span style="color: black;">基本</span>，三个月基本能学成。</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><strong style="color: blue;">一</strong></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><strong style="color: blue;">数据分析思维</strong></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><span style="color: black;">为何</span>要学习数据分析思维？<span style="color: black;">由于</span><span style="color: black;">倘若</span><span style="color: black;">咱们</span>在分析一个问题前，思维缺失就会<span style="color: black;">显现</span>不<span style="color: black;">晓得</span>问题出在哪里？学习数据分析思维就像是给大脑装了个GPS，当你面对一堆问题时，它就能帮你<strong style="color: blue;">快速定位</strong>，<strong style="color: blue;">找到<span style="color: black;">处理</span>问题的方向。</strong><span style="color: black;">倘若</span><span style="color: black;">无</span>这个思维，拿到数据就像是手里拿着一张地图，却不<span style="color: black;">晓得</span>怎么用，完全不<span style="color: black;">晓得</span>从<span style="color: black;">哪里</span>开始。</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><strong style="color: blue;"><span style="color: black;">常用的<span style="color: black;">有些</span>思维方式：</span></strong></span></p>
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<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><strong style="color: blue;">1、结构化思考</strong></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">结构化思考是《金字塔原理》的核心观点，把问题拆分成<span style="color: black;">区别</span>的方向，把所有能想到的点子都列出来，<span style="color: black;">而后</span><strong style="color: blue;">把这些想法按类别分好</strong>，最后用<strong style="color: blue;">思维导图</strong>把它们串起来，形成一个清晰的金字塔模型。</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><img src="//q4.itc.cn/q_70/images03/20240619/66da54f0742946a5ada908fb309d4507.jpeg" 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;"><span style="color: black;">经过</span>这种方式，<span style="color: black;">能够</span><strong style="color: blue;">更系统、更深入地思考问题</strong>，把一团麻变成一个表，就像是用放大镜观察细节，找到问题的核心。</span></p>
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<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><img src="//q0.itc.cn/q_70/images03/20240619/f118bbc2c3db42cea2f0f42ff15ac989.jpeg" 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;"><strong style="color: blue;">2、</strong></span><span style="color: black;"><strong style="color: blue;">业务化分析</strong></span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><span style="color: black;">业务化分析，<span style="color: black;">便是</span>把分析做到点子上，让分析结果能真正用得上，而<span style="color: black;">不仅</span>是一堆好看的数字和图表。这就<span style="color: black;">必须</span>数据分析师</span><strong style="color: blue;"><span style="color: black;">深入<span style="color: black;">认识</span>业务</span></strong><span style="color: black;">的每一个角落，<span style="color: black;">而后</span><strong style="color: blue;">把这些信息和<span style="color: black;">详细</span>项目结合起来</strong>，进行<strong style="color: blue;">深入的分析</strong>。<span style="color: black;">这般</span>分析结果<span style="color: black;">不仅</span>是停留在纸面上，而是<strong style="color: blue;">能够真正落地，</strong>对业务产生<span style="color: black;">实质</span>的影响。</span></span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><span style="color: black;">想要</span>对业务实实在在的<span style="color: black;">帮忙</span>，<span style="color: black;">必定</span>要带着业务思维去深挖，站在业务人员或分析对象的<span style="color: black;">方向</span>去思考问题，找<span style="color: black;">显现</span>象<span style="color: black;">背面</span>的<span style="color: black;">原由</span>，<span style="color: black;">或</span>用数据来推动业务的发展。</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><span style="color: black;">要培养这种业务思维，有几个<span style="color: black;">办法</span>：</span><strong style="color: blue;"><span style="color: black;">贴近业务，换位思考，<span style="color: black;">累积</span>经验</span></strong><span style="color: black;">，多参与<span style="color: black;">实质</span>的业务分析，<span style="color: black;">经过</span>实践来<span style="color: black;">累积</span>经验。</span></span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><span style="color: black;">另外</span>，在特定的业务场景下，还有<span style="color: black;">有些</span><span style="color: black;">基本</span>的分析<span style="color: black;">办法</span><span style="color: black;">能够</span><span style="color: black;">帮忙</span><span style="color: black;">咱们</span>构建分析模型，<span style="color: black;">例如</span>：</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><span style="color: black;"><strong style="color: blue;">·</strong></span><strong style="color: blue;">象限法</strong><span style="color: black;">：<span style="color: black;">经过</span>两个维度将数据分为四个象限，<span style="color: black;">帮忙</span><span style="color: black;">咱们</span>快速识别问题和机会。</span></span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><span style="color: black;"><strong style="color: blue;">·</strong></span><strong style="color: blue;">多维法</strong><span style="color: black;">：从多个<span style="color: black;">方向</span>分析数据，以<span style="color: black;">得到</span>更全面的视角。</span></span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><span style="color: black;"><strong style="color: blue;">·</strong></span><strong style="color: blue;">假设法</strong><span style="color: black;">：基于假设进行分析，<span style="color: black;">而后</span><span style="color: black;">经过</span>数据来验证这些假设。</span></span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><span style="color: black;"><strong style="color: blue;">·</strong></span><strong style="color: blue;">指数法</strong><span style="color: black;">：<span style="color: black;">运用</span>指数来衡量业务的增长或衰减趋势。</span></span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><span style="color: black;"><strong style="color: blue;">·</strong></span><strong style="color: blue;">二八法</strong><span style="color: black;">：即帕累托原则，关注最重要的20%<span style="color: black;">原因</span>，它们<span style="color: black;">常常</span>能产生80%的效果。</span></span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><span style="color: black;"><strong style="color: blue;">·</strong></span><strong style="color: blue;">对比法</strong><span style="color: black;">：<span style="color: black;">经过</span>比较<span style="color: black;">区别</span>时间段或<span style="color: black;">区别</span>对象的数据，找出差异和趋势。</span></span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><span style="color: black;"><strong style="color: blue;">·</strong></span><strong style="color: blue;">漏斗法</strong><span style="color: black;">：分析业务流程中的各个<span style="color: black;">周期</span>，找出瓶颈和改进点。</span></span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">这些思维模型就像是<span style="color: black;">区别</span>的工具，每种工具都适合<span style="color: black;">区别</span>的场景。<span style="color: black;">经过</span>对这些思维模型的学习和训练，<span style="color: black;">咱们</span><span style="color: black;">能够</span>更<strong style="color: blue;">有效地观察事物、分析问题</strong>，<span style="color: black;">加强</span><span style="color: black;">处理</span>问题的成功率。</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><strong style="color: blue;">二</strong></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><strong style="color: blue;">硬技能</strong></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><strong style="color: blue;"><span style="color: black;">Excel</span></strong></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">学习Excel是一个循序渐进的过程</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><strong style="color: blue;"><span style="color: black;"><span style="color: black;">基本</span>的：</span></strong><span style="color: black;">简单的表格数据处理、筛选、排序</span></span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><strong style="color: blue;"><span style="color: black;">函数和公式：</span></strong><span style="color: black;">常用函数、高级数据计算、数组公式、多维引用、function</span></span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><strong style="color: blue;"><span style="color: black;">可视化图表：</span></strong><span style="color: black;">图形图示展示、高级图表、图表插件</span></span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">数据透视表、VBA程序<span style="color: black;">研发</span>……</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><span style="color: black;">根据</span>这个<span style="color: black;">办法</span>，先过一遍<span style="color: black;">基本</span>，<span style="color: black;">认识</span>个大概，<span style="color: black;">而后</span>去找些案例练习。多逛逛excelhome论坛，平常多思考<span style="color: black;">怎样</span>用excel来<span style="color: black;">处理</span>问题。</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><span style="color: black;">另一</span>，<span style="color: black;">此刻</span><strong style="color: blue;">Excel的AI工具<span style="color: black;">非常多</span></strong>，能<span style="color: black;">火速</span><span style="color: black;">提高</span>效率，<span style="color: black;">能够</span>关注这5个小工具。</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;">【干货】5款超强大的AI数据分析工具，<span style="color: black;">意见</span><span style="color: black;">保藏</span> </p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><strong style="color: blue;"><span style="color: black;">SQL</span></strong></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">做数据分析，<strong style="color: blue;">取数、清洗数据，基本都要依赖SQL</strong>。初入门<span style="color: black;">周期</span>，<span style="color: black;">针对</span>数据库不必太焦虑，只需<span style="color: black;">认识</span>常用的数据库类型，能够在现有的表格里面<span style="color: black;">查找</span>出数据，能够<strong style="color: blue;">更新数据对数据进行重编码，<span style="color: black;">晓得</span>怎么<span style="color: black;">增多</span>添加数据</strong>，把数据变得规整就行。</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><span style="color: black;">理解<strong style="color: blue;">主键，索引等含义和用处</strong>；导入导出数据<span style="color: black;">能够</span><span style="color: black;">运用</span>工具，分析数据<span style="color: black;">能够</span><span style="color: black;">运用</span>OBDC</span><span style="color: black;"><span style="color: black;">或</span>其他的接口对数据库进行连接。</span></span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><strong style="color: blue;"><span style="color: black;">取数的排序，</span></strong><span style="color: black;">做数据的交集并集</span><span style="color: black;">，数据转换，数据表合并等这些，最好<span style="color: black;">亦</span>能<span style="color: black;">把握</span>。</span></span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><img src="//q1.itc.cn/q_70/images03/20240619/ecaf145900d9438293761306cda14fd4.jpeg" 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;"><span style="color: black;">统计学</span></strong></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><span style="color: black;">为何</span>要学统计学？</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">数据怎么能说话呢，算出一个数据，怎么<span style="color: black;">晓得</span>这个数据是好还是坏？<strong style="color: blue;">有多好有多坏？</strong>两组数据呈<span style="color: black;">此刻</span>你面前，<strong style="color: blue;">怎么判断这两组数据<span style="color: black;">是不是</span>有<span style="color: black;">显著</span>差异？</strong></span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">要回答这些问题，就<span style="color: black;">必要</span>要用到统计学知识，而不是相信自己的眼睛，<span style="color: black;">由于</span>眼睛有时候<span style="color: black;">亦</span>会说谎，你看到的“好”不<span style="color: black;">必定</span>是好，你看到的“<span style="color: black;">无</span>差异”不<span style="color: black;">表率</span><span style="color: black;">无</span>差异。</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><span style="color: black;">针对</span>大部分数据分析师<span style="color: black;">来讲</span>，并不<span style="color: black;">必须</span><span style="color: black;">把握</span>的<span style="color: black;">那样</span>全面和深入，<span style="color: black;">咱们</span>只<span style="color: black;">必须</span><strong style="color: blue;"><span style="color: black;">把握</span>部分知识点</strong>，理论<span style="color: black;">倘若</span>暂时搞不懂，只要先<span style="color: black;">晓得</span>在<strong style="color: blue;">什么场景下用</strong>就行，用起来你才会慢慢地搞懂！</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><img src="//q2.itc.cn/q_70/images03/20240619/018bfbf24c6b400b8c2136066d5ec942.jpeg" 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;"><strong style="color: blue;"><span style="color: black;">数据可视化</span></strong></span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">可视化说白了是一种表达，<strong style="color: blue;">数据分析结果表达</strong>的<span style="color: black;">是不是</span>到位，领导<span style="color: black;">是不是</span>认同，工资涨不涨，全靠这可视化。</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><span style="color: black;">怎样</span><strong style="color: blue;"><span style="color: black;">选取</span>最佳的图表类型？</strong>趋势性、<span style="color: black;">关联</span>性、分布性、周期性、地理位置分布性……</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">颜色和字体等细节样式方面，<span style="color: black;">怎样</span>进行更加<strong style="color: blue;">美观的调配？</strong></span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><span style="color: black;">布局设计原则，</span><strong style="color: blue;"><span style="color: black;">故事性<span style="color: black;">部署</span>可视化仪表板</span></strong><span style="color: black;">，报告的标题和结论注释，以及整体展现的<span style="color: black;">规律</span>性。</span><span style="color: black;">还有<span style="color: black;">非常多</span>可视化的陷阱，都<span style="color: black;">必须</span>认真学习。</span></span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><img src="//q6.itc.cn/q_70/images03/20240619/10133dea915c4238970db37bcfa6d787.jpeg" 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;"><strong style="color: blue;"><span style="color: black;">怎样</span><span style="color: black;">有效</span>学习数据分析</strong></span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><img src="https://q0.itc.cn/q_70/images03/20240619/fe9ebe6424214d0d865d5c1eb3348a27.gif" 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;"><strong style="color: blue;">在学习这块，觉得效率和实用最重要，看<span style="color: black;">欠好</span>的书，看无用的书，</strong><span style="color: black;"><span style="color: black;">常常</span>感动了自己，却做不出感动上司和领导的成绩，你的能力并<span style="color: black;">无</span>得到提升。</span></span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><strong style="color: blue;"><span style="color: black;">倘若</span>你<span style="color: black;">亦</span>想跟着老师快速学习，</strong><span style="color: black;"><span style="color: black;">这儿</span>我给<span style="color: black;">大众</span><span style="color: black;">举荐</span>一下CDA Level I 考证班。</span></span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">“<strong style="color: blue;">CDA数据分析师认证</strong>”是一套科学化，专业化，国际化的人才考核标准，共分为CDA LEVELⅠ ，LEVEL Ⅱ，LEVEL Ⅲ三个等级，<span style="color: black;">触及</span>行业<span style="color: black;">包含</span>互联网、金融、咨询、电信、零售、医疗、旅游等，<span style="color: black;">触及</span>岗位<span style="color: black;">包含</span>大数据、数据分析、市场、<span style="color: black;">制品</span>、运营、咨询、投资、<span style="color: black;">开发</span>等。该标准符合当今<span style="color: black;">全世界</span>数据科学技术潮流，<span style="color: black;">能够</span>为各行业企业和<span style="color: black;">公司</span><span style="color: black;">供给</span>数据人才参照标准。</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">CDA数据分析师行业标准由国际范围数据科学<span style="color: black;">行业</span>的行业专家、学者及知名企业<span style="color: black;">一起</span>制定并每年修订更新，<span style="color: black;">保证</span>了标准的公立性、权威性、前沿性。<span style="color: black;">经过</span>CDA认证考试者可<span style="color: black;">得到</span>CDA数据分析师中英文认证证书。</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;"><strong style="color: blue;"><span style="color: black;">CDA Level I 考证班</span></strong></span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">专门为<span style="color: black;">期盼</span>零<span style="color: black;">基本</span>学习业务数据分析技能的在职人员以及<span style="color: black;">期盼</span>参与 CDA LEVEL I 考试的人员开设。课程技能覆盖各行业的业务数据分析岗、数据运营岗、数据<span style="color: black;">制品</span>岗、数据营销岗等数据分析专项技能岗所<span style="color: black;">需求</span>的技能，<span style="color: black;">同期</span>适用于财务数据分析、人力资源数据分析等数据赋能岗。</span></p>
<p style="font-size: 16px; color: black; line-height: 40px; text-align: left; margin-bottom: 15px;"><span style="color: black;">课程适合<strong style="color: blue;">零<span style="color: black;">基本</span>学员学习</strong>，课程设计遵循循序渐进的<span style="color: black;">教育</span>规律，<span style="color: black;">包括</span> Excel、PowerBI、SQL 数据库、统计学<span style="color: black;">基本</span>等工具与理论课程模块，<span style="color: black;">同期</span><span style="color: black;">包括</span><span style="color: black;">海量</span>基于<span style="color: black;">实质</span>业务场景的各行业实战项目案例，<span style="color: black;">例如</span><span style="color: black;">经过</span>制作客户运营分析仪表板实现客户价值分析、挖掘潜在客户、监控电商运营指标等，<span style="color: black;">提高</span>电商运营效益。</span></p>
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