The Data Analytics Skills Employers Are Seeking Most
In our modern economy, data is often acclaimed as the most valuable currency. 有一个无限的信息存储在网络，存储和 cloud. 问题是大部分数据都是非结构化的，因此不容易使用.
因此，数据分析技能受到追捧也就不足为奇了 by employers looking to harness the power of data. The ability to gather, analyze 并且解释原始数据可以让组织做出明智的决策，优化工作流程 and gain a competitive edge.
加入我们，让我们一起探索数据分析需要什么，并发现九项重要技能 for data analytics professionals with insight from Dr. Srikanth Mudigonda, director of analytics at 博彩网址大全’s School for Professional Studies.
But First, What Does a Data Analyst Do?
Before diving in, it’s important to understand this role. According to Dr. Mudigonda, “数据分析师帮助企业在运营和运营方面做出数据驱动的决策 strategic levels.” They accomplish this wrangling and examination of data to extract 有意义的见解，识别模式，并提出明智的建议.
According to the Computing Technology Industry Association (CompTIA), the three stages of data use are:
- Collect and store
- Process and organize
- Analyze and visualize
Data analysts work across all three stages. Their job requires a combination of technical expertise, statistical knowledge and business acumen. Analysts are needed in all kinds of industries, 包括会计、金融、银行、零售、营销、房地产、医疗保健、 sales, wholesalers and more.
Nine Data Analytics Skills That are in High Demand
有大量的技术知识和技能应该不足为奇 needed to work in data analytics. But “soft” skills are just as important to be successful in the field. In fact, it is this “Combination of conceptual, analytical, technical 以及使数据分析师在任何组织中都成为宝贵资产的沟通技巧。” says Dr. Mudigonda.
让我们来仔细看看雇主最看重的九种能力 are looking for when hiring data analysts.
Computer and Technical Skills for Data Analysts
要履行数据分析师的职责，您需要掌握一些专业知识 skills. Here are five that are becoming increasingly important:
1. Data Manipulation
Experts estimate that 90% of all data that is generated around the world is unstructured, meaning it follows no defined schema. This makes it very difficult to catalogue or sort.
数据操作包括清理信息、减少冗余和组织 it in a more accessible format. This step is crucial because it creates a usable data set that can be shared and analyzed.
2. Mathematics, Statistical Analysis and Modeling
分析大量的信息往往是复杂的，需要精通 of math concepts like:
- Data mining
- Marketing analytics
- Web analytics
- Risk analytics
- Descriptive and inferential statistics
- Regression analysis
- Calculus
- Linear algebra
使用这些技术，分析师可以发现隐藏的模式，使准确 预测并提取有价值的见解以使其组织受益.
3. Machine Learning
Machine learning is a branch of artificial intelligence 这教会了计算机如何在没有编程的情况下预测和预测结果 to do so. 计算机是使用大量非结构化数据和高度结构化数据进行“训练”的 engineered algorithms.
Data analysts can make use of machine learning techniques like:
- Predictive modeling
- Classification
- Clustering
- Anomaly detection
- Natural language processing (NLP)
这门学科需要对数据科学和软件工程有深刻的理解. 投资开发这些技能的数据分析师将处于有利地位 this cutting-edge technology.
4. Proficiency in Programming Languages
编程语言是使高效工作成为可能的基本工具 with large data sets. Some of the most commonly used programming languages are:
- Python
- R
- SQL (Structured Query Language)
- Julia
- Scala
作为一名分析师，多才多艺，乐于学习新的语言和技术 会提升你的简历，并有可能增加你的工作机会吗.
5. Data Visualization
一旦你收集了信息，将其编译成有用的数据集并进行分析 thoroughly, it’s time to share your findings. Turning raw data into a compelling argument or clearly laid out narrative can be tricky.
这就是为什么分析师使用他们的数据可视化技能来创建可视化模型和 representations of their work. Examples of data visualization could include:
- Dashboards
- Charts
- Graphs
- Tables
- Infographics
- Business intelligence reports
数据分析师经常使用可视化工具，如Tableau、Power BI、Google Charts 和微软Excel，所以熟悉这些程序可以帮助你成为一名优秀的工程师 competitive job candidate.
Communication and Organization skills for Data Analysts
最好的数据分析师都有一套坚实的软技能，而软技能不是 具体到任何一个工作-以补充上述技术能力.
以下是帮助数据分析师有效完成工作的四个重要品质:
6. Strong Written Communication
您可能会惊讶地发现，数据分析师实际上做了大量的写作工作. Analysts 应该是一个善于沟通的人，能够提供清晰而简洁的见解. They are 通常的任务是在报告、电子邮件、白皮书、案例中列出他们的发现 studies and other documents.
数据分析师还负责记录他们的流程和方法. 保持准确的记录可以实现知识共享、再现性和透明度.
7. Public Speaking
用数据讲故事需要语言沟通和表达能力 技能，特别是在向非技术受众传递信息时. Many data 分析类工作需要分析师定期分享他们的发现和建议 basis. 这意味着公开演讲、参加会议和演讲是必不可少的 parts of the job.
8. Problem Solving
数据分析师的任务通常是识别改进的机会 and solving existing problems within an organization. This requires careful consideration, objectivity and creativity.
Critical thinking skills are crucial for making informed decisions. Data analysts 必须能够在任何给定的情况下采用深思熟虑和合乎道德的循证策略 situation.
9. Collaboration
与主管、商业领袖、同事、客户合作的能力 与业务中的其他利益相关者沟通是数据分析师的一项关键技能. They 经常在团队中收集和处理信息，建立关键绩效 indicators (KPIs) and make smart recommendations for business growth.
建立关系和人际交往能力对这个角色很重要. 数据分析师通常必须依赖于公司内的其他部门和个人 要及时提供数据——同时也需要了解受众的需求 their reports.
Become the Data Analyst Today’s Organizations Need
随着组织在使用数据和先进人工智能工具方面的成熟，有越来越多的 需要训练有素和有道德的专业人士磨练上述技能; Dr. Mudigonda says. “公司需要分析师保持信息灵通，做出数据驱动的决策 and stay competitive in the market.”
也许你已经具备了本文中概述的一些软技能， 而他们所缺少的只是一套专门的技术能力.
看看博彩网址大全(Saint Louis University)的分析学硕士学位就知道了. As part 该课程是为忙碌的专业人士开设的 像你一样，在线和混合课程分成八周的课程.
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