12 posts tagged with "Data Analysis"

Introduction​

"According to incomplete statistics, the proportion of white hair of data workers is higher than the average of the same age group." by a data worker

Data, a familiar but mysterious word, has become a totem pursued by everyone. Managers love fancy data reports, data analysts are keen on building complicated statistical models, and salesmen take dashboards as compasses to see whether they can complete their KPIs. Since over ten years ago, the data industry has been developing fast, and there have been some novel yet formidable jargons, such as Big Data, Data Science, Data Lake, Data Mesh, Data Governance. Yet the "traditional" terms are still abstruse: Data Warehouse, Business Intelligence, Data Mart, Data Mining. What is more headachy is that many people are still unable to understand their relationship with recently popular concepts such as Artificial Intelligence, Machine Learning, and Deep Learning. These hot buzzwords are the results of aggressive development in the data area.

Professional Doctor or Fortune Teller?​

Years ago, with the rapid development of the Internet industry, the bubble of the data industry was getting larger. Data, the by-product of the Internet applications, has large volumes and diversities. Data owners would like to get the most out of it and regard it as the gold mine. Therefore, data mining engineers became one of the most popular professionals. Later, a brand new yet more popular position Data Scientist emerged as "the sexiest job in the 21st century".

The popularity of data scientists is its requirement for abilities and experience in various areas:

• Programming Skills: at least able to use Python or R to do data cleansing, analysis and modeling.
• Mathematics and Statistics: familiar with probability theory, calculus, and discrete mathematics.
• Business Knowledge: deep understanding of market, process and macro trends in related areas.
• Communication Skills: able to convey insights and analysis results in a human-friendly way.

Introduction​

A bad plan is better than no plan.

坏计划也好过没有计划。--彼得·蒂尔《从0到1》

In software development engineering, there are rarely lone wolf programmers. This is because modern, commonly seen software projects are usually very complex, requiring substantial human resources, resources, and time. Having a single developer complete a large software project alone would be like "an old man moving mountains." Therefore, software development is inseparable from team collaboration and project management. Project Management, simply put, is a methodology for orderly organizing, planning, executing, and completing various tasks in a project. Of course, the actual scope of project management goes far beyond this, usually involving resource allocation, priority setting, progress tracking, etc. It's a product of the Industrial Revolution and a branch of modern management science that can significantly improve engineering completion efficiency and success rates. This article mainly discusses software project management, which is very different from traditional project management in construction engineering, mechanical engineering, etc. Early IT project management borrowed from traditional project management methodologies like construction engineering, playing an important role in the early information age and significantly improving software development and collaboration efficiency. However, with the rapid development of the IT industry, consumer product demands change rapidly, and market conditions have become increasingly volatile. Traditional software project management models can no longer meet software development needs. Therefore, modern software development models, such as Agile Development, emerged and became the preferred choice for many internet companies.

What are the drawbacks of traditional project management models (such as waterfall)? What improvements do modern project management models (such as agile) offer? Should we completely abandon waterfall models and fully embrace agile development? As a programmer, should you master some project management knowledge and related tools? As a team leader, how should you establish project management processes to ensure development efficiency and quality? If readers have similar questions, this article will provide detailed analysis and answers.