Name: 什麼是數據倉庫？ (What Is a Data Warehouse?)
Uploaded: 2025-06-03T12:14:23.000Z
Duration: 3 min 32 s

Data warehousing is one of the hottest topics both in business and in data science.

數據倉庫是商業和數據科學領域最熱門的話題之一。

情態副詞

But if you're new to the field, you're probably wondering what a data warehouse is, why we need it, and how it works.

但如果你是該領域的新手，你可能會想知道什麼是數據倉庫，為什麼我們需要它，以及它是如何工作的。

轉承詞

Don't worry, because in 4 minutes, you'll know the answers to all these questions.

別擔心，因為在 4 分鐘內，你就能知道所有這些問題的答案。

Alright, first, let's start with the definition.

好吧，首先讓我們從定義開始。

What is the meaning of the phrase, single source of truth?

單一真理源泉 "這句話的含義是什麼？

In information systems theory, the single source of truth is the practice of structuring all the best quality data in one place.

在信息系統理論中，"單一真實來源 "是將所有高質量數據集中到一個地方的做法。

讓我們來看一個非常簡單的例子。

Surely it has happened to you to work on a file and to create many different versions of it.

您肯定遇到過這樣的情況：在處理一個文件時，您會創建許多不同的版本。

Well, once you are done, you often place the word, final, at the end.

好吧，一旦你完成了，你通常會在最後加上 "最後 "這個詞。

This results in having a bunch of files with extensions, final, final, final, final, final, or my favorite, really final, final.

這樣就會出現一堆擴展名為 final、final、final、final、final、final 或我最喜歡的 final、final 的文件。

如果你是這樣的人，你並不孤單。

It seems that even corporations never know where the most recent or most appropriate file is.

似乎就連公司也不知道最新或最合適的文件在哪裡。

But what if you knew that there is one single place where you would always have the single source of information?

但是，如果您知道有一個地方可以讓您始終獲得唯一的資訊來源，那又會怎樣呢？

That would be quite helpful, wouldn't it?

Well, a data warehouse exists to fill that need.

那麼，數據倉庫的存在就是為了滿足這一需求。

那麼，究竟什麼是數據倉庫呢？

It is the place where companies store their valuable data assets, including customer data, sales data, employee data, and so on.

它是公司存儲客戶數據、銷售數據、員工數據等寶貴數據資產的地方。

In short, a data warehouse is the de facto single source of data truth for an organization.

簡而言之，數據倉庫是企業事實上的單一數據源。

It is usually created and used primarily for data reporting and analysis purposes.

它通常主要用於數據報告和分析目的。

There are several defining features of a data warehouse.

It is subject-oriented, integrated, time-variant, non-volatile, summarized.

它具有主題導向性、綜合性、時變性、非易失性和總結性。

Let's quickly go through these one by one.

Subject-oriented means that the information in a data warehouse revolves around some subject.

面向主題是指數據倉庫中的資訊圍繞某個主題展開。

Therefore, it does not contain all company data ever, but only the subject matters of interest.

是以，它並不包含公司的所有數據，而只包含感興趣的主題。

For instance, data on your competitors need not appear in a data warehouse.

例如，有關競爭對手的數據不必出現在數據倉庫中。

However, your own sales data will most certainly be there.

不過，您自己的銷售數據肯定會存在。

Integrated corresponds to the example from the beginning of the video.

綜合與視頻開頭的例子相對應。

Each database or each team or even each person has their own preferences when it comes to naming conventions.

每個數據庫、每個團隊甚至每個人在命名約定方面都有自己的偏好。

That is why common standards are developed to make sure that the data warehouse picks the best quality data from everywhere.

這就是為什麼要制定通用標準，以確保數據倉庫能從各處選取最優質的數據。

This relates to master data governance, but that is a topic for another time.

這與主數據治理有關，但這是另一個話題。

Time-variant relates to the fact that a data warehouse contains historical data too.

時間變量與數據倉庫也包含歷史數據這一事實有關。

As said before, we mainly use a data warehouse for analysis and reporting, which implies we need to know what happened 5 or 10 years ago.

如前所述，我們主要使用數據倉庫進行分析和報告，這意味著我們需要知道 5 年或 10 年前發生了什麼。

Non-volatile implies that the data only flows in the data warehouse as is.

非易失性意味著數據只能原封不動地在數據倉庫中流動。

Once there, it cannot be changed or deleted.

一旦存在，就無法更改或刪除。

Summarized once again touches upon the fact that the data is used for data analytics.

總結再次觸及數據用於數據分析這一事實。

Often it is aggregated or segmented in some ways, in order to facilitate analysis and reporting.

為了便於分析和報告，通常會以某種方式對其進行彙總或細分。

Alright, so that's what a data warehouse is – a very well-structured and non-volatile de facto single source of truth for a company.

好吧，這就是數據倉庫--一個結構非常完善、不易揮發的公司事實上的單一真相來源。

If you enjoyed this video, don't forget to hit the like button and share it with your friends.

如果您喜歡這段視頻，別忘了點擊 "喜歡 "按鈕並與朋友分享。

And if you'd like to become an expert in all things data science, subscribe to our channel.

如果您想成為數據科學方面的專家，請訂閱我們的頻道。