Stay tuned.

敬請期待。

Hey everyone, I'm Josh Matlock.

大家好，我是喬希-馬特洛克。

For those of you who are new to my channel, I am a clinical data analyst with eight years of experience and in my channel, I teach current and aspiring data professionals how to succeed in the healthcare industry.

我是一名擁有八年工作經驗的臨床數據分析師，在我的頻道里，我向在職和有抱負的數據專業人士傳授如何在醫療保健行業取得成功。

Jumping right into things, there are four major types of data that you might expect to encounter in the healthcare industry.

直接進入主題，您可能會在醫療保健行業遇到四大類型的數據。

They are data coming from EHRs or electronic health records, clinical slash disease registries, claims data, and external reporting data.

這些數據來自電子病歷或電子健康記錄、臨床疾病登記、報帳數據以及外部報告數據。

And that's things like data that have to be submitted to various vendors and organizations for various reasons.

比如出於各種原因必須提交給不同供應商和組織的數據。

As you can imagine, healthcare data covers a very wide variety of subjects and it's very rich.

可以想象，醫療保健數據涵蓋的主題非常廣泛，內容也非常豐富。

So let's start with EHR data.

是以，讓我們從電子病歷數據開始。

EHRs are a type of software that allow healthcare professionals to document information about a patient, order tests, medications, and labs, schedule appointments and surgeries, assign resources to a patient, and much more.

電子病歷是一種軟件，可讓醫療保健專業人員記錄病人的資訊，開具化驗單、藥單和化驗單，安排預約和手術，為病人分配資源等。

Believe it or not, only in the last 10 to 15 years have we actually seen EHRs be widely adopted in the United States, which could explain why healthcare has a lot of technical debt compared to other industries like banking or tech, which have had digital records for much longer.

信不信由你，只有在過去的 10 到 15 年裡，我們才真正看到電子病歷在美國被廣泛採用，這也可以解釋為什麼醫療保健行業與銀行或科技等其他行業相比存在大量技術債務，而這些行業擁有數字記錄的時間要長得多。

In general, when you're a patient in a hospital, there could be many different people interacting with the EHR to record the details of the encounter.

一般來說，當病人在醫院就診時，可能會有許多不同的人與電子病歷互動，以記錄就診細節。

For example, if a patient came into the hospital with appendicitis, there might be a record showing the patient arriving in the emergency room, along with the notes describing what the doctor actually observed when they evaluated the patient.

例如，如果一名病人因闌尾炎入院，可能會有一份記錄顯示病人到達急診室的情況，以及醫生在評估病人時實際觀察到的情況。

There might be a section where the patient's vitals were assessed.

可能會有一個評估病人生命體徵的部分。

There might have been lab values that were drawn, a physical examination.

可能會進行化驗和體格檢查。

There could have been relevant imaging performed, as well as a surgery to remove the appendix.

可能已經進行了相關的影像學檢查，以及闌尾切除手術。

A medical coder is going to assign ICD-10-CM codes to provide the patient with a diagnosis, as well as possibly ICD-10-PCS codes, which are the inpatient procedural codes that identify the surgery.

醫療編碼員將分配 ICD-10-CM 代碼，為患者提供診斷，還可能分配 ICD-10-PCS 代碼，即確定手術的住院程序代碼。

Many staff members might be entering information into the patient's chart, and they can see those updates live.

許多工作人員可能正在將資訊輸入病人的病歷，他們可以實時看到這些更新。

However, if you wanted to pull data out of the EMR en masse for a group of patients and not just one, using something like SQL, you're probably not going to be able to see the data live like the clinicians that are documenting.

但是，如果你想使用類似 SQL 的方法從 EMR 中提取一組病人（而不僅僅是一個病人）的數據，你可能無法像正在記錄的臨床醫生一樣看到實時數據。

Why is that?

為什麼會這樣？

Well, many medical applications use a language called MUMPS, which stands for the Massachusetts General Hospital Utility Multiprogramming System, also known as M.

許多醫療應用程序都使用一種名為 MUMPS 的語言，MUMPS 是麻省總醫院實用程序多編程系統的縮寫，也被稱為 M。

MUMPS is a programming and database management language that is used widely in EHRs.

MUMPS 是一種編程和數據庫管理語言，在電子病歷中廣泛使用。

However, the way that it stores data is complicated.

不過，它存儲數據的方式比較複雜。

The data is basically stored like a tree, where data exists at terminal nodes.

數據基本上像樹一樣存儲，數據存在於終端節點。

This differs dramatically from relational database management systems, which store data in a tabular format.

這與以表格格式存儲數據的關係數據庫管理系統大相徑庭。

It has to be moved over to the tabular format using a data migration process called ETL, which stands for extract, transform, and load.

必須使用一種稱為 ETL（提取、轉換和加載）的數據遷移過程，將其轉換為表格格式。

Because there's so much data that needs to be transported, it would be very inefficient to transmit it every single second or minute.

因為需要傳輸的數據量太大，如果每秒或每分鐘都傳輸數據，效率會非常低。

So instead, data usually gets moved from that MUMPS database into a relational database in one big giant batch every night.

是以，數據通常會在每天晚上從 MUMPS 數據庫轉移到關係數據庫中，形成一個巨大的批次。

So by the time you see that data in SQL, it's already about a day old usually.

是以，當你在 SQL 中看到這些數據時，通常已經是一天前的數據了。

There are many tables that you will see imported into the relational database from the EMR system.

你會看到有許多表格從 EMR 系統導入到關係數據庫中。

Some of the main ones include patient information, like their name and their demographics, encounter information, and that'll include things like outpatient encounters, where the patient will usually be in the hospital for less than a day, or inpatient encounters, where the patient needed to be hospitalized and spend several days in the hospital.

其中一些主要資訊包括病人資訊（如姓名和人口統計數據）、就診資訊（如門診病人就診資訊，病人通常在醫院住院不到一天）或住院病人就診資訊（病人需要住院並在醫院住上幾天）。

You also have observations information, which are things like lab values, survey data, vitals, and those are recorded multiple times over a given period using something called a flowsheet.

你還需要觀察資訊，如化驗值、調查數據、生命體徵等，這些資訊會在特定時間段內使用一種叫做 "流程表 "的東西進行多次記錄。

You also have a conditions table, which will store things like the diagnosis during the encounter or the admitting diagnosis or the discharge diagnosis.

您還有一個條件表，用於存儲會診期間的診斷、入院診斷或出院診斷等資訊。

You might have a problem list, which tracks the active and resolved problems that a patient had throughout their lifetime.

您可能有一個問題列表，用於跟蹤病人一生中遇到的有效問題和已解決的問題。

There's going to be a procedures table that's going to track all of the surgeries or medical interventions that were needed to be performed on the patient, and those could be major things like heart transplants, or they could be routine things like a colonoscopy.

這裡會有一個程序表，跟蹤病人需要進行的所有手術或醫療干預，這些可能是心臟移植等重大手術，也可能是結腸鏡檢查等常規手術。

This doesn't even scratch the surface of the type of data that you might expect to see in an EMR relational database.

這還不是您可能希望在醫療記錄系統關係數據庫中看到的數據類型的表面。

The list goes on and on and on, but needless to say, one patient can generate an enormous amount of data within their lifetime for just one hospital.

這樣的例子不勝枚舉，但毋庸置疑的是，一個病人在其一生中會為一家醫院產生大量數據。

The two most common EHRs are Epic and Cerner, which possess most of the market share when it comes to EHRs.

最常見的兩種電子病歷是 Epic 和 Cerner，它們佔據了電子病歷的大部分市場份額。

Now, before we move on, I should mention that I have a free 13-page PDF on my website that teaches you more about the most common EHR data that you'll encounter as a data analyst, as well as important clinical concepts that you should be familiar with.

現在，在我們繼續之前，我應該提一下，我的網站上有一份免費的 13 頁 PDF 文件，教你更多作為數據分析師會遇到的最常見的電子病歷數據，以及你應該熟悉的重要臨床概念。

So I encourage you to check that out.

所以，我鼓勵你們去看看。

This is actually an excerpt from my upcoming clinical analytics accelerator course, which I hope to launch by the end of the year.

這實際上是我即將推出的臨床分析加速器課程的節選，我希望能在年底推出該課程。

So if you want to receive a copy of that PDF, go to my website, datawizardry.academy, input your name and email, and I'll send you a copy of the PDF.

是以，如果你想收到 PDF 的副本，請訪問我的網站 datawizardry.academy，輸入你的姓名和電子郵件，我就會給你發送 PDF 的副本。

You can opt out of future emails at any time.

您可以隨時退出今後的電子郵件。

I also have an entire one-hour lesson dedicated to learning the basics of SQL with EMR data using a synthetic dataset called Cynthia.

我還有一整節一小時的課程，專門使用名為 Cynthia 的合成數據集，通過 EMR 數據學習 SQL 的基礎知識。

So also check that tutorial out if you haven't already.

所以，如果還沒有的話，也可以看看這個教程。

All right, so next we have claims data.

好了，接下來是索賠數據。

Now, to be honest, claims data is the one that I'm least familiar with as I don't work with this data very often.

老實說，理賠數據是我最不熟悉的數據，因為我並不經常使用這些數據。

So I invite other people watching this video to leave a comment if you have anything to add or revise.

是以，如果您有任何需要補充或修改的地方，請在觀看本視頻時留言。

But for the most part, claims data is simply a request submitted by doctors, hospitals, and pharmacies to an insurance company to get reimbursed for the medical care that they're providing.

但在大多數情況下，理賠數據只是醫生、醫院和藥房向保險公司提交的申請，以獲得醫療服務的報帳。

The amount that a hospital gets paid depends on the complexity of the claim and the resources allocated to treat that patient.

醫院獲得的賠付金額取決於索賠的複雜程度以及為治療該患者所分配的資源。

There's also a process called adjudication where the claim is evaluated by the insurance company to determine how legitimate the claim is before they actually pay the amount that is requested.

保險公司在實際支付索賠金額之前，還要對索賠進行評估，以確定索賠的合法性。

For example, a provider might commit fraud by trying to submit a claim using a diagnosis code that they know will earn them more money than a more accurate code that would make them less.

例如，醫療服務提供者可能會進行欺詐，試圖使用他們知道會比更準確的代碼賺更多錢的診斷代碼提交索賠，而更準確的代碼會讓他們賺更少的錢。

Insurance companies don't want to pay more than they have to, so they adjudicate the claims to ensure that the money that they are about to pay is fair and accurate.

保險公司不希望支付超過他們必須支付的金額，是以他們會對索賠進行裁定，以確保他們將要支付的金額是公平和準確的。

The claims data might be pre-adjudicated or post-adjudicated, and it might also contain information like the name of the provider submitting the claim, the amount paid out by the insurance company to the provider submitting the claim, procedure codes that were rendered during the encounter, diagnosis codes, information about the beneficiary or the patient whom the claim was about.

理賠數據可能是裁定前的數據，也可能是裁定後的數據，還可能包含提交理賠的醫療服務提供者的名稱、保險公司向提交理賠的醫療服務提供者支付的金額、診療過程中提供的程序代碼、診斷代碼、受益人或理賠病人的相關資訊。

But claims data doesn't capture as much detail as EHRs do.

但報帳數據並不像電子病歷那樣能捕捉更多細節。

For example, we might be able to see that a test was given to a particular patient in the claims data on a certain date, but we won't be able to see what the test results were like we might see in the EHR.

例如，我們也許能在報帳數據中看到某患者在某日接受了某項檢查，但我們無法像在電子病歷中那樣看到檢查結果。

So what advantage does claims data confer over EHR records?

那麼，與電子病歷記錄相比，報帳數據有什麼優勢呢？

Well, the data might capture information not just from one healthcare organization, but many if it is held by an organization that is administering insurance, like the Center for Medicare and Medicaid Services.

那麼，這些數據獲取的資訊可能不只來自一家醫療機構，如果是由一家管理保險的機構（如醫療保險和醫療補助服務中心）掌握，則可能來自許多醫療機構。

So it is not uncommon to see extremely large data sets emerge from the claims data with hundreds of millions of records.

是以，理賠數據中出現上億條記錄的超大數據集的情況並不少見。

So what it lacks in quality, it makes up for in quantity.

是以，它在品質上的不足在數量上得到了彌補。

An insurance company might be interested in analyzing the claims data to study the possibility of fraud, cost drivers in different areas of healthcare, and to see if the quality of care aligns with what they're actually paying out to the healthcare providers.

保險公司可能有興趣分析理賠數據，以研究欺詐的可能性、不同醫療領域的成本驅動因素，以及醫療品質是否與他們實際支付給醫療服務提供者的費用相符。

In other words, are the patients actually getting what the insurers are paying for?

換句話說，病人是否真的得到了保險公司支付的費用？

Hospitals might also be interested in the claims data.

醫院可能也會對報帳數據感興趣。

They might study referral patterns.

他們可能會研究轉診模式。

They might try to improve population health, increase sales, among other things, using the claims data.

他們可能會嘗試利用報帳數據改善人口健康狀況、增加銷售額等。

Next, we have clinical and disease registries.

其次是臨床和疾病登記。

And generally speaking, these are repositories of data that are dedicated to certain diseases.

一般來說，這些都是專門針對某些疾病的數據儲存庫。

So you might have one for stroke patients, another one for cancer patients, another one for patients who had specific surgeries that were performed.

是以，你可能會有一個用於中風病人，另一個用於癌症病人，還有一個用於做過特定手術的病人。

The data is typically collected by a data abstractor who will gather the necessary details from the patient's medical record and plug them into a repository.

數據通常由數據抽取員收集，他將從病人的醫療記錄中收集必要的細節，並將其輸入存儲庫。

The data is often then analyzed by the owners of that registry and compared to similar healthcare organizations across the country.

然後，登記處的所有者通常會對數據進行分析，並與全國類似的醫療機構進行比較。

Hospitals might participate in these registries because it helps them identify costly areas of the care provided.

醫院可能會參與這些登記，因為這有助於他們確定所提供的醫療服務中成本較高的領域。

It helps identify weaknesses in the provision of care.

它有助於找出在提供護理方面的不足之處。

The registry might grant the hospital access to resources that will educate them on the best practices of care.

登記處可為醫院提供資源，使其瞭解最佳護理實踐。

Some of the registries might offer accreditation, which will make the hospital appear more reputable.

有些註冊機構可能會提供認證，這將使醫院看起來更有信譽。

And they can also compare how they're doing to other hospitals.

他們還可以將自己的情況與其他醫院進行比較。

And this last part is really important.

最後一部分非常重要。

Once the data is analyzed, a report containing the results are shared with the healthcare organization and it will show them their strengths and weaknesses compared to similar hospitals and clinics.

數據分析完成後，醫療機構會收到一份包含分析結果的報告，該報告將向醫療機構展示其與同類醫院和診所相比的優勢和劣勢。

Sometimes individual physicians will also be compared to their peers, like how many surgeries and subsequent infection rates were at the hand of Surgeon A versus Surgeon B versus Surgeon C.

有時，醫生個人也會與同行進行比較，比如外科醫生 A 與外科醫生 B、外科醫生 C 的手術數量和隨後的感染率。

There's lots of different registries a hospital or clinic might be a part of and they're typically utilized by analysts, researchers, and people involved in quality improvement efforts to gain insights about their population of interest.

醫院或診所可能會加入許多不同的登記處，這些登記處通常由分析師、研究人員和參與品質改進工作的人員使用，以瞭解他們所關注人群的情況。

So to give you an example, before I was a data analyst, I was a data abstractor for a bunch of different registries.

舉個例子，在我成為數據分析師之前，我曾是許多不同註冊機構的數據抽取員。

The registry that I was tasked with using the most, however, was one called NISQIP, or the National Surgery Quality Improvement Program.

不過，我使用最多的登記冊是一個名為 NISQIP 的登記冊，即 "國家手術品質改進計劃"（National Surgery Quality Improvement Program）。

In this repository, data will be tracked for patients receiving general surgeries like appendectomies, colectomies, hysterectomies.

在這個存儲庫中，將對接受闌尾切除術、結腸切除術、子宮切除術等普通手術的患者的數據進行跟蹤。

I was tasked with determining if the patients had certain medications, if their vital signs crossed a certain threshold at some point, like having an elevated heart rate, breathing rate, body temperature, which could indicate a fever, determining whether the patient had any mortalities or morbidities, also known as M&Ms. Mortalities simply meaning death from the surgery, morbidities being things like pneumonia or surgical site infections.

我的任務是確定病人是否服用了某些藥物，他們的生命體徵是否在某一時刻超過了某個臨界點，比如心率、呼吸頻率、體溫（可能表示發燒）升高，確定病人是否有任何死亡病例或發病病例（也稱為 M&M）。死亡率指的是手術導致的死亡，發病率指的是肺炎或手術部位感染等。

And if the patient had surgical site infections, what was the severity?

如果病人有手術部位感染，嚴重程度如何？

I would go through several patients each day and plug them into a repository where it would then be analyzed by the organization that administered the repository.

我每天都要看幾個病人，然後把他們輸入一個存儲庫，然後由管理存儲庫的機構進行分析。

Then on a quarterly basis, we would get the results back and we would see metrics like an observed to expected ratio that showed how many mortalities or morbidities did we witness relative to what was expected of us.

然後，每季度我們都會得到結果，我們會看到一些指標，比如觀察結果與預期結果的比率，顯示我們目睹的死亡率或發病率與預期結果的比率。

The surgeons would also get to see how many overall SSIs their patients suffered from and would get to see how they compared to their peers.

外科醫生還可以瞭解病人的 SSI 總數量，並與同行進行比較。

Data professionals might be called upon to help automate some of this process, import the results into a database or analyze the results in a dashboard.

數據專業人員可能需要幫助實現部分流程自動化、將結果導入數據庫或在儀表板中分析結果。

The automation of data collection and entry into the registry is not always straightforward, however, because some of that data is really nuanced and requires a human to read through pages and pages of operative notes before they have a good understanding of the complications a patient might have suffered from during the surgery.

然而，數據收集和輸入登記冊的自動化工作並不總是那麼簡單，因為有些數據確實很微妙，需要人工閱讀一頁頁的手術記錄，才能很好地瞭解病人在手術過程中可能出現的併發症。

Some of the registries I've seen throughout my career include surgery registries, cancer registries, infectious disease registries like the National Healthcare Safety Network or NHSN, organ transplants, cardiac registries, stroke registries, among many, many others.

在我的職業生涯中，我所見過的登記處包括外科登記處、癌症登記處、傳染病登記處（如國家醫療安全網絡或 NHSN）、器官移植、心臟登記處、中風登記處等等。

Our final category is external reporting data.

最後一類是外部報告數據。

Given that healthcare is such a complex and heavily regulated industry, there's quite a few external entities that either require hospitals to submit data or are completely optional, yet provide numerous benefits to participation.

鑑於醫療行業是一個複雜且監管嚴格的行業，有許多外部實體或要求醫院提交數據，或完全不要求醫院提交數據，但卻為醫院的參與提供了許多好處。

We can split them out into required reporting and optional reporting.

我們可以將其分為必需報告和可選報告。

For required reporting, let's take hospitals in Washington State as an example.

以華盛頓州的醫院為例，就必須進行報告。

Hospitals are required to submit a list of their adverse events that happened within their hospital to the Washington State Department of Health.

醫院必須向華盛頓州衛生部提交一份在醫院內發生的不良事件清單。

These include things like wrong site surgeries, retained foreign objects during surgery, falls in a hospital that resulted in major injury or death, among many other things.

其中包括錯誤的手術部位、手術過程中的異物殘留、在醫院摔倒導致重大傷害或死亡等等。

In addition to state government, there's also data that must be submitted to the federal government.

除州政府外，還必須向聯邦政府提交數據。

I already mentioned NHSN earlier, but this is a disease registry owned by the Centers for Disease Control, or CDC, and it tracks hospital-acquired infections like catheter-associated urinary tract infections, central line-associated bloodstream infections, C. diff, antimicrobial stewardship, and lots of other things.

我之前已經提到過 NHSN，但這是疾病控制中心（CDC）擁有的一個疾病登記系統，它跟蹤醫院獲得性感染，如導管相關性尿路感染、中央管路相關性血流感染、C. diff、抗菌藥物管理等。

One of the reasons this is required is because many hospitals get money from the government through Medicare.

要求這樣做的原因之一是許多醫院通過醫療保險從政府獲得資金。

If a hospital slips and does a half-assed job of keeping infections in the hospital under control, they could lose millions of dollars.

如果醫院在控制院內感染方面稍有不慎，就會損失數百萬美元。

HAIs are just one type of data that hospitals have to submit to the federal government, though.

不過，HAIs 只是醫院必須向聯邦政府提交的一種數據。

There's other things like mortality rates for various conditions, survey data that measures patient satisfaction.

還有其他一些東西，比如各種疾病的死亡率、衡量病人滿意度的調查數據。

Specific data has to be submitted to the Center for Medicare and Medicaid Services.

具體數據必須提交給醫療保險和醫療補助服務中心。

They do this to reward the hospitals that exceed expectations and penalize those that don't meet expectations.

他們這樣做是為了獎勵那些超出預期的醫院，懲罰那些沒有達到預期的醫院。

Now for the optional reporting side of things, many hospitals choose to share a good portion of their data with other organizations.

在可選報告方面，許多醫院選擇與其他機構共享大部分數據。

For example, hospitals might choose to share their data with entities called hospital associations that will help facilitate quality improvement efforts for the hospital and provide them with averages and peer hospital comparisons within the state.

例如，醫院可以選擇與稱為醫院協會的實體共享數據，這將有助於促進醫院的品質改進工作，併為醫院提供平均值和州內同級醫院的比較。

Hospitals that provide a certain type of care, for example, children's hospitals, have special exclusive memberships with organizations like the Children's Hospital Association.

提供某類醫療服務的醫院，例如兒童醫院，都有兒童醫院協會等組織的特殊專屬會員資格。

This gets into one of the main perks of optional reporting.

這就是可選報告的主要好處之一。

Hospitals will often share data with many different organizations so that they can do benchmarking.

醫院通常會與許多不同的機構共享數據，以便進行基準測試。

Benchmarking is just a fancy way of saying, how well do we compare to hospitals similar to ours?

標杆管理只是一種花哨的說法，即與同類醫院相比，我們的情況如何？

By sharing their data with a central organization, that organization is able to pool the collective results from all of the hospitals it collects data from and come up with various statistics and then they can publish the results so that all of the participants can see if they are above the average or below the average.

通過與中央機構共享數據，該機構能夠彙集其收集數據的所有醫院的集體結果，並得出各種統計數據，然後公佈結果，讓所有參與者都能看到自己是高於平均水平還是低於平均水平。

Some of these organizations provide a huge amount of visibility and impact the reputation of the hospital.

其中一些組織提供了巨大的知名度，並影響著醫院的聲譽。

For example, US News and World Report is a program where hospitals submit large volumes of data and these large volumes of data are curated into specific metrics like how many cancer surgeries did we do?

例如，《美國新聞與世界報道》是一個醫院提交大量數據的項目，這些大量數據會被整理成具體的指標，比如我們做了多少例癌症手術？

How many patients were evaluated for epilepsy?

有多少患者接受了癲癇評估？

Once all that data is collected from all the participating hospitals, US News World Report then awards the hospital with a ranking out of all the hospitals in its cohort.

一旦從所有參與醫院收集到所有數據，《美國新聞世界報道》就會在同類所有醫院中對醫院進行排名。

And by cohort I mean like Best Hospitals in the Nation or Best Children's Hospital in the Nation.

我說的 "同類 "是指 "全美最佳醫院 "或 "全美最佳兒童醫院"。

The ranking will often be based off of the collective performance of the various service lines that the hospital has like cardiology, neurology, surgery, nephrology, cancer care.

排名通常基於醫院各服務項目的綜合表現，如心臟科、神經內科、外科、腎內科、癌症治療等。

For programs like these, they require a lot of planning and data wrangling and it can be a very time consuming process to prepare for.

像這樣的計劃需要大量的規劃和數據處理，準備過程可能非常耗時。

The tradeoff though is that hospitals with a really good reputation can attract more patients due to their high score.

不過，這樣做的好處是，聲譽真的很好的醫院可以因其高分而吸引更多病人。

They can attract more skilled physicians.

它們可以吸引更多技術熟練的醫生。

It can also give a hospital more leverage when negotiating and dealing with health insurance companies which means more money.

在與醫療保險公司談判和打交道時，它還能為醫院提供更多的籌碼，這意味著更多的資金。

Now believe it or not, we've barely even scratched the surface of all of the data that exists within healthcare organizations but that should be about 80% of the data that you might expect to see.

信不信由你，我們甚至還沒有觸及醫療機構內部所有數據的表面，但這應該是你可能期望看到的數據的 80%。

There's so much more but hopefully that gives you a general idea of the major types of data that you see in a healthcare system.

還有很多，但希望這能讓你對醫療系統中的主要數據類型有一個大致的瞭解。

If you want to learn more about what it's like to be a data analyst, check out this video next.

如果您想了解更多有關數據分析師的資訊，請觀看接下來的視頻。

Thank you so much for watching and I'll see you in another video.

非常感謝您的收看，我們下期視頻再見。