api數據庫管理

Data scientists regularly use APIs (Application Programming Interfaces) to implement advanced functionalities without having to build things from the ground up, import data from external sources, expose data for users to consume, or achieve other objectives.

數據科學家經常使用API??(應用程序編程接口)來實現高級功能，而無需從頭開始構建事物，從外部源導入數據， 將數據公開給用戶使用或實現其他目標。

For example, if you intend to create your own classifier that categorizes the genre of a piece of music, you can use the Spotify API to do that.

例如，如果您打算創建自己的分類器來對音樂的流派進行分類，則可以使用Spotify API來實現。

You’ll be able to tap into the massive data that Spotify has and build the classifier fast, without having to start from scratch. In such cases, APIs offer the right solution to your data science project.

您將能夠利用Spotify擁有的海量數據并快速構建分類器，而無需從頭開始。 在這種情況下，API為您的數據科學項目提供了正確的解決方案。

And, to make the most of APIs, there is a need to enforce API management. With an API management platform, such as the Rakuten RapidAPI Enterprise Hub, you can abstract most of the day-to-day administrative pain points of creating or consuming APIs and realize increased productivity.

并且，為了充分利用API，需要實施API管理。 借助Rakuten RapidAPI Enterprise Hub等API管理平臺，您可以抽象出創建或使用API??的大部分日常管理難題 ，并提高生產率。

These solutions assist you in designing, implementing, monitoring, securing, analyzing, managing, and growing your API program.

這些解決方案可幫助您設計，實施，監視，保護，分析，管理和擴展API程序。

In this article, I’m going to talk about how an API management platform can help in enhancing your data science projects.

在本文中，我將討論API管理平臺如何幫助您增強數據科學項目。

1.提供集中的可見性 (1. Provides centralized visibility)

An API management tool will provide you with centralized visibility into the performance of your internal APIs and external API subscriptions. As you use more APIs in your data science projects, it becomes difficult to keep track of them.

API管理工具將使您可以集中查看內部API和外部API訂閱的性能。 當您在數據科學項目中使用更多API時，很難跟蹤它們。

In fact, according to a 2017 study, an average company uses more than 300 different APIs. With these many APIs to take care of, simplifying their tracking process is required to optimize their value and deliverability.

實際上，根據2017年的一項研究 ，一個普通的公司使用300多種不同的API。 有了這些許多API，就需要簡化其跟蹤過程以優化其價值和可交付性。

Otherwise, it can be difficult to assess and improve their performance, enhance the developer experience, or make informed decisions.

否則，可能難以評估和改善其性能，增強開發人員的經驗或做出明智的決定。

An API management solution will give you the enhanced visibility and control you need to know what is happening with your APIs.

API管理解決方案將為您提供增強的可見性和控制力，您需要了解API所發生的情況。

With a single central location to manage your data science APIs, you can get rid of redundant APIs, identify performance inconsistencies, and ease the orchestration of the different moving parts of your APIs.

通過一個中心位置來管理數據科學API，您可以擺脫冗余的API，識別性能不一致的地方，并簡化API不同移動部分的編排。

2.改善API治理 (2. Improves API governance)

API governance refers to the practice of establishing various policies that control the use of an API product.

API治理是指建立控制API產品使用的各種策略的實踐。

It involves a wide range of management, administration, visibility, monitoring, and other measures that streamline and govern the adoption of APIs.

它涉及廣泛的管理，管理，可見性，監視和其他簡化和控制API采用的措施。

As a data scientist, having an API management platform will let you outline the terms and conditions that make your APIs accessible by different personas within and outside your enterprise.

作為數據科學家，擁有API管理平臺可讓您概述使企業內部和外部的不同角色可以訪問API的條款和條件。

It’s what you need to implement access management and safeguard against unauthorized use, undertake audit trails to discover abnormal usage trends, and blacklist or whitelist APIs.

這是實現訪問管理，防止未經授權使用，進行審計跟蹤以發現異常使用趨勢以及黑名單或白名單API所需要的。

Furthermore, managing your APIs makes it easy to analyze and monitor their performance.

此外，通過管理API，可以輕松分析和監視其性能。

Most of these solutions come with intuitive dashboards that allow you to get quick insights across all APIs used by your team. This way, you can evaluate and maintain the health of your APIs.

這些解決方案中的大多數都帶有直觀的儀表板，可讓您快速了解團隊使用的所有API。 這樣，您可以評估和維護API的運行狀況。

You can also use such a platform to collate APIs according to their different functions. For example, if you have different APIs that pull data sets for data visualization, you can group them and monitor their performance easily.

您還可以使用這樣的平臺根據API的不同功能來整理它們。 例如，如果您有不同的API提取數據集以進行數據可視化 ，則可以將它們分組并輕松監視其性能。

Also, even if there are multiple versions of an API, such a platform will allow you to track and govern the various versions effortlessly.

此外，即使API有多個版本，該平臺也可以使您輕松跟蹤和管理各種版本。

3.增強API發現 (3. Enhances API discovery)

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Most API management platforms come with a built-in developer portal that allows users to find APIs, learn how to consume them, test them out interactively, and ultimately register to get API keys.

大多數API管理平臺都帶有一個內置的開發人員門戶，該門戶允許用戶查找API，學習如何使用它們，進行交互測試以及最終注冊以獲得API密鑰。

These portals act as a repository of everything pertaining to using the given APIs — from providing documentation, code snippets, tools, and other helper resources.

這些門戶充當與使用給定API有關的所有內容的存儲庫-從提供文檔 ，代碼段，工具和其他幫助程序資源開始。

If you can use the portal to search for public and internal APIs, sign up to them, and incorporate them into your applications, you can greatly improve the capabilities of your data science projects.

如果您可以使用門戶網站搜索公共API和內部API，對其進行注冊并將它們合并到您的應用程序中，則可以極大地提高數據科學項目的功能。

Instead of having to create functionalities from scratch, you can use an API management solution to discover new APIs and save your development time, costs, and efforts. This will allow you to concentrate on improving the offerings of your core product.

無需從頭開始創建功能，您可以使用API??管理解決方案來發現新的API，并節省開發時間，成本和工作量。 這將使您可以專注于改進核心產品。

More so, leveraging APIs can lead to several improvements across most crucial elements of your data science projects. According to a recent study, users who adopted APIs realized a significant increase in productivity (at 59%), direct revenues (at 43%), and innovation (at 51%).

更重要的是，利用API可以在您的數據科學項目的最關鍵要素上帶來多項改進。 根據最近的一項研究 ，采用API的用戶實現了生產率(59％)，直接收入(43％)和創新(51％)的顯著提高。

Therefore, the ability to find and connect to APIs is an important feature you can take advantage of to increase the efficiency of your projects.

因此，查找并連接到API的能力是您可以利用的一項重要功能，可以提高項目的效率。

4.鞏固API安全性 (4. Solidifies API security)

When using APIs in your data science applications, security should be an important consideration.

在數據科學應用程序中使用API??時，安全性應該是一個重要的考慮因素。

Currently, with the increased utilization of APIs, attackers are shifting their focus from the traditional targets to a new area that hasn’t been extensively exploited yet: application programming interfaces.

當前，隨著API利用率的提高，攻擊者將重點從傳統目標轉移到了尚未被廣泛利用的新領域：應用程序編程接口。

APIs are highly susceptible to attacks because they expose the underlying enactment of a computing technique.

API非常容易受到攻擊，因為它們暴露了計算技術的基本實現。

Since they provide programmatic access to data and services, this also enlarges the attack surface area — unlike other user-facing applications.

因為它們提供對數據和服務的編程訪問，所以這也擴大了攻擊的范圍-與其他面向用戶的應用程序不同。

According to a recent report, the number of API vulnerabilities has been rising tremendously year-over-year, increasing by about 154% from 2015 to 2018.

根據最近的一份報告 ，API漏洞的數量同比激增，從2015年到2018年增加了約154％。

By managing APIs, you can enforce their security and realize the value you initially envisioned with your data science projects.

通過管理API，您可以加強其安全性并實現您最初在數據科學項目中設想的價值。

A management platform can help you to maximize your API’s security from various types of attacks, such as man-in-the-middle, denial of service (DoS), injection, or social engineering attacks.

管理平臺可以幫助您從各種類型的攻擊(例如中間人攻擊，拒絕服務(DoS)，注入或社會工程攻擊)中最大化API的安全性 。

Besides authenticating and authorizing access, an API management tool can assist in setting up various security measures for your APIs.

除了對訪問進行身份驗證和授權外，API管理工具還可以幫助您為API設置各種安全措施。

These include configuring the OAuth token authorizing system, instituting policies to block bad actors, revoking compromised APIs, implementing API key rotation, applying quotas and rate limiting, and setting permissions for accessing APIs.

這些措施包括配置OAuth令牌授權系統，制定策略以阻止不良行為者，撤銷受侵害的API，實施API密鑰輪換，應用配額和速率限制以及設置訪問API的權限。

Also, as earlier mentioned, such a platform will increase the visibility into your APIs. This heightened visibility lets you analyze the API activities against normal usage patterns, discover unauthorized intrusions based on strange behaviors, and identify threats as early as possible before the extent of damage is amplified.

另外，如前所述，這樣的平臺將增加對API的可見性。 這種增強的可見性使您可以對照正常使用模式分析API活動，基于奇怪的行為發現未經授權的入侵，并在損害程度擴大之前盡早識別威脅。

5.啟用API貨幣化 (5. Enables API monetization)

API monetization, just as the name suggests, refers to the process of earning revenues from your APIs. Monetization allows API providers to grow their pursuits and discover new opportunities with developers, partners, and customers.

顧名思義，API貨幣化是指從您的API中獲得收入的過程。 貨幣化使API提供者可以不斷發展追求，并與開發人員，合作伙伴和客戶一起發現新的機會。

Depending on your objectives, there are three main monetization options you can pursue with your API program: providing it for free, the consumer pays, or consumer gets paid.

根據您的目標，您可以使用API??程序進行三種主要的貨幣化選擇：免費提供，消費者付費或消費者付費。

For example, if you have created an algorithm that performs sentiment analysis, you can expose it as an API and allow other developers to use it to find the opinion expressed in documents or articles.

例如，如果您創建了一種執行情感分析的算法，則可以將其公開為API，并允許其他開發人員使用它來查找文檔或文章中表達的觀點。

And to generate some money from the use of your sentiment analysis API, you can monetize it by charging other data scientists for using it.

為了通過使用情緒分析API來賺錢，您可以向其他數據科學家收取使用費，從而從中獲利。

Most API management solutions offer an easy way to monetize and unlock value from your API products.

大多數API管理解決方案都提供了一種簡便的方法來從您的API產品中獲利和解鎖價值。

These platforms will provide you with a centralized payment center for your APIs, the ability to implement subscription plans, billing capabilities, and more.

這些平臺將為您提供API的集中式支付中心，實施訂閱計劃的能力，計費功能等等。

結論 (Conclusion)

APIs are widely used in data science projects. However, ad hoc API adoption often leads to performance discrepancies, security issues, and reduced productivity.

API已廣泛用于數據科學項目中。 但是，臨時采用API通常會導致性能差異，安全性問題和生產率下降。

An API management plan provides a single source of truth to bring unity, cohesion, and versatility to your APIs.

API管理計劃提供了一個真實的來源，可為您的API帶來統一性，凝聚力和多功能性。

With a platform to manage and control your APIs, you can optimize their value and make the most of your data science projects.

借助用于管理和控制API的平臺，您可以優化其價值并充分利用您的數據科學項目。

So, are you using (or planning to use) a tool for the management of APIs?

那么，您是否正在使用(或計劃使用)用于API管理的工具？

Or, do you have any comments or questions?

或者，您有任何意見或問題嗎？

Please post them below.

請在下面發布它們。

翻譯自: https://towardsdatascience.com/api-management-platform-data-science-projects-43120558a000

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