Amazon Digital Services LLC, 2016. — 53 p. — ASIN: B01D42UBP4More and more companies these days are learning that they need to make DATA-DRIVEN decisions.
With big data and data science on the rise, we have more data than we know what to do with.
One of the basic languages of data analytics is SQL, which is used for many popular databases including MySQL, Postgres, Microsoft SQL Server, Oracle, and even big data solutions like Hive and Cassandra.I’m going to let you in on a little secret. Most high-level marketers and product managers at big tech companies know how to manipulate data to gain important insights. No longer do you have to wait around the entire day for some software engineer to answer your questions - now you can find the answers directly, by yourself, using SQL!
Your existing solutions are inefficient
Are you tired of depending on crufty “analytics” software? Do you have to ask an engineer to help you whenever you have a question about the data?
This is not ideal and won’t help you do your job efficiently.
SQL, short for “structured query language”, is a language that can be used for all kinds of databases - from the tiny databases stored in your iPhone, to large big data databases that span multiple continents.
Engineers have done a great job of creating these different types of complex data stores, while still allowing you to use the same language, more or less, for all of them.
What does that mean for you?
It means as long as you know SQL, you can take advantage of ALL of this software, and gain insights into this data, no matter what kind of database it is stored in, as long as it supports SQL.
You can ask questions like:
How many people are falling into each stage of the sales funnel?
What is my year over year profit?
Are there any differences in the demographics between the people who are buying product X and product Y?
What is our most profitable month?
What are the seasonal trends in our industry?
I’m an engineer, so I probably haven’t even thought of all the questions you’ve already had for years! But I guarantee you, knowing SQL will help you answer these questions.

On various teams I’ve worked on in the tech world - I’ve noticed that marketing people and product managers have SQL skills and sometimes even coding skills! So if you are looking to not only make your day more productive, but make yourself more marketable to employers and catch up to the other go-getters in your field - then you should most definitely learn SQL.

亚马逊数字服务有限公司，2016年。- 53页 - ASIN: B01D42UBP4如今，越来越多的公司了解到，他们需要做出数据驱动的决策。

随着大数据和数据科学的兴起，我们拥有的数据比我们知道的要多。

数据分析的基本语言之一是SQL，它被用于许多流行的数据库，包括MySQL、Postgres、Microsoft SQL Server、Oracle，甚至像Hive和Cassandra这样的大数据解决方案。我将告诉你一个小秘密。大科技公司的大多数高级营销人员和产品经理都知道如何操纵数据以获得重要的洞察力。你不再需要整天等待一些软件工程师来回答你的问题--现在你可以直接找到答案，由你自己用SQL来解决！你可以在你的网站上找到这些问题。

你现有的解决方案是低效的

你是否已经厌倦了依赖笨重的 "分析 "软件？每当你有关于数据的问题时，你都要请工程师来帮助你吗？

这并不理想，不能帮助你有效地完成工作。

SQL是 "结构化查询语言 "的简称，是一种可用于各种数据库的语言--从存储在你的iPhone中的微小数据库，到横跨多个大陆的大型大数据数据库。

工程师们在创建这些不同类型的复杂数据存储方面做得很好，同时仍然允许你使用相同的语言，或多或少，用于所有这些数据。

这对你意味着什么？

这意味着只要你知道SQL，你就可以利用所有这些软件，并获得对这些数据的洞察力，不管它存储在什么样的数据库中，只要它支持SQL。

你可以问这样的问题。

有多少人落入销售漏斗的每个阶段？

我每年的利润是多少？

购买产品X和产品Y的人在人口统计学上有什么不同吗？

我们最赚钱的月份是什么？

我们行业的季节性趋势是什么？

我是一个工程师，所以我可能连你多年来已经想到的所有问题都没有想到! 但我向你保证，了解SQL将帮助你回答这些问题。

在我在科技界工作过的各种团队中--我注意到，营销人员和产品经理都有SQL技能，有时甚至还有编码技能！这也是我的一个优势。因此，如果你希望不仅使你的工作更有效率，而且使你自己对雇主更有吸引力，并赶上你所在领域的其他有能力的人--那么你绝对应该学习SQL。