Snowflake tutorial curriculum

Snowflake is one of many technologies that data scientists can use to collect, analyze, and organize large amounts of data. For learners new to the platform, a Snowflake tutorial can introduce its different uses and applications. A Snowflake course or tutorial can cover:

• Data loading methods

• Snowflake SQL queries

• Snowflake schema design and data modeling

• Querying in Snowflake

• Snowflake security and access control mechanisms

As learners become more familiar with the platform, them may move on to learning about: 

• Data visualization and cloud technologies

• Process automation with Snowflake integrations

• Data-to-decisions pipelines connected to Snowflake

• Predictive modeling for business analytics with Snowflake integration

Learn about Snowflake to supplement your knowledge of data science. edX offers a variety of educational opportunities for learners interested in these topics, as well as a host of other disciplines. A boot camp can provide flexible, hands-on learning for those who want to upskill quickly, while executive education courses are designed for busy professionals. You can also pursue a more comprehensive curriculum in a bachelor’s degree program or, for more advanced learners, a master’s degree program. Find the right learning path for you.

Explore Snowflake jobs

There are a variety of jobs that can benefit from knowledge of Snowflake, including:

• Data scientist: Utilizes analytical expertise to work with statistics, data sets, and machine learning algorithms to extract meaningful insights.^{Footnote 2}

• Data quality analyst: Ensures the accuracy, integrity, and reliability of data within an organization; uses a series of tools to validate and clean large volumes of data, which can include working in test environments and keeping detailed documentation.^{Footnote 3}

• Content marketer: Optimizes digital marketing campaigns using data on campaign performance, audience demographics, user engagement, and more.^{Footnote 4}

• BizOps engineer: Bridges the gap between business strategy and operational execution with an increasing reliance on data-driven intelligence; accesses data that measure operational efficiency and makes recommendations.^{Footnote 5}

• Snowflake AWS developer: Designs, develops, and maintains technology solutions built around the platform. This includes architecture, integration, SQL development, performance tuning, and more.^{Footnote 6}

• ELT developer: Designs and implements data integrations to make Snowflake or similar cloud-based platforms feed data into operational management platforms. ELT stands for extract, load, and transform and is a common acronym in the world of integration development.^{Footnote 7}

• System administrator: Maintains a platform like Snowflake within an organization and works directly with system configuration, like managing access controls and enforcing security policies; monitors and optimizes system performance, handles capacity planning, and manages backup and recovery systems.^{Footnote 8}

Each of these roles will have different education and skills requirements. For example, you may be able to build relevant skills in a data analytics boot camp. However, some employers may seek candidates with a degree in data science, depending on the role. Before deciding on a specific learning path, research the positions you hope to pursue and align your coursework with your career goals.

How to use Snowflake in your career

Technical familiarity with Snowflake is useful for anyone who works directly with data, in fields such as data analysis or business intelligence. The ability to access and use data without relying on a technical specialist to retrieve the data can make their work more efficient. Additionally, data engineers can benefit from ELT and SQL-based technical skills to streamline their workflows. Other roles in data governance, marketing, and BizOps can benefit from Snowflake skills. 

For example, a data scientist can utilize Snowflake to pull in semi-structured data from various sources, analyze it, and use that data to train models that will provide business intelligence insights. Snowflake supports integrations with many machine learning models, which makes it a useful technology for AI-driven data solutions that make business management more effective.

Start learning how to use Snowflake and building the skills you need for your next career move. Embark on your learning journey today with edX.