4 ways to add cloud and data skills to your portfolio

More than seven years ago Marc Andreessen penned a now famous essay in the Wall Street Journal headlined Why Software Is Eating The World (paywalled, sorry.) Most will agree he was right.

In 2016, Andreessen with associates Ben Horowitz, Scott Kupor, and Sonal Chokshi put out a podcast Software Programs The World. And while the soothsayers have yet to say it, Data Runs The World. Consider the 2016 elections, the widespread calls for data privacy laws and the five crazy 1000 point intra-day swings of the stock market in 2018. It is beginning to seem as if training in data will be required just to be a responsible citizen.

As we approach the fourth quarter of 2020 , it’s especially important for anyone who works with data to update their career portfolios with data skills. Even if they did so last year. Technology stacks are constantly changing and being a master at something that isn’t used anymore could put you last in line when it comes to working on important and interesting projects. Not only that, but expertise in data engineering and data analytics, for example, will make you one of the most highly sought after tech professionals in the industry. This according to burningglass, the world’s largest provider of labor market data.

This doesn’t mean that you have to spend a big bucks and take six weeks off from work to skill-up. Here are a few ways to add data skills to your portfolio for free.

Snowflake, the hot data management solutions platform provider for analytics, offers free training via its Data Cloud Academy. There are three instructional tracks:

Data-Driven Decision-Making
Govern and Manage Data in the Era of the Data Cloud
Build Businesses and Products Around Data

Instructors range from Snowflake’s marketing team, data scientist Steve Griswold from US Foods, product marketer, Conor Knowles from Tableau, Rupesh Dandekar, Senior Manager | Analytics and Information Management from Deloitte, Avinash Deshpande, Head of Architecture, Data Solutions, ML & AILogitech, and Susan Wilson, VP Data Governance and Privacy Segment Leader at Informatica.

You can register for the free training here.

Amazon offers 19 introductory labs via qwikLabs.com. They are geared toward working in the Amazon ecosystem. Courses in Amazon Machine Learning, Amazon DynamoDB, Amazon RedShift and others might be of interest.

How does Uber figure out whether it should offer $4.99 or $6.99 for the next ride? It uses Presto, a high performance, distributed SQL query engine for big data. Its architecture allows users to query a variety of data sources such as Hadoop, AWS S3, Alluxio, MySQL, Cassandra, Kafka, and MongoDB. One can even query data from multiple data sources within a single query. Sounds marvelous, right?

Well it is, but Presto was difficult to use until now. Today, startup Ahana introduced its new Presto-as-a-Service offering designed to simplify the deployment, management and integration of Presto, an open source distributed SQL query engine, with data catalogs, databases and data lakes on Amazon Web Services (AWS). Ahana Cloud for Presto is the only easy-to-use, cloud-native managed service for Presto, and is deployed within the user’s AWS account, giving customers complete control and visibility of clusters and their data.

You can learn more about Presto here and get early access to Ahana Cloud for Presto here.

Google offers temporary credentials for Google Cloud Platform. Once you have them you can take anything from short, 30-minute labs to multi-day courses offered from beginner to expert levels. There’s a 9h 40m BigQuery for Data Analysis Quest, a 7hr 56m Data Engineering Quest, an 8 hr Data Science on Google Cloud Platform: Data, ML, AI course and more.

Narrating the trek to the digital economy from ActBrilliant.com

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