Hashmap Engineering & Technology: Our Top 10 Most Popular Articles in 2020
In 2020, we published over fifty blog posts, over fifty Hashmap on Tap podcast episodes, over twenty videos, and built four open-source utilities. That’s a whole lot of content. So to help you prepare for next year and catch-up on the best Hashmap blog posts we had to offer, we thought it would be interesting (and fun) to take a look back at our most popular stories Hashmappers wrote in 2020.
To all Hashmap customers, partners, and the broader community that viewed, read, and are fans of our stories, we want to say THANK YOU!
Also, a very special thank you to all of the Hashmap writers that contributed content, ideas, stories, and significant time to make the Hashmap blog a great resource for the community!
So here they are in order, as ranked by Medium reads, our top ten in 2020!
#1 The Hitchhiker’s Guide to Timestamps in Snowflake
If you’re considering storing timestamp data in Snowflake, you’ll want to keep reading to save yourself from the heartache of a misused DATEADD or an automatic UTC conversion thanks to your current session timezone. . .
#2 Three Best Practices for On-Prem to Snowflake
I want to share three best practices for modernizing, migrating, and getting data to the cloud and Snowflake. Snowflake has some uniquenesses that set it apart from anything else in the market today (and definitely from on-prem solutions). For us, three aspects really stand out. . .
#3 Automate Code Deployment with AWS EC2 Build Agents for your Azure DevOps Pipelines
Two households, both alike in dignity, combine to create the hybrid cloud CI/CD pipeline of your dreams. To make sure your builds have unlimited runway, this tutorial shows how to use Azure Pipelines to orchestrate builds that run on AWS EC2 Virtual Machines instances. This approach. . .
#4 #Tech in 5 — Snowflake & Dask
Why Snowflake and Dask could revolutionize data discovery for data engineers and data scientists alike by providing a fast, scalable, purely Python-based stack. . .
#5 Quickly Visualize Snowflake’s Roles, Grants, & Privileges
How I Used Dagre-d3 to Go Beyond Table Views. In this blog post, I’m going to walk you through a new and improved approach and demonstrate a visualization prototype code sample for understanding role hierarchy and relationships between roles and grants. . .
#6 Snowflake Solution Anti-Patterns: Spark is My Hammer
Is Spark a long-term solution? The question comes down to how we will be doing transformational logic for Snowflake and whether Spark is an appropriate tool. So here are the common reasons Spark is utilized. . .
#7 Schema Unification with Snowflake: A Design Made Simpler
If only there were a tool, a system out there that empowers data engineers to store data with all of its raw pieces of information intact and yet combine them without too much pre-processing/modeling effort. Enter, Snowflake Cloud Data Warehouse and its native support for. . .
#8 Moving On-Prem Oracle Databases to Snowflake
A simple way to export from Oracle and import to Snowflake. How do you export your data into a format that Snowflake can ingest, and how can you import this data into Snowflake as an initial load? I’ll try to help you avoid pitfalls along the way by showing you. . .
#9 Data Sync to Snowflake Using Confluent Kafka Connect
Moving On-Prem Oracle Databases to Snowflake in Azure with Kafka Connect. While there are many blogs that cover this topic, they don’t provide scenarios that deviate from the normal happy path and demonstrate how to overcome the deviations. I will go over some of the hurdles we observed during the engagement and. . .
#10 5 Steps to Converting Python Jobs to PySpark
In this blog post, I am going to list out the steps I followed while converting a Python script to a PySpark job. I have put together best practices and recommendations to improve Spark job performance. The steps outlined in this blog post will assist with a smoother and more organized transition from pandas to PySpark using Apache Arrow or Koalas. . .
We hope you enjoyed a look back at top stories from 2020 and we look forward to working together and providing fresh insights on new topics in 2021 as the Data, Cloud, IoT, and AI/ML technology landscape continues to shift and change.
Let us know what you want to hear about and here’s to a great year ahead!
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