O'Reilly on Data

SEPTEMBER 15, 2021

When we looked at the most popular programming languages for data and AI practitioners, we didn’t see any surprises: Python was dominant (61%), followed by SQL (54%), JavaScript (32%), HTML (29%), Bash (29%), Java (24%), and R (20%). The tools category includes tools for building and maintaining data pipelines, like Kafka.

Machine Learning 363

Machine Learning Statistics Reporting Consulting 363

Smart Data Collective

OCTOBER 26, 2023

Subjects such as incident response, risk management, access control, and cryptography fall under this category. Learning and using scripting languages like PowerShell and Bash and programming languages like Python, Java, and C++ are also helpful.

Technology 92

Technology Risk Measurement IoT 92

Insight

AUGUST 12, 2019

These categories are listed in order of importance: Linux Fundamentals Data Structures and Algorithms System Design Parsing DevOps Tools It’s good to develop a wide, shallow base of knowledge first, so load balance across topics in a round-robin fashion at first. It doesn’t look flashy, but the Advanced Bash Scripting Guide is a goldmine.

Software 65

Software Data-driven Testing Interactive 65

AWS Big Data

JUNE 1, 2023

The data stream pipeline can involve multiple models for different purposes, such as classifying uploaded images into ecommerce categories of electronics, toys, fashion, and so on. Clean up To clean up the CloudFormation script you launched, complete the following steps: Empty the source bucket you specified in the bash script.

Deep Learning 62

Deep Learning Data Analytics Analytics Machine Learning 62

Cloudera

MARCH 9, 2021

To create all required typedef for the entire data pipeline you can also use the following bash script ( create_typedef.sh ): ATLAS_USER="admin". classificationDefs": [. {. "category": "CLASSIFICATION", "name": "xyz", "typeVersion": "1.0", "attributeDefs": [], "superTypes": ["APPLICATION"]. }. ]. }'.

Data Governance 94

Data Governance Metadata Enterprise Data Processing 94

Depict Data Studio

MARCH 3, 2020

You can view more examples of color-coding by category here. It’s SO unhelpful to bash pie charts without offering better alternatives, which is where all my pie chart makeover blog posts come in. And everything in that chapter is the same color: the headings, the graphs, the call-out boxes, and even the bullet points.

Reporting 59

Reporting Visualization Software IT 59