Tag

data

Making Types Work for You

From Street Coder by Sedat Kapanoǧlu

This article discusses the importance of using data types in programming for writing and maintaining code bases.

Learn to Run Data Infrastructure on Azure

From Azure Data Engineering by Vlad Riscutia

Implementing a MapReduce Framework Using Python Threads

From High-Performance Python for Data Analytics by Tiago Rodrigues Antao

In this article we will start to explore Python’s framework for concurrency – the first step in developing parallel applications.

The Practical Guide to Data Leadership

From Become a Leader in Data Science by Jike Chong and Yue Cathy Chang

The Layers of a Cloud Data Platform

From Designing Cloud Data Platforms by Danil Zburivsky and Lynda Partner

In this article, we’ll layer some of the critical and more advanced functionality needed for most data platforms today. Without this added layer of sophistication your data platform would work but it wouldn’t scale easily, nor would it meet the growing data velocity challenges. It would also be limited in terms of the types of data consumers (people and systems who consume the data from the platform) it supports, as they’re also growing in both numbers and variety.

Getting started with graphs

From R in Action, Third Edition by Robert Kabacoff

This article dicusses graphs and graphic using the ggplot2 package

Techniques for handling modern big data applications

From Algorithms and Data Structures for Massive Datasets by Dzejla Medjedovic, Emin Tahirovic, and Ines Dedovic

All About Bloom Filters

From Algorithms and Data Structures for Massive Datasets by Dzejla Medjedovic, Emin Tahirovic, and Ines Dedovic

This article covers:

·  Learning what Bloom filters are, why and when they are useful

·  Understanding how Bloom filters work

·  Configuring a Bloom filter in a practical setting

·  Exploring the interplay between Bloom filter parameters

Introducing Edge Computing

From Making Sense of Edge Computing by Cody Bumgardner

Conceptually, edge computing is concerned with when it’s best to migrate computational functionally toward source of data and when it is best to move the data itself. This abstract concept of function versus data migration drives not only the fundamental motivations of edge computing, but also the broader field of distributed systems. The act of distributing processes makes even the simplest tasks more complicated.

Transparent and understandable AI systems

From Interpretable AI by Ajay Thampi

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