Altexsoft

JUNE 25, 2019

If we look at the hierarchy of needs in data science implementations, we’ll see that the next step after gathering your data for analysis is data engineering. This discipline is not to be underestimated, as it enables effective data storing and reliable data flow while taking charge of the infrastructure.

Data Engineering 106

Data Engineering Engineering Data Artificial Inteligence 106

Kentik

APRIL 11, 2016

Developed as a model for “processing and generating large data sets,” MapReduce was built around the core idea of using a map function to process a key/value pair into a set of intermediate key/value pairs, and then a reduce function to merge all intermediate values associated with a given intermediate key.

Big Data 40

Big Data Analytics Network Architecture 40

Altexsoft

JULY 29, 2022

Apache Hadoop is an open-source Java-based framework that relies on parallel processing and distributed storage for analyzing massive datasets. Developed in 2006 by Doug Cutting and Mike Cafarella to run the web crawler Apache Nutch, it has become a standard for Big Data analytics. What is Hadoop? Cost efficiency.

Big Data 59

Big Data Data Google Cloud Storage 59

Altexsoft

JANUARY 22, 2020

As a result, it became possible to provide real-time analytics by processing streamed data. Please note: this topic requires some general understanding of analytics and data engineering, so we suggest you read the following articles if you’re new to the topic: Data engineering overview. Stream processing.

Analytics 20

Analytics Data IoT Analysis 20

Xebia

JANUARY 9, 2024

Let’s imagine we are running dbt as a container within a cloud run job (a cloud-native container runtime within Google Cloud). Every morning when all the raw source data is ingested, we spin up a container via a trigger to do our daily data transformation workload using dbt.

Testing 130

Testing Data Open Source Google Cloud 130

O'Reilly Media - Ideas

JANUARY 25, 2024

Our own theory is that it’s a reaction to GPT models leaking proprietary code and abusing open source licenses; that could cause programmers to be wary of public code repositories. This change is apparently not an error in the data. If you want to run an open source language model on your laptop, try llamafile.)

Trends 116

Trends Technical Review Technology Artificial Inteligence 116

Altexsoft

APRIL 16, 2021

An overview of data warehouse types. Optionally, you may study some basic terminology on data engineering or watch our short video on the topic: What is data engineering. What is data pipeline. This could be a transactional database or any other storage we take data from. Data extraction.

Analytics 98

Analytics Analysis Storage Business Intelligence 98

Altexsoft

APRIL 26, 2022

The data journey from different source systems to a warehouse commonly happens in two ways — ETL and ELT. The former extracts and transforms information before loading it into centralized storage while the latter allows for loading data prior to transformation. As such, it is considered cloud-agnostic.

Weak Development Team 59

Weak Development Team Data Storage Technical Review 59

Altexsoft

DECEMBER 4, 2020

Three types of data migration tools. Use cases: small projects, specific source and target locations not supported by other solutions. Automation scripts can be written by data engineers or ETL developers in charge of your migration project. Phases of the data migration process. Data sources and destinations.

Software Review 69

Software Review Software Data Technical Review 69

Altexsoft

OCTOBER 21, 2022

Similar to Google in web browsing and Photoshop in image processing, it became a gold standard in data streaming, preferred by 70 percent of Fortune 500 companies. Apache Kafka is an open-source, distributed streaming platform for messaging, storing, processing, and integrating large data volumes in real time.

Weak Development Team 93

Weak Development Team Technical Review Systems Review Software Review 93

Daniel Bryant

SEPTEMBER 13, 2019

What was worth noting was that (anecdotally) even engineers from large organisations were not looking for full workload portability (i.e. There were also two patterns of adoption of HashiCorp tooling I observed from engineers that I chatted to: Infrastructure-driven?—?in

Infrastructure 8

Infrastructure Azure Software Engineering Cloud 8

Cloudera

DECEMBER 12, 2018

And so Impala was really about taking the experience of these big MPP systems on top of distributed file systems and moving that into an open source project for the world to use. But many of the execution tricks that SQL engines use, like Teradata, are being implemented in Apache Impala. This [F1] was more on the query side.

Data 42

Data Marketing Storage Big Data 42

Altexsoft

MARCH 30, 2023

What is Databricks Databricks is an analytics platform with a unified set of tools for data engineering, data management , data science, and machine learning. It combines the best elements of a data warehouse, a centralized repository for structured data, and a data lake used to host large amounts of raw data.

Weak Development Team 64

Weak Development Team Machine Learning Artificial Inteligence Software Review 64

O'Reilly Media - Ideas

JANUARY 25, 2022

A quick look at bigram usage (word pairs) doesn’t really distinguish between “data science,” “data engineering,” “data analysis,” and other terms; the most common word pair with “data” is “data governance,” followed by “data science.” It’s clear that Amazon Web Services’ competition is on the rise.

Trends 109

Trends Technical Review Technology Artificial Inteligence 109