Data Engineering Podcast

JUNE 5, 2022

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode. In fact, while only 3.5%

Data Security 100

Data Security Metadata MongoDB MySQL 100

Data Engineering Podcast

JULY 3, 2022

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode. In fact, while only 3.5%

Data Integration 100

Data Integration MongoDB MySQL Scala 100

Data Engineering Podcast

JULY 31, 2022

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode. In fact, while only 3.5%

Data Analysis 100

Data Analysis MongoDB Algorithm MySQL 100

Data Engineering Podcast

OCTOBER 30, 2022

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode. In fact, while only 3.5%

Engineering 100

Engineering MongoDB MySQL Scala 100

Data Engineering Podcast

NOVEMBER 13, 2022

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode. In fact, while only 3.5%

MongoDB 100

MongoDB MySQL Google Cloud Scala 100

Rockset

NOVEMBER 12, 2020

Offloading analytics from MongoDB establishes clear isolation between write-intensive and read-intensive operations. In most scenarios, MongoDB can be used as the primary data storage for write-only operations and as support for quick data ingestion. Monstache is also available as a sync daemon and a container.

MongoDB 40

MongoDB NoSQL Data Pipeline Data Storage 40

Data Engineering Podcast

JUNE 26, 2022

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode. In fact, while only 3.5%

Data Management 100

Data Management Management MongoDB MySQL 100

Data Engineering Podcast

AUGUST 6, 2022

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode. In fact, while only 3.5%

Machine Learning 100

Machine Learning Database MySQL PostgreSQL 100

Data Engineering Podcast

AUGUST 13, 2022

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode. In fact, while only 3.5%

Machine Learning 100

Machine Learning Pipeline-centric Database-centric MongoDB 100

ProjectPro

DECEMBER 7, 2021

Data pipelines are a significant part of the big data domain, and every professional working or willing to work in this field must have extensive knowledge of them. Table of Contents What is a Data Pipeline? The Importance of a Data Pipeline What is an ETL Data Pipeline?

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

Rockset

SEPTEMBER 3, 2020

MongoDB’s Advantages & Disadvantages MongoDB has comprehensive aggregation capabilities. You can run many analytic queries on MongoDB without exporting your data to a third-party tool. In this situation, the MongoDB cluster doesn’t have to keep up with the read requests. This is never a good thing.

MongoDB 40

MongoDB PostgreSQL SQL Database 40

Rockset

OCTOBER 11, 2022

Introduction Managing streaming data from a source system, like PostgreSQL, MongoDB or DynamoDB, into a downstream system for real-time analytics is a challenge for many teams. With the aliases API, it is still tricky to keep the new index in sync with the latest data.

Data Ingestion 52

Data Ingestion Kafka Relational Database PostgreSQL 52

Data Engineering Podcast

SEPTEMBER 4, 2022

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode. In fact, while only 3.5%

MongoDB 100

MongoDB MySQL Scala Machine Learning 100

DareData

JANUARY 30, 2023

In this post, we'll discuss some key data engineering concepts that data scientists should be familiar with, in order to be more effective in their roles. These concepts include concepts like data pipelines, data storage and retrieval, data orchestrators or infrastructure-as-code.

Data Engineering 52

Data Engineering Data Engineer NoSQL Engineering 52

Rockset

MARCH 15, 2021

This includes making the data available for query as soon as it is ingested, creating proper indexes on the data so that the query latency is very low, and much more. Before it can be ingested, there’s usually a data pipeline for transforming incoming data. latency, indexing, etc.),

MongoDB 40

MongoDB Data Ingestion Analytics Application Kafka 40

Knowledge Hut

APRIL 25, 2023

Data engineering is a field that requires a range of technical skills, including database management, data modeling, and programming. Data engineering tools can help automate many of these processes, allowing data engineers to focus on higher-level tasks like extracting insights and building data pipelines.

Data Engineering 52

Data Engineering Data Engineer Engineering Google Cloud 52

Rockset

AUGUST 30, 2021

A Quick Primer on Indexing in Rockset Rockset allows users to connect real-time data sources — data streams (Kafka, Kinesis), OLTP databases (DynamoDB, MongoDB, MySQL, PostgreSQL) and also data lakes (S3, GCS) — using built-in connectors. In example above, these base aggregate metrics are count(*) and sum(error_flag).

SQL 52

SQL Kafka MongoDB MySQL 52

AltexSoft

MAY 14, 2021

Big Data analytics encompasses the processes of collecting, processing, filtering/cleansing, and analyzing extensive datasets so that organizations can use them to develop, grow, and produce better products. Big Data analytics processes and tools. Data ingestion. Let’s take a closer look at these procedures.

Big Data 78

Big Data Data Analytics IT NoSQL 78

Rockset

NOVEMBER 28, 2022

First, CDC theoretically allows companies to analyze and react to data in real time, as it’s generated. It works with existing streaming systems like Apache Kafka, Amazon Kinesis, and Azure Events Hubs, making it easier than ever to build a real-time data pipeline. Striim : A unified data integration and streaming platform.

Data Warehouse 52

Data Warehouse PostgreSQL MongoDB SQL 52

ProjectPro

OCTOBER 28, 2015

Apache Hadoop is synonymous with big data for its cost-effectiveness and its attribute of scalability for processing petabytes of data. Data analysis using hadoop is just half the battle won. Getting data into the Hadoop cluster plays a critical role in any big data deployment. then you are on the right page.

ETL Tools 52

ETL Tools Hadoop Relational Database Unstructured Data 52

ProjectPro

AUGUST 24, 2021

Data Sourcing: Building pipelines to source data from different company data warehouses is fundamental to the responsibilities of a data engineer. So, work on projects that guide you on how to build end-to-end ETL/ELT data pipelines. Google BigQuery receives the structured data from workers.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

Rockset

MAY 12, 2022

Lambda systems try to accommodate the needs of both big data-focused data scientists as well as streaming-focused developers by separating data ingestion into two layers. One layer processes batches of historic data. It provides instant views of the real-time data.

Analytics Application 52

Analytics Application Lambda Architecture Hadoop Database 52

Rockset

DECEMBER 9, 2021

Lifting-and-shifting their big data environment into the cloud only made things more complex. The modern data stack introduced a set of cloud-native data solutions such as Fivetran for data ingestion, Snowflake, Redshift or BigQuery for data warehousing , and Looker or Mode for data visualization.

Transportation 52

Transportation BI SQL Database 52

AltexSoft

JUNE 26, 2023

Read our article on Hotel Data Management to have a full picture of what information can be collected to boost revenue and customer satisfaction in hospitality. While all three are about data acquisition, they have distinct differences. For this task, you need a dedicated specialist — a data engineer or ETL developer.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

AltexSoft

MARCH 14, 2023

Also, there are NoSQL databases that can be home to all sorts of data, including unstructured and semi-structured (images, PDF files, audio, JSON, etc.) Some popular databases are Postgres and MongoDB. Data orchestration involves managing the scheduling and execution of data workflows.

IT 59

IT Data Warehouse Data Governance Data Lake 59

ProjectPro

JANUARY 19, 2022

Build an Awesome Job Winning Project Portfolio with Solved End-to-End Big Data Projects AWS Projects AWS Project-Website Monitoring using AWS Lambda and Aurora How to deal with slowly changing dimensions using Snowflake? Depending on the company you want to work with, you will be asked to learn them deeply.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

ProjectPro

JANUARY 31, 2023

There are three steps involved in the deployment of a big data model: Data Ingestion: This is the first step in deploying a big data model - Data ingestion, i.e., extracting data from multiple data sources. Query Surge helps us automate our manual efforts in Big Data testing.

Big Data 52

Big Data Hadoop Relational Database AWS 52

Data Engineering Podcast

AUGUST 28, 2022

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode. In fact, while only 3.5%

Building 100

Building MongoDB MySQL Scala 100

AltexSoft

JULY 29, 2022

To facilitate data ingestion, there are Apache Flume aggregating log data from multiple servers and Apache Sqoop designed to transport information between Hadoop and relational (SQL) databases. You are welcome to explore them yourself to find the right instruments for your requirements and for data engineering of any complexity.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59