Data Engineering Podcast

DECEMBER 16, 2018

At each level of scale it is important to minimize the impact of the ETL process on the source systems. What are your selection criteria when determining what workflow or ETL engines to use in your pipeline? At each level of scale it is important to minimize the impact of the ETL process on the source systems.

Data Pipeline 100

Data Pipeline Data Lake Data Warehouse Python 100

Data Engineering Podcast

MARCH 22, 2021

Datafold also helps automate regression testing of ETL code with its Data Diff feature that instantly shows how a change in ETL or BI code affects the produced data, both on a statistical level and down to individual rows and values. RudderStack’s smart customer data pipeline is warehouse-first.

Data Warehouse 100

Data Warehouse Metadata Data Lake Hadoop 100

Data Science Blog: Data Engineering

DECEMBER 23, 2022

Besonders im Trend liegen derzeitig die Cloud-nativen Datenbanken BigQuery von Google, Redshift von Amazon und Synapse von Microsoft sowie die cloud-unabhängige Datenbank snowflake. The post Jobprofil des Data Engineers appeared first on Data Science Blog (English only).

Data Engineering 52

Data Engineering Data Engineer Engineering Business Intelligence 52

ProjectPro

JULY 23, 2021

AWS (Amazon Web Services) is the world’s leading and widely used cloud platform, with over 200 fully featured services available from data centers worldwide. This blog presents some of the most unique and innovative AWS projects from beginner to advanced levels. Kubernetes Clusters on Amazon EC2 Spot 9.

AWS 52

AWS Project Amazon Web Services Cloud Computing 52

ProjectPro

DECEMBER 7, 2021

This blog will give you an in-depth knowledge of what is a data pipeline and also explore other aspects such as data pipeline architecture, data pipeline tools, use cases, and so much more. The Importance of a Data Pipeline What is an ETL Data Pipeline? ETL is the acronym for Extract, Transform, and Load.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

Rockset

AUGUST 13, 2019

DynamoDB Streams + Lambda + Kinesis Firehose + Redshift 2. Low data latency requirements rule out ETL-based solutions which increase your data latency above the real-time threshold and inevitably lead to “ETL hell”. We consider several approaches, all of which use DynamoDB Streams but differ in how the dashboards are served: 1.

BI 40

BI NoSQL PostgreSQL AWS 40

Rockset

APRIL 29, 2019

In this blog post I compare options for real-time analytics on DynamoDB - Elasticsearch , Athena, and Spark - in terms of ease of setup, maintenance, query capability, latency. Developers often have a need to serve fast analytical queries over data in Amazon DynamoDB. AWS Glue is a fully managed ETL service that lets us do both.

NoSQL 52

NoSQL PostgreSQL AWS SQL 52

Big Data Tools

JULY 13, 2022

Amazon spent tremendous amounts of money developing on top of Postgres in Redshift. It integrates with different Message Queues out of the box, provides a real-time ETL experience, and offers built-in alerting and monitoring. Follow JetBrains Big Data Tools on Twitter and subscribe to our blog for more news!

Data Engineering 52

Data Engineering Data Engineer Engineering Kafka 52

Big Data Tools

JULY 13, 2022

Amazon spent tremendous amounts of money developing on top of Postgres in Redshift. It integrates with different Message Queues out of the box, provides a real-time ETL experience, and offers built-in alerting and monitoring. Follow JetBrains Big Data Tools on Twitter and subscribe to our blog for more news!

Data Engineering 52

Data Engineering Data Engineer Engineering Kafka 52

ProjectPro

FEBRUARY 21, 2023

Whether you are just starting your career as a Data Engineer or looking to take the next step, this blog will walk you through the most valuable data engineering certifications and help you make an informed decision about which one to pursue. Don’t worry! Why Are Data Engineering Skills In Demand?

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Rockset

AUGUST 12, 2019

Low data latency requirements rule out ETL-based solutions which increase your data latency above the real-time threshold and inevitably lead to “ETL hell”. Amazon S3 The first approach for DynamoDB reporting and dashboarding we’ll consider makes use of Amazon S3’s static website hosting.

NoSQL 40

NoSQL AWS SQL Datasets 40

ProjectPro

JANUARY 19, 2022

The report also mentioned that big tech giants like Amazon and Accenture are willing to dig a deep hole in their pockets for hiring skilled data engineers. Build and execute data ETL solution pipelines for multiple clients in different industries. For appropriate resources, refer to this blog’s data engineering learning path.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

Rockset

JANUARY 23, 2019

Have you ever wanted to run SQL queries on Amazon DynamoDB tables without impacting your production workloads? Wouldn't it be great to do so without needing to set up an ETL job and then having to manually monitor that job? DynamoDB supports scan operations over one or more items and also captures table activity using DynamoDB Streams.

SQL 40

SQL NoSQL AWS Datasets 40

Monte Carlo

AUGUST 31, 2023

Now, with the rise of data-driven analytics, cross-functional data teams, and most importantly, the cloud, cloud data warehousing solutions such as Amazon Redshift, Snowflake, and Google BigQuery have become increasingly popular options for companies bullish on data. Meet: the data lakehouse.

Data Lake 52

Data Lake Data Pipeline Unstructured Data Data Warehouse 52

ProjectPro

FEBRUARY 8, 2023

Do ETL and data integration activities seem complex to you? Read this blog to understand everything about AWS Glue that makes it one of the most popular data integration solutions in the industry. Glue uses ETL jobs for extracting data from various AWS cloud services and integrating it into data warehouses and lakes.

AWS 98

AWS Scala Metadata Data Lake 98

Edureka

JUNE 1, 2023

In this blog, we’ll explore the world of Cloud Data Analytics and a real-life application of AWS Data Analytics. AWS Data analytics Amazon Redshift Hands on Industries using AWS Data Analytics Conclusion The following statistics gives an overview of the amount of data that is shared across the globe every day.

AWS 52

AWS Data Analytics Cloud Amazon Web Services 52

Monte Carlo

JANUARY 16, 2024

In this blog post, we’ll look at six innovations that are shaping the future of the data warehousing, as well as challenges and considerations that organizations should keep in mind. Beyond zero-copy data sharing, Amazon (AWS) has a grander vision for a zero ETL future altogether. Table of Contents 1.

Data Lake 52

Data Lake Data Warehouse Unstructured Data AWS 52

Knowledge Hut

NOVEMBER 17, 2023

One popular cloud computing service is AWS (Amazon Web Services). What is Amazon Web Services (AWS)? What is Amazon Web Services (AWS)? AWS was launched by Amazon as a cloud computing platform, offering various services like IaaS, PaaS, SaaS, and others. In 2006, Amazon launched AWS to handle its online retail operations.

AWS 52

AWS Data Science Certification Amazon Web Services 52

ProjectPro

AUGUST 24, 2021

And, out of these professions, this blog will discuss the data engineering job role. So, work on projects that guide you on how to build end-to-end ETL/ELT data pipelines. The primary step in this data project is to gather streaming data from Airline API using NiFi and batch data using AWS redshift using Sqoop.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

Rockset

FEBRUARY 24, 2022

AWS Kinesis Kinesis is Amazon’s solution for collecting and processing streaming data in real time. It’s a fully managed service within the Amazon Web Services (AWS) cloud, which obviates the need to manage infrastructure. Redshift has some limitations. You need to move data quickly from Kinesis to Redshift via Firehose.

AWS 52

AWS Amazon Web Services Kafka Business Intelligence 52

ProjectPro

JUNE 16, 2022

Amazon Web Services (AWS) offers an AWS Data Pipeline solution that helps businesses automate the transformation and movement of data. With AWS Data Pipeline, companies can quickly get started with Amazon Web Services and define data-driven workflows and parameters of data transformations. 2) What is AWS data pipeline vs. AWS glue?

Data Pipeline 59

Data Pipeline AWS Amazon Web Services Data Consolidation 59

Data Science Blog: Data Engineering

SEPTEMBER 19, 2023

Whether you’re using Redshift, Snowflake, or any other cloud-based data warehouse solutions, you can codify your architecture settings, allowing you to track changes over time. This brings reliability to data ETL (Extract, Transform, Load) processes, query performances, and other critical data operations.

Data Warehouse 52

Data Warehouse Coding Systems Cloud 52

Knowledge Hut

DECEMBER 21, 2023

Data warehouse engineers are responsible for the execution of ETL methods, cube construction for database and performance management and dimensional planning for the table structure. Companies that provide higher salaries are bigger businesses with higher, more experienced data science teams, such as IBM, Amazon, Meta, and Google.

Data Engineering 52

Data Engineering Data Engineer Engineering MongoDB 52

dbt Developer Hub

NOVEMBER 22, 2022

Below is a summary table highlighting the core benefits and drawbacks of certain ETL tooling options for getting spreadsheet data in your data warehouse. It’s also the most provider-agnostic, with support for Amazon S3, Google Cloud Storage, Azure and the local file system.

Data Warehouse 52

Data Warehouse ETL Tools Google Cloud Cloud Storage 52

Knowledge Hut

JANUARY 24, 2024

If you are an expert in working with data or a beginner excited to use visualization, this blog will help you understand the differences between power bi and tableau. ETL/Discovery suite: Compared to Tableau, Power BI has a robust set of tools for implementing ETL functions.

BI 93

BI Business Intelligence Non-relational Database Data Analysis 93

AltexSoft

JANUARY 26, 2022

Data engineers build data pipelines and perform ETL — extract data from sources, transform it, and load it into a centralized repository like a data warehouse. If we take the more traditional approach to data-related jobs used by larger companies, there are different specialists doing narrowly-focused tasks on different sides of the project.

Engineering 59

Engineering Software Engineer Software Engineering Data Warehouse 59

U-Next

SEPTEMBER 7, 2022

Amazon Redshift. . Amazon Web Services S3 . It also includes implementing or refactoring the ETL processes for loading the data since data that enters data warehouses requires a rigorous governance process. . We hope our blog will come to your rescue when choosing between a data lake and a data warehouse.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Amazon Web Services 52

AltexSoft

OCTOBER 21, 2022

After trying all options existing on the market — from messaging systems to ETL tools — in-house data engineers decided to design a totally new solution for metrics monitoring and user activity tracking which would handle billions of messages a day. cloud data warehouses — for example, Snowflake , Google BigQuery, and Amazon Redshift.

Kafka 93

Kafka Hadoop ETL Tools Big Data 93

ProjectPro

JANUARY 31, 2022

This blog walks you through what does Snowflake do , the various features it offers, the Snowflake architecture, and so much more. Snowflake puts all data on a single high-performance platform by bringing data in from many locations, reducing the complexity and delay imposed by standard ETL processes.

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

Datakin

OCTOBER 5, 2021

Cloud data warehouses & BYOP "Today, cloud data warehouses (Snowflake, Amazon Redshift and Google BigQuery) and lakehouses (Databricks) provide the ability to store massive amounts of data in a way that’s useful, not completely cost-prohibitive and doesn’t require an army of very technical people to maintain.

Data Warehouse 52

Data Warehouse Machine Learning Data Science Datasets 52

ProjectPro

SEPTEMBER 6, 2021

AWS vs. GCP blog compares the two major cloud platforms to help you choose the best one. Amazon and Google are the big bulls in cloud technology, and the battle between AWS and GCP has been raging on for a while. Google launched its Cloud Platform in 2008, six years after Amazon Web Services launched in 2002.

AWS 52

AWS Amazon Web Services Google Cloud Cloud Storage 52

ProjectPro

MAY 31, 2021

This blog lists over 20 big data projects you can work on to showcase your big data skills and gain hands-on experience in big data tools and technologies. Have you ever looked for sneakers on Amazon and seen advertisements for similar sneakers while searching the internet for the perfect cake recipe? How Big Data Works?

Big Data 52

Big Data Coding Project Hadoop 52

RandomTrees

NOVEMBER 29, 2023

Data Vault Architecture Some simple benefits As it is very clearly inferred from the above conceptual architecture a data vault technique is more scalable till and above pita bits of data, being ready for refactoring, more agile, can use familiar architecture principles using most available ETL/ELT codes and they can be generated at will.

Data Warehouse 52

Data Warehouse Data Lake Database-centric Data Cleanse 52