ProjectPro

FEBRUARY 16, 2023

ETL is a critical component of success for most data engineering teams, and with teams harnessing it with the power of AWS, the stakes are higher than ever. AWS refers to Amazon Web Service, the most widely used cloud computing system. AWS offers cloud services to businesses and developers, assisting them in maintaining agility.

AWS 52

AWS Data Management ETL Tools Management 52

U-Next

MARCH 1, 2023

A solid understanding of relational databases and SQL language is a must-have skill, as an ability to manipulate large amounts of data effectively. A good Data Engineer will also have experience working with NoSQL solutions such as MongoDB or Cassandra, while knowledge of Hadoop or Spark would be beneficial. What is AWS Kinesis?

Data Engineering 75

Data Engineering Data Engineer Non-relational Database Engineering 75

Data Engineering Weekly

JUNE 29, 2023

Well, how do we know a human writes the SQL for an ad-hoc request, which often goes through a zero review process, wrote the correct SQL query? Snowflake is a DataLake Platform Snowflake is moving beyond a SQL data warehouse. AWS EMR replicated the exact Hadoop layer and burned these two companies (combined).

Data Engineering 76

Data Engineering Data Engineer Google Cloud Engineering 76

ProjectPro

MAY 2, 2017

News on Hadoop-April 2017 AI Will Eclipse Hadoop, Says Forrester, So Cloudera Files For IPO As A Machine Learning Platform. Apache Hadoop was one of the revolutionary technology in the big data space but now it is buried deep by Deep Learning. Hortonworks unveiled this use case of SQL through Apache Hive 2.0

Hadoop 52

Hadoop Entertainment Data Lake Big Data 52

Knowledge Hut

APRIL 25, 2023

These tools include both open-source and commercial options, as well as offerings from major cloud providers like AWS, Azure, and Google Cloud. Data processing: Data engineers should know data processing frameworks like Apache Spark, Hadoop, or Kafka, which help process and analyze data at scale. What are Data Engineering Tools?

Data Engineering 52

Data Engineering Data Engineer Engineering Google Cloud 52

Christophe Blefari

APRIL 8, 2023

I was in the Hadoop world and all I was doing was denormalisation. The only normalisation I did was back at the engineering school while learning SQL with Normal Forms. Under the hood it uses sqlglot the SQL parser that has been developper by the same developper. Denormalisation everywhere. YAML configured.

Pipeline-centric 130

Pipeline-centric Database-centric Algorithm Data 130

Christophe Blefari

APRIL 8, 2023

I was in the Hadoop world and all I was doing was denormalisation. The only normalisation I did was back at the engineering school while learning SQL with Normal Forms. Under the hood it uses sqlglot the SQL parser that has been developper by the same developper. Denormalisation everywhere. YAML configured.

Pipeline-centric 130

Pipeline-centric Database-centric Algorithm Data 130

Knowledge Hut

DECEMBER 26, 2023

It helps to understand concepts like abstractions, algorithms, data structures, security, and web development and familiarizes learners with many languages like C, Python, SQL, CSS, JavaScript, and HTML. Select and use one of Google Cloud's storage solutions, which include Cloud Storage, Cloud SQL, Cloud Bigtable, and Firestore.

Certification 95

Certification Java Google Cloud Education 95

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. Table of Contents What is AWS? Customer Logic Workflow 8.

AWS 52

AWS Project Amazon Web Services Cloud Computing 52

Data Engineering Podcast

DECEMBER 11, 2022

Datafold shows how a change in SQL code affects your data, both on a statistical level and down to individual rows and values before it gets merged to production. Output data can be streamed into a data lake for query engines like Presto, Trino or Spark SQL, a data warehouse like Snowflake or Redshift., Pricing for SQLake is simple.

Database 100

Database MySQL Data Lake MongoDB 100

Knowledge Hut

MARCH 20, 2024

Handling databases, both SQL and NoSQL. Working on cloud infrastructure like AWS and other data platforms like Databricks and Snowflake. Working with cloud technologies: deploying solutions on platforms like AWS and Azure and ensuring scalability and security. Helped create various APIs, respond to payload requests, etc.

Engineering 52

Engineering NoSQL Programming Language Deep Learning 52

Data Engineering Podcast

JANUARY 13, 2019

Links TimescaleDB Original Appearance on the Data Engineering Podcast 1.0 Links TimescaleDB Original Appearance on the Data Engineering Podcast 1.0

Database 100

Database PostgreSQL SQL MongoDB 100

Knowledge Hut

JUNE 23, 2023

You should be well-versed with SQL Server, Oracle DB, MySQL, Excel, or any other data storing or processing software. Hard Skills SQL, which includes memorizing a query and resolving optimized queries. Apache Hadoop-based analytics to compute distributed processing and storage against datasets.

Data Engineering 52

Data Engineering Data Engineer Engineering Non-relational Database 52

Cloudera

AUGUST 26, 2021

Ozone natively provides Amazon S3 and Hadoop Filesystem compatible endpoints in addition to its own native object store API endpoint and is designed to work seamlessly with enterprise scale data warehousing, machine learning and streaming workloads. Boto3 is the standard python client for the AWS SDK. Spark SQL to access Hive table.

Data Science 114

Data Science Cloud Hadoop Metadata 114

Monte Carlo

APRIL 24, 2023

Databricks Data Catalog and AWS Lake Formation are examples in this vein. Snowflake simplifies data ingestion, querying, and transformation through its built-in support for SQL and compatibility with numerous data processing and integration tools. AWS is one of the most popular data lake vendors.

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 52

ProjectPro

APRIL 20, 2017

You have read some of the best Hadoop books , taken online hadoop training and done thorough research on Hadoop developer job responsibilities – and at long last, you are all set to get real-life work experience as a Hadoop Developer.

Hadoop 40

Hadoop Big Data Coding Project 40

ProjectPro

FEBRUARY 21, 2023

AWS or Azure? For instance, earning an AWS data engineering professional certificate can teach you efficient ways to use AWS resources within the data engineering lifecycle, significantly lowering resource wastage and increasing efficiency. Cloudera or Databricks? The exam is available in English, Japanese, Korean, and Chinese.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Knowledge Hut

NOVEMBER 2, 2023

CSV, SQL Server), transform it, and load it into a target storage (e.g., Azure SQL Database, Azure Data Lake Storage). Learn how to aggregate real-time data using several big data tools like Kafka, Zookeeper, Spark, HBase, and Hadoop. A strong understanding of data sourcing with SQL.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

Knowledge Hut

SEPTEMBER 6, 2023

Big Data Frameworks : Familiarity with popular Big Data frameworks such as Hadoop, Apache Spark, Apache Flink, or Kafka are the tools used for data processing. Cloud Computing : Knowledge of cloud platforms like AWS, Azure, or Google Cloud is essential as these are used by many organizations to deploy their big data solutions.

Big Data 52

Big Data Certification Hadoop Scala 52

Knowledge Hut

MARCH 28, 2024

Implemented and managed data storage solutions using Azure services like Azure SQL Database , Azure Data Lake Storage, and Azure Cosmos DB. Education & Skills Required Proficiency in SQL, Python, or other programming languages. Experience with Azure data services like Azure SQL Database, Azure Data Factory, and Azure Databricks.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

ProjectPro

NOVEMBER 14, 2015

Apache Hadoop and Apache Spark fulfill this need as is quite evident from the various projects that these two frameworks are getting better at faster data storage and analysis. These Apache Hadoop projects are mostly into migration, integration, scalability, data analytics, and streaming analysis. Table of Contents Why Apache Hadoop?

Hadoop 52

Hadoop Project Big Data Healthcare 52

AltexSoft

FEBRUARY 11, 2023

It serves as a foundation for the entire data management strategy and consists of multiple components including data pipelines; , on-premises and cloud storage facilities – data lakes , data warehouses , data hubs ;, data streaming and Big Data analytics solutions ( Hadoop , Spark , Kafka , etc.);

Data Architect 87

Data Architect Certification Generalist Big Data 87

Pipeline Data Engineering

SEPTEMBER 20, 2021

A future for SQL on the web James Long, Software Engineer, Stripe Absurd-sql is a persistent backend for SQLite on the web. That means it doesn’t have to load the whole db into memory, and writes persist.

Hadoop 52

Hadoop Software Engineer Software Engineering AWS 52

Knowledge Hut

SEPTEMBER 25, 2023

Languages : Prior to obtaining a related certificate, it's crucial to have at least a basic understanding of SQL since it is the most often used language in data analytics. Students will study the theory of data analytics as well as how to use Python and SQL for data analysis. Python is useful for various data analytics positions.

Certification 52

Certification Business Analyst Big Data Data Analysis 52

Cloud Academy

JANUARY 27, 2022

Many of them are already familiar with SQL or have experience working with databases, whether they’re relational or non-relational. Get a basic understanding of SQL A second requirement is to have a basic understanding of SQL. Learn about the AWS-managed Kafka offering in this course to see how it can be more quickly deployed.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Data Engineering Podcast

JULY 10, 2022

Ascend users love its declarative pipelines, powerful SDK, elegant UI, and extensible plug-in architecture, as well as its support for Python, SQL, Scala, and Java. Ascend automates workloads on Snowflake, Databricks, BigQuery, and open source Spark, and can be deployed in AWS, Azure, or GCP.

Data Engineering 100

Data Engineering Data Engineer Engineering MongoDB 100

Data Engineering Podcast

DECEMBER 9, 2018

With the large array of capabilities, and the complexity of the underlying system, it can be difficult to understand how to get started using it.

Scala 100

Scala MySQL Kafka Hadoop 100

Rockset

NOVEMBER 4, 2021

Here are some examples of the things you can do in your apps with Apache Spark: Build continuous ETL pipelines for stream processing SQL BI and analytics Do machine learning, and much more! Since Spark supports SQL queries that can help with data analytics, you’re probably thinking why would I use Rockset ???

Scala 52

Scala Java AWS Hadoop 52

Data Engineering Podcast

OCTOBER 9, 2022

Ascend users love its declarative pipelines, powerful SDK, elegant UI, and extensible plug-in architecture, as well as its support for Python, SQL, Scala, and Java. Ascend automates workloads on Snowflake, Databricks, BigQuery, and open source Spark, and can be deployed in AWS, Azure, or GCP.

Food 100

Food MongoDB Scala MySQL 100

Knowledge Hut

NOVEMBER 28, 2023

SQL Today, more and more cloud-based systems add SQL-like interfaces that allow you to use SQL. Traditional data transformation tools are still relevant today, while next-generation Kafka, cloud-based tools, and SQL are on the rise for 2023. ETL is central to getting your data where you need it.

Data Engineering 52

Data Engineering Data Engineer Engineering Generalist 52

Databand.ai

DECEMBER 13, 2022

He also has more than 10 years of experience in big data, being among the few data engineers to work on Hadoop Big Data Analytics prior to the adoption of public cloud providers like AWS, Azure, and Google Cloud Platform. On LinkedIn, he focuses largely on Spark, Hadoop, big data, big data engineering, and data engineering.

Data Engineering 52

Data Engineering Data Engineer Engineering AWS 52

ProjectPro

JANUARY 19, 2022

Data Engineering Requirements Data Engineer Learning Path: Self-Taught Learn Data Engineering through Practical Projects Azure Data Engineer Vs AWS Data Engineer Vs GCP Data Engineer FAQs on Data Engineer Job Role How long does it take to become a data engineer? Experience with using cloud services providing platforms like AWS/GCP/Azure.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

Data Engineering Podcast

AUGUST 31, 2020

In what ways have you found it necessary/useful to extend SQL? In what ways have you found it necessary/useful to extend SQL? What are some of the most challenging aspects of building a data warehouse platform that is optimized for speed? How do you handle support for nested and semi-structured data?

Data Warehouse 100

Data Warehouse Cloud Building Data Lake 100

ProjectPro

APRIL 8, 2015

With the demand for big data technologies expanding rapidly, Apache Hadoop is at the heart of the big data revolution. Here are top 6 big data analytics vendors that are serving Hadoop needs of various big data companies by providing commercial support. The Global Hadoop Market is anticipated to reach $8.74 billion by 2020.

Hadoop 40

Hadoop Big Data Data Solutions Amazon Web Services 40

Data Engineering Podcast

OCTOBER 21, 2019

This week’s episode is also sponsored by Datacoral, an AWS-native, serverless, data infrastructure that installs in your VPC. He started Datacoral with the goal to make SQL the universal data programming language. He started Datacoral with the goal to make SQL the universal data programming language.

Cloud 100

Cloud Data Lake Hadoop Programming Language 100

Knowledge Hut

MAY 2, 2024

It is also friendly for database developers as it provides Spark SQL which supports most of the ANSI SQL functionality. It does work with a variety of other Data sources like Cassandra, MySQL, AWS S3 etc. Spark SQL: Spark has an amazing SQL support and has an in-built SQL optimizer.

Scala 52

Scala Hospitality Healthcare Retail 52

ProjectPro

DECEMBER 7, 2021

Data Pipeline Tools AWS Data Pipeline Azure Data Pipeline Airflow Data Pipeline Learn to Create a Data Pipeline FAQs on Data Pipeline What is a Data Pipeline? AWS Glue You can easily extract and load your data for analytics using the fully managed extract, transform, and load (ETL) service AWS Glue. What is a Big Data Pipeline?

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52