ProjectPro

FEBRUARY 8, 2023

AWS Glue is a widely-used serverless data integration service that uses automated extract, transform, and load ( ETL ) methods to prepare data for analysis. It offers a simple and efficient solution for data processing in organizations. Create schedules or events that will act as job triggers.

AWS 98

AWS Scala Metadata Data Lake 98

AltexSoft

OCTOBER 21, 2022

This scenario involves three main characters — publishers, subscribers, and a message or event broker. A publisher (say, telematics or Internet of Medical Things system) produces data units, also called events or messages , and directs them not to consumers but to a middleware platform — a broker. Kafka cluster and brokers.

Kafka 93

Kafka Hadoop Big Data ETL Tools 93

DareData

JULY 5, 2023

The architecture of a data lake project may contain multiple components, including the Data Lake itself, one or multiple Data Warehouses or one or multiple Data Marts. The Data Lake acts as the central repository for aggregating data from diverse sources in its raw format.

Data Lake 52

Data Lake Building Raw Data ETL Tools 52

Ascend.io

SEPTEMBER 14, 2023

PySpark, for instance, optimizes distributed data operations across clusters, ensuring faster data processing. Use Case: Storing data with PostgreSQL (example) import psycopg2 conn = psycopg2.connect(dbname="mydb", Use Case: Processing streaming tweets from pyspark.streaming import StreamingContext from pyspark.

Data Engineering 52

Data Engineering Data Engineer Python Engineering 52

Knowledge Hut

NOVEMBER 17, 2023

To be an Azure Data Engineer, you must have a working knowledge of SQL (Structured Query Language), which is used to extract and manipulate data from relational databases. You should be able to create intricate queries that use subqueries, join numerous tables, and aggregate data. The certification cost is $165 USD.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

Confluent

FEBRUARY 6, 2019

However, some data scientists do not even know “bread-and-butter” concepts of software engineers, such as version control systems like GitHub or continuous integration tools like Jenkins. Apache Kafka and KSQL for data scientists and data engineers. Rapid prototyping is typically used here.

Machine Learning 107

Machine Learning Python Kafka Java 107

Databand.ai

JULY 10, 2023

Faster issue diagnosis: Aggregating data from multiple sources enables engineers to correlate events more easily when troubleshooting problems, allowing them to resolve issues more quickly and prevent future occurrences through proactive measures such as capacity planning or automated remediation actions based on observed trends.

Data Pipeline 52

Data Pipeline Algorithm Raw Data Data Engineering 52

ProjectPro

DECEMBER 7, 2021

The big data pipeline must process data in large volumes concurrently because, in reality, multiple big data events are likely to occur at once or relatively close together. Consequently, data engineers implement checkpoints so that no event is missed or processed twice.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

AltexSoft

SEPTEMBER 21, 2023

Besides Elasticsearch, which is the hub for indexing, searching, and complex data analytics, the stacks include the following tools Beats are lightweight data shippers that are part of the Elastic Stack. Beats facilitate data movement from source to destination, which can be either Elasticsearch or Logstash, depending on the use case.

Engineering 52

Engineering NoSQL Programming Language Java 52

AltexSoft

DECEMBER 23, 2022

ELT makes it easier to manage and access all this information by allowing both raw and cleaned data to be loaded and stored for further analysis. With the ETL shift from a traditional on-premise variant to a cloud solution, you can also use it to work with different data sources and move a lot of data. Aggregation.

Process 52

Process Building Raw Data Data Lake 52

ProjectPro

NOVEMBER 15, 2021

It serves as a distributed processing engine for both categories of data streams: unbounded and bounded. Support for stream and batch processing, comprehensive state management, event-time processing semantics, and consistency guarantee for the state are just a few of Flink's capabilities.

Big Data 52

Big Data Project Metadata Programming Language 52

ProjectPro

OCTOBER 28, 2015

Get More Practice, More Big Data and Analytics Projects , and More guidance.Fast-Track Your Career Transition with ProjectPro How Apache Flume works? Flume has a simple event driven pipeline architecture with 3 important roles-Source, Channel and Sink. Sinks defined the destination of the data pipelined from various sources.

ETL Tools 52

ETL Tools Hadoop Relational Database Unstructured Data 52

ProjectPro

AUGUST 24, 2021

Data Engineering Project for Beginners If you are a newbie in data engineering and are interested in exploring real-world data engineering projects, check out the list of data engineering project examples below. This big data project discusses IoT architecture with a sample use case.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

ProjectPro

JUNE 28, 2016

Kafka is extensively being used across industries for general – purpose messaging system where high availability and real time data integration and analytics are of utmost importance. It provides a scalable and reliable messaging system for cloud based environment for asynchronous messaging distribution.

Kafka 40

Kafka Systems Hadoop Big Data 40

phData: Data Engineering

JANUARY 3, 2022

This likely requires you to aggregate data from your ERP system, your supply chain system, potentially third-party vendors, and data around your internal business structure. Performance It’s not as simple as having data correct and available for a data engineer. Data must also be performant.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Governance 52

ProjectPro

JULY 27, 2021

Data Engineer Interview Questions on Big Data Any organization that relies on data must perform big data engineering to stand out from the crowd. But data collection, storage, and large-scale data processing are only the first steps in the complex process of big data analysis.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

ProjectPro

OCTOBER 29, 2021

With the size of the datasets used for data mining , the data preprocessing step is such a vital part of data mining that it has come to be known as a data mining technique. Before moving on to the steps to improve data quality, let us spend a moment in this section to understand just what it is we seek to change.

Data Mining 52

Data Mining Datasets Machine Learning Metadata 52

AltexSoft

MARCH 14, 2023

As the volume and complexity of data continue to grow, organizations seek faster, more efficient, and cost-effective ways to manage and analyze data. In recent years, cloud-based data warehouses have revolutionized data processing with their advanced massively parallel processing (MPP) capabilities and SQL support.

IT 59

IT Data Warehouse Data Governance Data Lake 59

DoorDash Engineering

APRIL 12, 2023

Data scientists are the primary metric creators and are already familiar with SQL, so it made sense to use SQL as the language to define metrics instead of building our own DSL. Data modeling Our platform requires access to data at the raw fact or event level, not just the aggregates.

SQL 83

SQL Metadata Raw Data Government 83