Knowledge Hut

APRIL 25, 2024

There are a variety of big data processing technologies available, including Apache Hadoop, Apache Spark, and MongoDB. Spark provides an interactive shell that can be used for ad-hoc data analysis, as well as APIs for programming in Java, Python, and Scala. The most popular NoSQL database systems include MongoDB, Cassandra, and HBase.

Big Data 98

Big Data Technology Hadoop NoSQL 98

Data Engineering Podcast

SEPTEMBER 25, 2022

With their new managed database service you can launch a production ready MySQL, Postgres, or MongoDB cluster in minutes, with automated backups, 40 Gbps connections from your application hosts, and high throughput SSDs. Go to dataengineeringpodcast.com/ascend and sign up for a free trial.

Food 100

Food MongoDB Scala MySQL 100

Data Engineering Podcast

AUGUST 28, 2022

With their new managed database service you can launch a production ready MySQL, Postgres, or MongoDB cluster in minutes, with automated backups, 40 Gbps connections from your application hosts, and high throughput SSDs. Go to dataengineeringpodcast.com/ascend and sign up for a free trial.

Building 100

Building MongoDB Scala MySQL 100

Cloud Academy

JANUARY 27, 2022

Some good options are Python (because of its flexibility and being able to handle many data types), as well as Java, Scala, and Go. Microsoft SQL Server Document-oriented database: MongoDB (classified as NoSQL) The Basics of Data Management, Data Manipulation and Data Modeling This learning path focuses on common data formats and interfaces.

Certification 52

Certification Data Engineer Data Engineering Engineering 52

Data Engineering Podcast

AUGUST 6, 2022

With their new managed database service you can launch a production ready MySQL, Postgres, or MongoDB cluster in minutes, with automated backups, 40 Gbps connections from your application hosts, and high throughput SSDs. Go to dataengineeringpodcast.com/ascend and sign up for a free trial.

Machine Learning 100

Machine Learning Database MySQL PostgreSQL 100

Monte Carlo

OCTOBER 31, 2024

In addition, AI data engineers should be familiar with programming languages such as Python , Java, Scala, and more for data pipeline, data lineage, and AI model development. Get familiar with data warehouses, data lakes, and data lakehouses, including MongoDB , Cassandra, BigQuery, Redshift and more.

Data Engineer 52

Data Engineer Data Engineering Engineering Unstructured Data 52

Knowledge Hut

JUNE 20, 2023

Languages Python, SQL, Java, Scala R, C++, Java Script, and Python Tools Kafka, Tableau, Snowflake, etc. Kafka: Kafka is a top engineering tool highly valued by big data experts. Machine learning engineer: A machine learning engineer is an engineer who uses programming languages like Python, Java, Scala, etc.

Machine Learning 52

Machine Learning Data Engineer Data Engineering Engineering 52

Knowledge Hut

OCTOBER 27, 2023

Android Local Train Ticketing System Developing an Android Local Train Ticketing System with Java, Android Studio, and SQLite. Java, Android Studio, and SQLite are the tools used to create an app that helps commuters to book train tickets directly from their mobile devices. cvtColor(image, cv2.COLOR_BGR2GRAY) findContours(thresh, cv2.RETR_TREE,

Software Engineering 98

Software Engineering Software Engineer Coding Project 98

Knowledge Hut

APRIL 25, 2023

Strong programming skills: Data engineers should have a good grasp of programming languages like Python, Java, or Scala, which are commonly used in data engineering. Data processing: Data engineers should know data processing frameworks like Apache Spark, Hadoop, or Kafka, which help process and analyze data at scale.

Data Engineer 52

Data Engineer Data Engineering Engineering Google Cloud 52

Ascend.io

SEPTEMBER 14, 2023

Read More: Data Automation Engineer: Skills, Workflow, and Business Impact Python for Data Engineering Versus SQL, Java, and Scala When diving into the domain of data engineering, understanding the strengths and weaknesses of your chosen programming language is essential. csv') data_excel = pd.read_excel('data2.xlsx')

Data Engineer 52

Data Engineer Data Engineering Python Engineering 52

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. Streaming analytics became possible with the introduction of Apache Kafka , Apache Spark , Apache Storm , Apache Flink , and other tools to build real-time data pipelines. What is Hadoop?

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

Knowledge Hut

APRIL 24, 2024

Android Local Train Ticketing System Developing an Android Local Train Ticketing System with Java, Android Studio, and SQLite. Java, Android Studio, and SQLite are the tools used to create an app that helps commuters to book train tickets directly from their mobile devices. cvtColor(image, cv2.COLOR_BGR2GRAY) findContours(thresh, cv2.RETR_TREE,

Software Engineering 52

Software Engineering Software Engineer Coding Project 52

Knowledge Hut

DECEMBER 26, 2023

Data Science also requires applying Machine Learning algorithms, which is why some knowledge of programming languages like Python, SQL, R, Java, or C/C++ is also required. They use technologies like Storm or Spark, HDFS, MapReduce, Query Tools like Pig, Hive, and Impala, and NoSQL Databases like MongoDB, Cassandra, and HBase.

Data Science 97

Data Science BI Business Intelligence Machine Learning 97

Knowledge Hut

NOVEMBER 17, 2023

Data engineers must know data management fundamentals, programming languages like Python and Java, cloud computing and have practical knowledge on data technology. Programming and Scripting Skills Building data processing pipelines requires knowledge of and experience with coding in programming languages like Python, Scala, or Java.

Data Engineer 52

Data Engineer Data Engineering Engineering Scala 52

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. The connector does require installing and managing additional tooling, Kafka Connect. This is because the mapping cannot be changed once it is already defined.

Data Ingestion 52

Data Ingestion Kafka Relational Database PostgreSQL 52

Edureka

FEBRUARY 9, 2023

Experience with data warehousing and ETL concepts, as well as programming languages such as Python, SQL, and Java, is required. Data engineers must be well-versed in programming languages such as Python, Java, and Scala. A data engineer should be familiar with popular Big Data tools and technologies such as Hadoop, MongoDB, and Kafka.

Data Engineer 52

Data Engineer Data Engineering Engineering Data Mining 52

Rockset

APRIL 3, 2020

It uses Cognito federated identities in conjunction with AWS IoT to create a client certificate and private key and store it in a local Java Keystore. The app will use the certificate and private key saved in the local java Keystore for future connections. We had selected Amazon MSK to run Kafka and Spark.

Data Pipeline 40

Data Pipeline Systems Management NoSQL 40

Knowledge Hut

SEPTEMBER 26, 2023

Programming languages like Python, Java, or Scala require a solid understanding of data engineers. Popular Big Data tools and technologies that a data engineer has to be familiar with include Hadoop, MongoDB, and Kafka. Data engineers handle vast volumes of data on a regular basis and don't only deal with normal data.

Certification 52

Certification Data Engineer Data Engineering Engineering 52

Striim

NOVEMBER 13, 2023

Versatile Source Connectivity: Striim offers a wide array of streaming source connectors including databases like Oracle, Microsoft SQL Server, MongoDB, PostgreSQL, IoT streams, Kafka, and many more.

Data Ingestion 59

Data Ingestion Utilities Data Integration Data 59

Knowledge Hut

SEPTEMBER 6, 2023

Programming Languages : Good command on programming languages like Python, Java, or Scala is important as it enables you to handle data and derive insights from it. 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.

Big Data 52

Big Data Certification Hadoop Kafka 52

Confluent

SEPTEMBER 20, 2019

As a distributed system for collecting, storing, and processing data at scale, Apache Kafka ® comes with its own deployment complexities. To simplify all of this, different providers have emerged to offer Apache Kafka as a managed service. BigQuery, Amazon Redshift, and MongoDB Atlas) and caches (e.g.,

Kafka 21

Kafka Management Cloud AWS 21

Knowledge Hut

JUNE 23, 2023

Other Competencies You should have proficiency in coding languages like SQL, NoSQL, Python, Java, R, and Scala. Equip yourself with the experience and know-how of Hadoop, Spark, and Kafka, and get some hands-on experience in AWS data engineer skills, Azure, or Google Cloud Platform. You can also post your work on your LinkedIn profile.

Data Engineer 52

Data Engineer Data Engineering Engineering Non-relational Database 52

ProjectPro

AUGUST 24, 2021

This architecture shows that simulated sensor data is ingested from MQTT to Kafka. The data in Kafka is analyzed with Spark Streaming API, and the data is stored in a column store called HBase. Finally, the data is published and visualized on a Java-based custom Dashboard. Collection happens in the Kafka topic.

Data Engineer 52

Data Engineer Data Engineering Coding Project 52

ProjectPro

JANUARY 19, 2022

Data engineers must thoroughly understand programming languages such as Python, Java, or Scala. Hadoop, MongoDB, and Kafka are popular Big Data tools and technologies a data engineer needs to be familiar with. They should be able to use PowerShell, read C# or Java code, and understand JSON.

Data Engineer 52

Data Engineer Data Engineering Engineering Data Storage 52

Databand.ai

DECEMBER 13, 2022

He currently runs a YouTube channel, E-Learning Bridge , focused on video tutorials for aspiring data professionals and regularly shares advice on data engineering, developer life, careers, motivations, and interviewing on LinkedIn.

Data Engineer 52

Data Engineer Data Engineering Engineering AWS 52

Knowledge Hut

DECEMBER 21, 2023

Data engineering involves a lot of technical skills like Python, Java, and SQL (Structured Query Language). Key education and technical skills include: A degree in computer science, information technology, or a related field Expert in programming languages Python, Java, and SQL. Knowledge of Hadoop, Spark, and Kafka.

Data Engineer 52

Data Engineer Data Engineering Engineering MongoDB 52

ProjectPro

JULY 6, 2016

Recommended Reading: Top 50 NLP Interview Questions and Answers 100 Kafka Interview Questions and Answers 20 Linear Regression Interview Questions and Answers 50 Cloud Computing Interview Questions and Answers HBase vs Cassandra-The Battle of the Best NoSQL Databases 3) Name few other popular column oriented databases like HBase.

Hadoop 40

Hadoop Bytes Metadata Database 40

ProjectPro

JULY 30, 2021

They get used in NoSQL databases like Redis, MongoDB, data warehousing. DB used in AWS MariaDB, Postgres, MongoDB, Oracle, MySQL are some common databases used in AWS. It supports PHP, GO, Java, Node,NET, Python, and Ruby. These instances use their local storage to store data.

Cloud Computing 40

Cloud Computing Cloud Amazon Web Services AWS 40

ProjectPro

NOVEMBER 14, 2015

Hadoop ecosystem has a very desirable ability to blend with popular programming and scripting platforms such as SQL, Java , Python, and the like which makes migration projects easier to execute. Tools/Tech stack used: The tools and technologies used for such healthcare data management using Apache Hadoop are MapReduce and MongoDB.

Hadoop 52

Hadoop Project Big Data Healthcare 52

U-Next

AUGUST 10, 2022

For this reason, learn an enterprise language, such as Java or C#. Numerous NoSQL databases are used today, including MongoDB, Cassandra, and Ruby. Apache Kafka is a well-liked tool for creating a broadcasting pipeline and is used by over 80% of Fortune 500 firms. Five Steps to Starting a Successful Career as a Data Engineer.

Data Engineer 52

Data Engineer Data Engineering Engineering Data Science 52