Knowledge Hut

JUNE 23, 2023

Apache Hadoop-based analytics to compute distributed processing and storage against datasets. Other Competencies You should have proficiency in coding languages like SQL, NoSQL, Python, Java, R, and Scala. Get certified in relational and non-relational database designs, which will help you with proficiency in SQL and NoSQL domains.

Data Engineering 52

Data Engineering Data Engineer Engineering Non-relational Database 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. Intellipaat Big Data Hadoop Certification Introduction : This Big Data training course helps you master big data and Hadoop skills like MapReduce, Hive, Sqoop, etc.

Big Data 52

Big Data Certification Hadoop Scala 52

Cloud Academy

JANUARY 27, 2022

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. MongoDB Configuration and Setup Watch an example of deploying MongoDB to understand its benefits as a database system.

Data Engineering 52

Data Engineering Data Engineer Certification Engineering 52

Ascend.io

SEPTEMBER 14, 2023

compute() Data Storage Python extends its mastery to data storage, boasting smooth integrations with both SQL and NoSQL databases. Be it PostgreSQL, MySQL, MongoDB, or Cassandra, Python ensures seamless interactions. Use Case: Processing streaming tweets from pyspark.streaming import StreamingContext from pyspark.

Data Engineering 52

Data Engineering Data Engineer Python Engineering 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

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. You should be skilled in SQL and knowledgeable about NoSQL databases like Cassandra, MongoDB, and HBase.

Machine Learning 52

Machine Learning Data Engineering Data Engineer Engineering 52

ProjectPro

JUNE 17, 2016

You will need a complete 100% LinkedIn profile overhaul to land a top gig as a Hadoop Developer , Hadoop Administrator, Data Scientist or any other big data job role. Location and industry – Locations and industry helps recruiters sift through your LinkedIn profile on the available Hadoop or data science jobs in that locations.

Hadoop 40

Hadoop Recruitment Big Data NoSQL 40

U-Next

AUGUST 10, 2022

NoSQL databases are non-tabular, so they can be either a network or a record based on their data structure. 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.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Science 52

Rockset

AUGUST 11, 2022

Our talk follows an earlier video roundtable hosted by Rockset CEO Venkat Venkataramani, who was joined by a different but equally-respected panel of data engineering experts, including: DynamoDB author Alex DeBrie ; MongoDB director of developer relations Rick Houlihan ; Jeremy Daly , GM of Serverless Cloud.

Bytes 52

Bytes Consulting Kafka MongoDB 52

AltexSoft

MARCH 14, 2023

Many components of a modern data stack (such as Apache Airflow, Kafka, Spark, and others) are open-source and free. 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.

IT 59

IT Data Warehouse Data Governance Data Lake 59

Rockset

APRIL 15, 2022

Explosion in Streaming Data Before Kafka, Spark and Flink, streaming came in two flavors: Business Event Processing (BEP) and Complex Event Processing (CEP). Many (Kafka, Spark and Flink) were open source. Earlier at Yahoo, he was one of the founding engineers of the Hadoop Distributed File System.

Analytics Application 52

Analytics Application Data Warehouse Raw Data Kafka 52

AltexSoft

OCTOBER 8, 2021

ODI has a wide array of connections to integrate with relational database management systems ( RDBMS) , cloud data warehouses, Hadoop, Spark , CRMs, B2B systems, while also supporting flat files, JSON, and XML formats. There are also out-of-the-box connectors for such services as AWS, Azure, Oracle, SAP, Kafka, Hadoop, Hive, and more.

Data Integration 52

Data Integration Hadoop Data Warehouse Data Lake 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

JULY 6, 2016

This article will give you a sneak peek into the commonly asked HBase interview questions and answers during Hadoop job interviews. But at that moment, you cannot remember, and then blame yourself mentally for not preparing thoroughly for your Hadoop Job interview. HBase provides real-time read or write access to data in HDFS.

Hadoop 40

Hadoop Bytes Metadata MongoDB 40

ProjectPro

JULY 30, 2021

Map-reduce - Map-reduce enables users to use resizable Hadoop clusters within Amazon infrastructure. Amazon’s counterpart of this is called Amazon EMR ( Elastic Map-Reduce) Hadoop - Hadoop allows clustering of hardware to analyse large sets of data in parallel. What are the platforms that use Cloud Computing?

Cloud Computing 40

Cloud Computing Cloud Amazon Web Services AWS 40

ProjectPro

JANUARY 19, 2022

Hadoop, MongoDB, and Kafka are popular Big Data tools and technologies a data engineer needs to be familiar with. They must be skilled at creating solutions that use the Azure Cosmos DB for NoSQL API. Data engineers don't just work with conventional data; and they're often entrusted with handling large amounts of data.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

ProjectPro

JULY 27, 2021

E.g. Redis, MongoDB, Cassandra, HBase , Neo4j, CouchDB What is data modeling? Prepare for Your Next Big Data Job Interview with Kafka Interview Questions and Answers How is a data warehouse different from an operational database? How does Network File System (NFS) differ from Hadoop Distributed File System (HDFS)?

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40