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

Knowledge Hut

SEPTEMBER 26, 2023

The role-specific competencies highlight the essential skills and knowledge needed by data engineers to perform their duties. For the Azure certification path for data engineering, we should think about developing the following role-specific skills: Most of the data processing and storage systems employ programming languages.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Knowledge Hut

DECEMBER 26, 2023

They use technologies like Storm or Spark, HDFS, MapReduce, Query Tools like Pig, Hive, and Impala, and NoSQL Databases like MongoDB, Cassandra, and HBase. They also make use of ETL tools, messaging systems like Kafka, and Big Data Tool kits such as SparkML and Mahout.

Data Science 97

Data Science BI Business Intelligence Data Mining 97

AltexSoft

JUNE 7, 2021

Hadoop and Spark are the two most popular platforms for Big Data processing. They both enable you to deal with huge collections of data no matter its format — from Excel tables to user feedback on websites to images and video files. Obviously, Big Data processing involves hundreds of computing units.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

ProjectPro

JANUARY 25, 2022

Features of PySpark Features that contribute to PySpark's immense popularity in the industry- Real-Time Computations PySpark emphasizes in-memory processing, which allows it to perform real-time computations on huge volumes of data. PySpark is used to process real-time data with Kafka and Streaming, and this exhibits low latency.

Big Data 52

Big Data Data Process Process Kafka 52

ProjectPro

APRIL 20, 2017

There are various kinds of hadoop projects that professionals can choose to work on which can be around data collection and aggregation, data processing, data transformation or visualization. Apply what you have learned, explore a variety of hands-on example projects for data engineers. What is Data Engineering?

Hadoop 40

Hadoop Big Data Coding Project 40

Databand.ai

DECEMBER 13, 2022

He also has adept knowledge of coding in Python, R, SQL, and using big data tools such as Spark. Mark is the founder of On the Mark Data , where he uses the platform to share impactful ideas via content creation, as well as push for innovation through consulting startups.

Data Engineering 52

Data Engineering Data Engineer Engineering AWS 52

Edureka

FEBRUARY 9, 2023

Azure Data Engineering is a rapidly growing field that involves designing, building, and maintaining data processing systems using Microsoft Azure technologies. Proficiency in programming languages: Knowledge of programming languages such as Python and SQL is essential for Azure Data Engineers.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

ProjectPro

JUNE 29, 2021

Your search for Apache Kafka interview questions ends right here! Let us now dive directly into the Apache Kafka interview questions and answers and help you get started with your Big Data interview preparation! How to study for Kafka interview? What is Kafka used for? What are main APIs of Kafka?

Kafka 40

Kafka Bytes Big Data Java 40

ProjectPro

NOVEMBER 14, 2015

Hadoop projects make optimum use of ever-increasing parallel processing capabilities of processors and expanding storage spaces to deliver cost-effective, reliable solutions. Owned by Apache Software Foundation, Apache Spark is an open-source data processing framework. Why Apache Spark?

Hadoop 52

Hadoop Project Big Data Healthcare 52

ProjectPro

AUGUST 24, 2021

So, work on projects that guide you on how to build end-to-end ETL/ELT data pipelines. Big Data Tools: Without learning about popular big data tools, it is almost impossible to complete any task in data engineering. Finally, the data is published and visualized on a Java-based custom Dashboard.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

Edureka

FEBRUARY 9, 2023

Data engineers don’t just work with traditional data; they’re frequently tasked with handling massive amounts of data. A data engineer should be familiar with popular Big Data tools and technologies such as Hadoop, MongoDB, and Kafka.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Mining 52

ProjectPro

JANUARY 19, 2022

While data scientists are primarily concerned with machine learning, having a basic understanding of the ideas might help them better understand the demands of data scientists on their teams. 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

NOVEMBER 22, 2021

Python has a large library set, which is why the vast majority of data scientists and analytics specialists use it at a high level. If you are interested in landing a big data or Data Science job, mastering PySpark as a big data tool is necessary. Is PySpark a Big Data tool?

Hadoop 52

Hadoop Python Datasets Metadata 52

ProjectPro

AUGUST 11, 2021

ironSource has to collect and store vast amounts of data from millions of devices. ironSource started making use of Upsolver as its data lake for storing raw event data. Kafka streams, consisting of 500,000 events per second, get ingested into Upsolver and stored in AWS S3.

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

ProjectPro

APRIL 27, 2016

Innovations on Big Data technologies and Hadoop i.e. the Hadoop big data tools , let you pick the right ingredients from the data-store, organise them, and mix them. Now, thanks to a number of open source big data technology innovations, Hadoop implementation has become much more affordable.

Hadoop 40

Hadoop Big Data Technology Big Data Tools 40

ProjectPro

JUNE 24, 2021

Here are a few reasons why you should work on data analytics projects: Data analytics projects for grad students can help them learn big data analytics by doing instead of just gaining theoretical knowledge. Zeppelin allows individuals or teams to engage in data visualization on a collaborative basis.

Data Analytics 40

Data Analytics Project Insurance Hadoop 40

ProjectPro

AUGUST 26, 2016

Apache Spark is the most active open big data tool reshaping the big data market and has reached the tipping point in 2015.Wikibon Wikibon analysts predict that Apache Spark will account for one third (37%) of all the big data spending in 2022. Spark is based on the idea of data locality.

Hadoop 40

Hadoop Big Data Datasets Scala 40

ProjectPro

APRIL 15, 2016

Apache Pig differs from SQL in its usage for ETL, lazy evaluation, store data at any given point of time in the pipeline, support for pipeline splits and explicit declaration of execution plans. SQL has no in-built mechanism for splitting a data processing stream and applying different operators to each sub-stream.

Hadoop 40

Hadoop Java Big Data SQL 40

ProjectPro

AUGUST 21, 2015

Big Data Hadoop Interview Questions and Answers These are Hadoop Basic Interview Questions and Answers for freshers and experienced. Hadoop vs RDBMS Criteria Hadoop RDBMS Datatypes Processes semi-structured and unstructured data. Processes structured data. Best suited for OLTP and complex ACID transactions.

Hadoop 40

Hadoop Big Data Metadata Java 40

ProjectPro

JULY 27, 2021

Top 100+ Data Engineer Interview Questions and Answers The following sections consist of the top 100+ data engineer interview questions divided based on big data fundamentals, big data tools/technologies, and big data cloud computing platforms. Hadoop is highly scalable.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

ProjectPro

MAY 31, 2021

Ace your big data interview by adding some unique and exciting Big Data projects to your portfolio. 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.

Big Data 52

Big Data Coding Project Hadoop 52

ProjectPro

APRIL 1, 2017

Source : [link] ) Big Data Tool For Trump’s Big Government Immigration Plans. Source : [link] Monetizing big data with Hadoop as a Service: SAP’s story.SiliconAngle.com, March 15, 2017.

Hadoop 40

Hadoop Data Lake Electronics Big Data 40