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 Machine Learning Business Intelligence 97

ProjectPro

JANUARY 19, 2022

Knowledge of popular big data tools like Apache Spark, Apache Hadoop, etc. Good communication skills as a data engineer directly works with the different teams. Learning Resources: How to Become a GCP Data Engineer How to Become a Azure Data Engineer How to Become a Aws Data Engineer 6.

Data Engineer 52

Data Engineer Data Engineering Engineering Amazon Web Services 52

ProjectPro

OCTOBER 5, 2018

Microsoft has announced the addition of new connectors which will allow businesses to use SQL server to query other databases like MongoDB, Oracle, and Teradata. This will make Microsoft SQL server into a virtual integration layer where the data will never have to be replicated or moved to the SQL server. September 24, 2018.

Hadoop 40

Hadoop BI Big Data MongoDB 40

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 Engineer 52

Data Engineer Data Engineering Engineering Data Mining 52

Edureka

AUGUST 23, 2024

Amazon Web Service (AWS) offers the Amazon Kinesis service to process a vast amount of data, including, but not limited to, audio, video, website clickstreams, application logs, and IoT telemetry, every second in real-time. Compared to Big Data tools, Amazon Kinesis is automated and fully managed.

AWS 52

AWS Kafka Amazon Web Services Medical 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. MongoDB stores the processed and aggregated results.

Data Engineer 52

Data Engineer Data Engineering Coding Project 52

Knowledge Hut

NOVEMBER 17, 2023

Data engineers must therefore have a thorough understanding of programming languages like Python, Java, or Scala. Candidates looking for Azure data engineering positions should also be familiar with big data tools like Hadoop.

Data Engineer 52

Data Engineer Data Engineering Engineering Scala 52

Knowledge Hut

SEPTEMBER 26, 2023

Using scripts, data engineers ought to be able to automate routine tasks. Data engineers handle vast volumes of data on a regular basis and don't only deal with normal data. Popular Big Data tools and technologies that a data engineer has to be familiar with include Hadoop, MongoDB, and Kafka.

Certification 52

Certification Data Engineer Data Engineering Engineering 52

Knowledge Hut

SEPTEMBER 6, 2023

Problem-Solving Abilities: Many certification courses provide projects and assessments which require hands-on practice of big data tools which enhances your problem solving capabilities. Networking Opportunities: While pursuing big data certification course you are likely to interact with trainers and other data professionals.

Big Data 52

Big Data Certification Hadoop Kafka 52

Knowledge Hut

JUNE 23, 2023

You should be thorough with technicalities related to relational and non-relational databases, Data security, ETL (extract, transform, and load) systems, Data storage, automation and scripting, big data tools, and machine learning. You can also post your work on your LinkedIn profile.

Data Engineer 52

Data Engineer Data Engineering Engineering NoSQL 52

AltexSoft

JUNE 26, 2023

Semi-structured data is not as strictly formatted as tabular one, yet it preserves identifiable elements — like tags and other markers — that simplify the search. They can be accumulated in NoSQL databases like MongoDB or Cassandra. Unstructured data represents up to 80-90 percent of the entire datasphere. No wonder only 0.5

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Knowledge Hut

MARCH 5, 2024

Let us look at some of the functions of Data Engineers: They formulate data flows and pipelines Data Engineers create structures and storage databases to store the accumulated data, which requires them to be adept at core technical skills, like design, scripting, automation, programming, big data tools , etc.

Data Engineer 52

Data Engineer Data Engineering Engineering Education 52

Knowledge Hut

JUNE 20, 2023

The ML engineers act as a bridge between software engineering and data science. They take raw data from the pipelines and enhance programming frameworks using the big data tools that are now accessible. They transform unstructured data into scalable models for data science.

Machine Learning 52

Machine Learning Data Engineer Data Engineering Engineering 52

ProjectPro

DECEMBER 7, 2021

In addition, to extract data from the eCommerce website, you need experts familiar with databases like MongoDB that store reviews of customers. AWS Glue You can easily extract and load your data for analytics using the fully managed extract, transform, and load (ETL) service AWS Glue.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 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 Engineer 52

Data Engineer Data Engineering Engineering Data Storage 52

ProjectPro

JANUARY 31, 2023

The end of a data block points to the location of the next chunk of data blocks. DataNodes store data blocks, whereas NameNodes store these data blocks. Learn more about Big Data Tools and Technologies with Innovative and Exciting Big Data Projects Examples. Steps for Data preparation.

Big Data 52

Big Data Hadoop Relational Database AWS 52

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 Engineer 52

Data Engineer Data Engineering Engineering AWS 52

ProjectPro

NOVEMBER 14, 2015

Tools/Tech stack used: The tools and technologies used for such healthcare data management using Apache Hadoop are MapReduce and MongoDB. In this project, you will work on preparing a real-time analytics dashboard using popular Big Data tools.

Hadoop 52

Hadoop Project Big Data Healthcare 52

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.

Data Engineer 40

Data Engineer Data Engineering Engineering Hadoop 40