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

NOVEMBER 17, 2023

Azure Data Factory, Azure Databricks, Azure Synapse Analytics, Azure Storage, Azure Data Lake, Azure Blob Storage, Azure Cosmos DB, Azure Stream Analytics, Azure HDInsight, and other Azure data services are just a few of the many Azure data services that Azure data engineers deal with.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

Edureka

FEBRUARY 9, 2023

In this blog on “Azure data engineer skills”, you will discover the secrets to success in Azure data engineering with expert tips, tricks, and best practices Furthermore, a solid understanding of big data technologies such as Hadoop, Spark, and SQL Server is required.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Mining 52

ProjectPro

MARCH 7, 2016

If your career goals are headed towards Big Data, then 2016 is the best time to hone your skills in the direction, by obtaining one or more of the big data certifications. Acquiring big data analytics certifications in specific big data technologies can help a candidate improve their possibilities of getting hired.

Big Data 40

Big Data Certification Hadoop Big Data Skills 40

Knowledge Hut

JUNE 23, 2023

You should be well-versed in Python and R, which are beneficial in various data-related operations. Apache Hadoop-based analytics to compute distributed processing and storage against datasets. Machine learning will link your work with data scientists, assisting them with statistical analysis and modeling. What is Data Modeling?

Data Engineering 52

Data Engineering Data Engineer Engineering NoSQL 52

Knowledge Hut

DECEMBER 13, 2023

The company's focus on data is to make sure it is simple and accessible with scaled insights while being built on a stable foundation. It comes as no surprise that IBM, one of the biggest tech corporations in the world, develops big data solutions for its clients. This tool can process up to 80 terabytes of data.

Big Data 52

Big Data Consulting Hadoop Amazon Web Services 52

Knowledge Hut

SEPTEMBER 26, 2023

Additionally, we must be aware of how data systems have developed and helped data professionals. Find out what makes on-premises and cloud data solutions different. A data engineer has to be well-versed in both the duties of the field and the related sector.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Databand.ai

DECEMBER 13, 2022

Follow Charles on LinkedIn 3) Deepak Goyal Azure Instructor at Microsoft Deepak is a certified big data and Azure Cloud Solution Architect with more than 13 years of experience in the IT industry. 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

JANUARY 19, 2022

A data engineer should be aware of how the data landscape is changing. They should also be mindful of how data systems have evolved and benefited data professionals. Explore the distinctions between on-premises and cloud data solutions. Get familiar with popular ETL tools like Xplenty, Stitch, Alooma, etc.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Storage 52

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

News on Hadoop-March 2017 The cloud is disrupting Hadoop. Zdnet.com, March 6, 2017 Forrester estimates that organizations will spend $800 million in hadoop and its related services in 2017. Just like Hadoop is not designed for the cloud, it is not meant for doing matrix math that deep learning requires.

Hadoop 40

Hadoop Data Lake Electronics Big Data 40