Knowledge Hut

DECEMBER 29, 2023

A Data Engineer is someone proficient in a variety of programming languages and frameworks, such as Python, SQL, Scala, Hadoop, Spark, etc. One of the primary focuses of a Data Engineer's work is on the Hadoop data lakes. NoSQL databases are often implemented as a component of data pipelines.

Data Science 98

Data Science Data Mining Deep Learning Programming Language 98

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

Most of the big data certification initiatives come from the industry with the intent to establish equilibrium between the supply and demand for skilled big data professionals. Below are the top big data certifications that are worth paying attention to in 2016, if you are planning to get trained in a big data technology.

Big Data 40

Big Data Certification Hadoop Big Data Skills 40

Knowledge Hut

JUNE 23, 2023

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. Other Competencies You should have proficiency in coding languages like SQL, NoSQL, Python, Java, R, and Scala.

Data Engineering 52

Data Engineering Data Engineer Engineering NoSQL 52

Edureka

FEBRUARY 9, 2023

As the demand for data engineers grows, having a well-written resume that stands out from the crowd is critical. Azure data engineers are essential in the design, implementation, and upkeep of cloud-based data solutions. Write UDFs in Scala and PySpark to meet specific business requirements.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

Knowledge Hut

SEPTEMBER 26, 2023

We as Azure Data Engineers should have extensive knowledge of data modelling and ETL (extract, transform, load) procedures in addition to extensive expertise in creating and managing data pipelines, data lakes, and data warehouses. Find out what makes on-premises and cloud data solutions different.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

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. Soft skills for data engineering Problem solving using data-driven methods It’s key to have a data-driven approach to problem-solving. Rely on the real information to guide you.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Knowledge Hut

SEPTEMBER 26, 2023

Language Compatibility: Databricks provides extensive language compatibility, catering to data professionals with diverse skill sets. Some of the prominent languages supported include: Scala: Ideal for developers who want to leverage the full power of Apache Spark. However, its primary focus is on data warehousing and analytics.

Data Lake 52

Data Lake Database-centric Machine Learning Pipeline-centric 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. Different methods are used to store different types of data.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Storage 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 31, 2022

The cloud is the only platform to handle today's colossal data volumes because of its flexibility and scalability. Launched in 2014, Snowflake is one of the most popular cloud data solutions on the market. Snowflake is not based on existing database systems or big data software platforms like Hadoop.

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52