AltexSoft

OCTOBER 8, 2021

The tool supports all sorts of data loading and processing: real-time, batch, streaming (using Spark), etc. 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.

Data Integration 52

Data Integration Hadoop Data Warehouse Data Lake 52

ProjectPro

SEPTEMBER 26, 2021

You must have good knowledge of the SQL and NoSQL database systems. NoSQL databases are also gaining popularity owing to the additional capabilities offered by such databases. ETL Tools: Extract, Transfer, and Load (ETL) pulls data from numerous sources and applies specific rules on the data sets as per the business requirements.

Big Data 52

Big Data Data Engineering Data Engineer Engineering 52

Knowledge Hut

NOVEMBER 28, 2023

Traditional data transformation tools are still relevant today, while next-generation Kafka, cloud-based tools, and SQL are on the rise for 2023. NoSQL If you think that Hadoop doesn't matter as you have moved to the cloud, you must think again. Knowledge of requirements and knowledge of machine learning libraries.

Data Engineering 52

Data Engineering Data Engineer Engineering Generalist 52

Knowledge Hut

NOVEMBER 19, 2023

Open Source Support: Many Azure services support popular open-source frameworks like Apache Spark, Kafka, and Hadoop, providing flexibility for data engineering tasks. Top 10 Azure Data Engineer Tools I have compiled a list of the most useful Azure Data Engineer Tools here, please find them below.

Data Engineering 52

Data Engineering Data Engineer Engineering PostgreSQL 52

ProjectPro

JUNE 23, 2016

Hadoop job interview is a tough road to cross with many pitfalls, that can make good opportunities fall off the edge. One, often over-looked part of Hadoop job interview is - thorough preparation. Needless to say, you are confident that you are going to nail this Hadoop job interview. directly into HDFS or Hive or HBase.

Hadoop 40

Hadoop MySQL Relational Database Java 40

Edureka

FEBRUARY 7, 2023

One can use polybase: From Azure SQL Database or Azure Synapse Analytics, query data kept in Hadoop, Azure Blob Storage, or Azure Data Lake Store. Use a few straightforward T-SQL queries to import data from Hadoop, Azure Blob Storage, or Azure Data Lake Store without having to install a third-party ETL tool.

Data Engineering 52

Data Engineering Data Engineer Engineering Hadoop 52

ProjectPro

JUNE 2, 2015

Before organizations rely on data driven decision making, it is important for them to have a good processing power like Hadoop in place for data processing. Thus, organizations must make use of effective ETL tools to ease the process of data preparation that requires a less complex IT infrastructure.

Big Data 40

Big Data Hadoop Banking Data Analytics 40

Knowledge Hut

MAY 9, 2024

Skills Required Data architects must be proficient in programming languages such as Python, Java, and C++, Hadoop and NoSQL databases, predictive modeling, and data mining, and experience with data modeling tools like Visio and ERWin. Average Annual Salary of Data Architect On average, a data architect makes $165,583 annually.

Data Science 52

Data Science Data Architect Data Mining Programming Language 52

ProjectPro

JULY 27, 2021

Data architects require practical skills with data management tools including data modeling, ETL tools, and data warehousing. How does Network File System (NFS) differ from Hadoop Distributed File System (HDFS)? Network File System Hadoop Distributed File System NFS can store and process only small volumes of data.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

ProjectPro

JANUARY 19, 2022

ETL (extract, transform, and load) techniques move data from databases and other systems into a single hub, such as a data warehouse. Get familiar with popular ETL tools like Xplenty, Stitch, Alooma, etc. Hadoop, MongoDB, and Kafka are popular Big Data tools and technologies a data engineer needs to be familiar with.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Storage 52