AltexSoft

FEBRUARY 11, 2023

This suggests that today, there are many companies that face the need to make their data easily accessible, cleaned up, and regularly updated. Hiring a well-skilled data architect can be very helpful for that purpose. What is a data architect? Let’s discuss and compare them to avoid misconceptions.

Data Architect 87

Data Architect Certification Generalist Big Data 87

Knowledge Hut

JULY 27, 2023

The interesting world of big data and its effect on wage patterns, particularly in the field of Hadoop development, will be covered in this guide. As the need for knowledgeable Hadoop engineers increases, so does the debate about salaries. You can opt for Big Data training online to learn about Hadoop and big data.

Hadoop 52

Hadoop Programming Language Banking Scala 52

Knowledge Hut

DECEMBER 26, 2023

They are also accountable for communicating data trends. Let us now look at the three major roles of data engineers. Generalists They are typically responsible for every step of the data processing, starting from managing and making analysis and are usually part of small data-focused teams or small companies.

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

Knowledge Hut

DECEMBER 21, 2023

Data engineering involves a lot of technical skills like Python, Java, and SQL (Structured Query Language). For a data engineer career, you must have knowledge of data storage and processing technologies like Hadoop, Spark, and NoSQL databases. Knowledge of Hadoop, Spark, and Kafka.

Data Engineering 52

Data Engineering Data Engineer Engineering MongoDB 52

ProjectPro

APRIL 1, 2016

News on Hadoop- March 2016 Hortonworks makes its core more stable for Hadoop users. PCWorld.com Hortonworks is going a step further in making Hadoop more reliable when it comes to enterprise adoption. Hortonworks Data Platform 2.4, Source: [link] ) Syncsort makes Hadoop and Spark available in native Mainframe.

Hadoop 52

Hadoop BI Big Data Big Data Tools 52

AltexSoft

MAY 12, 2023

Without a fixed schema, the data can vary in structure and organization. File systems, data lakes, and Big Data processing frameworks like Hadoop and Spark are often utilized for managing and analyzing unstructured data. Amazon S3, Google Cloud Storage, Microsoft Azure Blob Storage), NoSQL databases (e.g.,

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

ProjectPro

JANUARY 31, 2023

Data Storage: The next step after data ingestion is to store it in HDFS or a NoSQL database such as HBase. HBase storage is ideal for random read/write operations, whereas HDFS is designed for sequential processes. Data Processing: This is the final step in deploying a big data model.

Big Data 52

Big Data Hadoop AWS Relational Database 52