Knowledge Hut

DECEMBER 21, 2023

What is Data Engineering? Data engineering is the method to collect, process, validate and store data. It involves building and maintaining data pipelines, databases, and data warehouses. The purpose of data engineering is to analyze data and make decisions easier.

Data Engineering 52

Data Engineering Data Engineer Engineering MongoDB 52

Edureka

JUNE 1, 2023

Without spending a lot of money on hardware, it is possible to acquire virtual machines and install software to manage data replication, distributed file systems, and entire big data ecosystems. By migrating to an AWS-powered solution, GERE improved deployment frequency, achieved 99.9

AWS 52

AWS Data Analytics Cloud Amazon Web Services 52

AltexSoft

JUNE 26, 2023

Find sources of relevant data. Choose data collection methods and tools. Decide on a sufficient data amount. Set up data storage technology. Below, we’ll elaborate on each step one by one and share our experience of data collection. From here, you’ll have to take the next steps.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

ProjectPro

FEBRUARY 8, 2017

The need for speed to use Hadoop for sentiment analysis and machine learning has fuelled the growth of hadoop based data stores like Kudu and adoption of faster databases like MemSQL and Exasol. 2) Big Data is no longer just Hadoop A common misconception is that Big Data and Hadoop are synonymous.

Big Data 40

Big Data Hadoop Data Lake Machine Learning 40

ProjectPro

JUNE 4, 2015

Big data applications using Apache Hadoop continue to run even if any of the individual cluster or server fails owing to the robust and stable nature of Hadoop. Table of Contents Big Data Hadoop Training Videos- What is Hadoop and its popular vendors? Hive makes querying faster through indexing.

Hadoop 52

Hadoop Architecture IT Java 52