Knowledge Hut

JULY 27, 2023

To ensure effective data processing and analytics for enterprises, work with data analysts, data scientists, and other stakeholders to optimize data storage and retrieval. Using the Hadoop framework, Hadoop developers create scalable, fault-tolerant Big Data applications. What do they do?

Hadoop 52

Hadoop Programming Language Banking Scala 52

U-Next

JUNE 29, 2022

Preparing data for analysis is known as extract, transform and load (ETL). While the ETL workflow is becoming obsolete, it still serves as a common word for the data preparation layers in a big data ecosystem. Working with large amounts of data necessitates more preparation than working with less data.

Big Data 40

Big Data Big Data Ecosystem Data Lake Raw Data 40

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. AWS Data Analytics Services AWS provides thorough, safe, scalable, and economical data analytics services.

AWS 52

AWS Data Analytics Cloud Amazon Web Services 52

Knowledge Hut

DECEMBER 21, 2023

The primary process comprises gathering data from multiple sources, storing it in a database to handle vast quantities of information, cleaning it for further use and presenting it in a comprehensible manner. Data engineering involves a lot of technical skills like Python, Java, and SQL (Structured Query Language).

Data Engineering 52

Data Engineering Data Engineer Engineering MongoDB 52

phData: Data Engineering

JANUARY 3, 2022

This involves: Building data pipelines and efficiently storing data for tools that need to query the data. Analyzing the data, ensuring it adheres to data governance rules and regulations. Understanding the pros and cons of data storage and query options. This is not a simple task.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Governance 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

Organizations focus on security of the centralized hadoop based data lakes by replacing the practice of dumping raw log files containing sensitive information with encryption of all long term data storage and systematic data classification procedures.

Big Data 40

Big Data Hadoop Data Lake Data Governance 40