Knowledge Hut

DECEMBER 26, 2023

Let’s say you are working Node.js, and you need to connect to MongoDB. To be able to work with MongoDB in Node.js you need to have MongoDB driver for Node.js. ii) Databases MySQL Most popular open-source relational database. Microsoft SQL Server Relational database managed by Microsoft.

MongoDB 98

MongoDB Programming Language Java Relational Database 98

Knowledge Hut

JUNE 30, 2023

Developed by the famous tech giant Microsoft, SQL Server is a durable DBMS that offers a vast range of features for the management of relational databases. They are used to organize data into different tables, which consist of rows and columns, and follow a relational model. Microsoft SQL Server: What is DBMS in SQL?

MySQL 52

MySQL Medical Relational Database Healthcare 52

Knowledge Hut

SEPTEMBER 6, 2023

This is an entry-level database certification, and it is a stepping stone for other role-based data-focused certifications, like Azure Data Engineer Associate, Azure Database Administrator Associate, Azure Developer Associate, or Power BI Data Analyst Associate. Skills acquired : Core data concepts.

Database 52

Database Certification MongoDB MySQL 52

Edureka

FEBRUARY 9, 2023

Here are some role-specific skills to consider if you want to become an Azure data engineer: Programming languages are used in the majority of data storage and processing systems. Data engineers must be well-versed in programming languages such as Python, Java, and Scala.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Mining 52

ProjectPro

JANUARY 31, 2023

Big Data is a collection of large and complex semi-structured and unstructured data sets that have the potential to deliver actionable insights using traditional data management tools. Big data operations require specialized tools and techniques since a relational database cannot manage such a large amount of data.

Big Data 52

Big Data Hadoop AWS Relational Database 52

ProjectPro

JANUARY 19, 2022

Here are some role-specific skills you should consider to become an Azure data engineer- Most data storage and processing systems use programming languages. Data engineers must thoroughly understand programming languages such as Python, Java, or Scala. Who should take the certification exam?

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

Knowledge Hut

DECEMBER 19, 2023

It is seeing its utility and application grow as businesses envisage growth in the market and operations within. Java has become the go-to language for mobile development, backend development, cloud-based solutions, and other trending technologies like IoT and Big Data.

Java 98

Java Programming Language Architecture Database 98

ProjectPro

JULY 30, 2021

There are many cloud computing job roles like Cloud Consultant, Cloud reliability engineer, cloud security engineer, cloud infrastructure engineer, cloud architect, data science engineer that one can make a career transition to. PaaS packages the platform for development and testing along with data, storage, and computing capability.

Cloud Computing 40

Cloud Computing Cloud Amazon Web Services AWS 40

ProjectPro

JULY 27, 2021

Complex algorithms, specialized professionals, and high-end technologies are required to leverage big data in businesses, and big Data Engineering ensures that organizations can utilize the power of data. Differentiate between relational and non-relational database management systems.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

ProjectPro

NOVEMBER 14, 2015

Big data has taken over many aspects of our lives and as it continues to grow and expand, big data is creating the need for better and faster data storage and analysis. These Apache Hadoop projects are mostly into migration, integration, scalability, data analytics, and streaming analysis. Data Integration 3.Scalability

Hadoop 52

Hadoop Project Big Data Healthcare 52

AltexSoft

JULY 29, 2022

No matter the actual size, each cluster accommodates three functional layers — Hadoop distributed file systems for data storage, Hadoop MapReduce for processing, and Hadoop Yarn for resource management. Today, Hadoop which combines data storage and processing capabilities remains a basis for many Big Data projects.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

AltexSoft

MAY 14, 2021

A growing number of companies now use this data to uncover meaningful insights and improve their decision-making, but they can’t store and process it by the means of traditional data storage and processing units. Key Big Data characteristics. And most of this data has to be handled in real-time or near real-time.

Big Data 78

Big Data Data Analytics IT NoSQL 78

Cloudera

DECEMBER 12, 2018

I would like to start off by asking you to tell us about your background and what kicked off your 20-year career in relational database technology? Greg Rahn: I first got introduced to SQL relational database systems while I was in undergrad. So, that’s kind of how I got introduced to databases and SQL systems.

Data Warehouse 42

Data Warehouse Relational Database Hadoop BI 42

AltexSoft

MAY 12, 2023

Structured data is formatted in tables, rows, and columns, following a well-defined, fixed schema with specific data types, relationships, and rules. A fixed schema means the structure and organization of the data are predetermined and consistent. Without a fixed schema, the data can vary in structure and organization.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

U-Next

AUGUST 10, 2022

Model Building and Pattern Recognition: Data Engineers utilize a descriptive data model to derive contextual information from data aggregation. Nevertheless, it will help you in your work as a Data Engineer if you understand how data may be utilized for statistical data processing and modeling.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Science 52

AltexSoft

MARCH 14, 2023

According to a recent Matillion and IDG Research survey , the average number of data sources per organization is 400. Moreover, over 20 percent of surveyed companies were found to be utilizing 1,000 or more data sources to provide data to analytics systems. Some popular databases are Postgres and MongoDB.

IT 59

IT Data Warehouse Data Governance Data Lake 59