Edureka

MARCH 5, 2024

In other words, full stack developers are proficient in both the technologies that power what users see and interact within their web browsers, as well as the technologies that handle data storage, user authentication, and server-side processing behind the scenes. The MERN stack comprises MongoDB, Express.js, React.js, and Node.js.

MongoDB 40

MongoDB PostgreSQL MySQL Java 40

Knowledge Hut

SEPTEMBER 6, 2023

Monitor and optimize operational resources in Azure SQL Optimize query performance in Azure SQL Automate database tasks for Azure SQL Plan and implement a high availability and disaster recovery environment. Skills acquired : Core data concepts. Concept of structured, semi-structured, and unstructured data.

Database 52

Database Certification MongoDB MySQL 52

Knowledge Hut

APRIL 25, 2024

Create data storage and acceptance solutions for websites, especially those that take payments. Knowledge of Databases When working on a project, you must realize that data storage is essential since they contain a lot of information. Therefore, developers employ MySQL, SQL, PostgreSQL, MongoDB, etc.,

Programming Language 98

Programming Language Java Algorithm MySQL 98

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

Knowledge Hut

MAY 31, 2023

Some of the most important lists of database project examples using MySQL are: Online Job Portal using Python and SQL database An online job portal is a platform that connects job seekers with potential employers. Here is a link to source codes for Online Job Portal using Python and SQL databases.

Database 52

Database Coding MongoDB Project 52

ProjectPro

NOVEMBER 5, 2014

Hadoop is the way to go for organizations that do not want to add load to their primary storage system and want to write distributed jobs that perform well. MongoDB NoSQL database is used in the big data stack for storing and retrieving one item at a time from large datasets whereas Hadoop is used for processing these large data sets.

MongoDB 40

MongoDB Hadoop NoSQL Big Data 40

Monte Carlo

NOVEMBER 20, 2023

But as businesses pivot and technologies advance, data migrations are—regrettably—unavoidable. Much like a chess grandmaster contemplating his next play, data migrations are a strategic move. A good data storage migration ensures data integrity, platform compatibility, and future relevance.

MongoDB 52

MongoDB ETL Tools Database Data 52

DareData

JANUARY 30, 2023

In this post, we'll discuss some key data engineering concepts that data scientists should be familiar with, in order to be more effective in their roles. These concepts include concepts like data pipelines, data storage and retrieval, data orchestrators or infrastructure-as-code.

Data Engineering 52

Data Engineering Data Engineer NoSQL Engineering 52

Knowledge Hut

JULY 26, 2023

MongoDB): MongoDB is a prominent database software that comes under the category of "document store" databases. Document store databases, such as MongoDB, are intended to store and manage data that is unstructured or semi-structured, such as documents. Database Software- Document Store (e.g.-MongoDB):

Database 52

Database NoSQL Telecommunication MongoDB 52

Edureka

MARCH 5, 2024

Among the well-liked tech stacks are: Mean Stack: MongoDB : A NoSQL database that is adaptable and scalable for managing massive volumes of data because it stores data in a format resembling JSON. MERN Stack: MongoDB: MongoDB is used for data storage, just like in the MEAN stack. They make use of SQL.

MySQL 40

MySQL MongoDB NoSQL PostgreSQL 40

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. Microsoft SQL Server Relational database managed by Microsoft. MongoDB Most popular NoSQL database. Go A general-purpose programming language by Google.

MongoDB 98

MongoDB Programming Language Java Relational Database 98

Knowledge Hut

NOVEMBER 17, 2023

Here is a step-by-step guide on how to become an Azure Data Engineer: 1. Understanding SQL You must be able to write and optimize SQL queries because you will be dealing with enormous datasets as an Azure Data Engineer. You should possess a strong understanding of data structures and algorithms.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

Rockset

SEPTEMBER 13, 2022

Rather than individual, transactional updates from your application clients, Rockset is designed for continuous, streaming ingestion from your primary data store. It has direct connectors for a number of primary data stores, including DynamoDB, MongoDB, Kafka, and many relational databases.

SQL 52

SQL Database Relational Database AWS 52

Knowledge Hut

DECEMBER 26, 2023

According to the World Economic Forum, the amount of data generated per day will reach 463 exabytes (1 exabyte = 10 9 gigabytes) globally by the year 2025. Certain roles like Data Scientists require a good knowledge of coding compared to other roles. In other words, they develop, maintain, and test Big Data solutions.

Data Science 97

Data Science BI Business Intelligence Data Mining 97

Knowledge Hut

APRIL 25, 2023

It allows data engineers to easily build and customize data models and create interactive dashboards and reports. Looker also provides an SQL-based interface for querying and analyzing data, which makes it easy for data engineers to integrate with existing tools and applications.

Data Engineering 52

Data Engineering Data Engineer Engineering Google Cloud 52

Knowledge Hut

MARCH 27, 2024

Real-time analytics platforms in big data apply logic and math to gain faster insights into data, resulting in a more streamlined and informed decision-making process. Some open-source technology for big data analytics are : Hadoop. Easily scales up to a large amount of data when it is distributed in small chunks.

Big Data 52

Big Data Data Analytics MongoDB Big Data Tools 52

Cloud Academy

JANUARY 27, 2022

Let’s review some of the big picture concepts as well finer details about being a data engineer. What does a data engineer do – the big picture Data engineers will often be dealing with raw data. They need to understand common data formats and interfaces, and the pros and cons of different storage options.

Data Engineering 52

Data Engineering Data Engineer Certification Engineering 52

Knowledge Hut

DECEMBER 21, 2023

HIVE Hive is an open-source data warehousing Hadoop tool that helps manage huge dataset files. Hive can run queries like SQL, known as HQL or Hive Query Language. Features: It uses queries that are similar to those of SQL. There are built-in functions used for data mining and other related works. Hive has high latency.

Hadoop 52

Hadoop Big Data NoSQL Unstructured Data 52

Edureka

FEBRUARY 9, 2023

In this blog on “Azure data engineer skills”, you will discover the secrets to success in Azure data engineering with expert tips, tricks, and best practices Furthermore, a solid understanding of big data technologies such as Hadoop, Spark, and SQL Server is required.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Mining 52

Ascend.io

SEPTEMBER 14, 2023

Read More: Data Automation Engineer: Skills, Workflow, and Business Impact Python for Data Engineering Versus SQL, Java, and Scala When diving into the domain of data engineering, understanding the strengths and weaknesses of your chosen programming language is essential. Compiled, targeting the JVM.

Data Engineering 52

Data Engineering Data Engineer Python Engineering 52

AltexSoft

MAY 12, 2023

A fixed schema means the structure and organization of the data are predetermined and consistent. It is commonly stored in relational database management systems (DBMSs) such as SQL Server, Oracle, and MySQL, and is managed by data analysts and database administrators. Data durability and availability.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

ProjectPro

MARCH 19, 2015

As data processing requirements grow exponentially, NoSQL is a dynamic and cloud friendly approach to dynamically process unstructured data with ease.IT professionals often debate the merits of SQL vs. NoSQL but with increasing business data management needs, NoSQL is becoming the new darling of the big data movement.

NoSQL 49

NoSQL Big Data SQL Database-centric 49

Knowledge Hut

JANUARY 18, 2024

Full-stack data science is a method of ensuring the end-to-end application of this technology in the real world. For an organization, full-stack data science merges the concept of data mining with decision-making, data storage, and revenue generation.

Data Science 96

Data Science Computer Science Programming Language Machine Learning 96

Knowledge Hut

NOVEMBER 7, 2023

Applications of Cloud Computing in Data Storage and Backup Many computer engineers are continually attempting to improve the process of data backup. Previously, customers stored data on a collection of drives or tapes, which took hours to collect and move to the backup location.

Cloud Computing 98

Cloud Computing Cloud Amazon Web Services Entertainment 98

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. The most common language for data analysis is SQL but barebone Hadoop doesn’t support it. Hadoop tutorials and courses.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

Knowledge Hut

JANUARY 3, 2024

A normalization database or normalization in DBMS design method avoids data duplication and removes undesired traits like Insertion, Update, and Deletion Anomalies. SQL normalization serves the dual purpose of removing unnecessary (repetitive) data and ensuring logical data storage. Why do we Need normalization?

MongoDB 52

MongoDB Database Coding Utilities 52

Knowledge Hut

JUNE 23, 2023

You should have the expertise to collect data, conduct research, create models, and identify patterns. You should be well-versed with SQL Server, Oracle DB, MySQL, Excel, or any other data storing or processing software. You must develop predictive models to help industries and businesses make data-driven decisions.

Data Engineering 52

Data Engineering Data Engineer Engineering Non-relational Database 52

Knowledge Hut

SEPTEMBER 6, 2023

Once the data is tailored to your requirements, it then should be stored in a warehouse system, where it can be easily used by applying queries. Some of the most popular database management tools in the industry are NoSql, MongoDB and oracle. You will learn about Python, SQL, statistical modeling and data analysis.

Data Science 97

Data Science Certification Business Analyst Machine Learning 97

Knowledge Hut

FEBRUARY 2, 2024

Skills Required HTML, CSS, JavaScript or Python for Backend programming, Databases such as SQL, MongoDB, Git version control, JavaScript frameworks, etc. And what better solution than cloud storage?

Programming Language 98

Programming Language Amazon Web Services Cloud Computing Java 98

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

Rockset

MAY 10, 2022

However, DynamoDB, like many other NoSQL databases, is great for scalable data storage and single row retrieval but leaves a lot to be desired when it comes to analytics. With SQL databases, analysts can quickly join, group and search across historical data sets. Again, we could continue to use Rockset in this scenario.

NoSQL 52

NoSQL AWS MongoDB Datasets 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. They can be accumulated in NoSQL databases like MongoDB or Cassandra.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Rockset

SEPTEMBER 20, 2022

Image Source There are several companies that enable users to analyze on-chain data, such as Dune Analytics, Nansen, Ocean Protocol, and others. Many of these services, as well as the dApps they may support, are built on transactional (OLTP) databases such as PostgreSQL, DynamoDB, MongoDB and others.

PostgreSQL 52

PostgreSQL MongoDB SQL Datasets 52

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. Data storage and processing.

Big Data 78

Big Data Data Analytics IT NoSQL 78

ProjectPro

JANUARY 31, 2023

There are three steps involved in the deployment of a big data model: Data Ingestion: This is the first step in deploying a big data model - Data ingestion, i.e., extracting data from multiple data sources. Data Variety Hadoop stores structured, semi-structured and unstructured data.

Big Data 52

Big Data Hadoop AWS Relational Database 52

Data Science Blog: Data Engineering

SEPTEMBER 24, 2021

This ensures that all data in the database is valid even if we execute big transactions which include multiple statements (e. SQL) composed into one transaction updating many data rows in the database. Redis, CouchDB, MongoDB, Cosmos DB, Cassandra, ElasticSearch, Neo4J, OrientDB or ArangoDB are just some popular examples.

NoSQL 52

NoSQL Data Warehouse Database MongoDB 52

Knowledge Hut

JUNE 30, 2023

Microsoft SQL Server: What is DBMS in SQL? 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. Some of the popular examples include Oracle, MySQL, and Microsoft SQL Server.

MySQL 52

MySQL Medical Relational Database Healthcare 52