ProjectPro

MARCH 19, 2015

Relational Databases – The fundamental concept behind databases, namely MySQL, Oracle Express Edition, and MS-SQL that uses SQL, is that they are all Relational Database Management Systems that make use of relations (generally referred to as tables) for storing data.

NoSQL 49

NoSQL Big Data SQL Database-centric 49

Knowledge Hut

DECEMBER 21, 2023

With the help of Hadoop big data tools, organizations can make decisions that will be based on the analysis of multiple datasets and variables, and not just small samples or anecdotal incidents. HIVE Hive is an open-source data warehousing Hadoop tool that helps manage huge dataset files. NoSQL databases can handle node failures.

Hadoop 52

Hadoop Big Data NoSQL Unstructured Data 52

Cloud Academy

JANUARY 27, 2022

These fundamentals will give you a solid foundation in data and datasets. Knowing SQL means you are familiar with the different relational databases available, their functions, and the syntax they use. MongoDB Configuration and Setup Watch an example of deploying MongoDB to understand its benefits as a database system.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Edureka

OCTOBER 10, 2024

Databases: The most used relational database platforms, such as SQL Server, Oracle, MySQL, and PostgreSQL databases, are recognized both as source and sink platforms. Also integrated are the cloud-based databases, such as the Amazon RDS for Oracle and SQL Server and Google Big Query, to name but a few. BlobSource).

MongoDB 40

MongoDB NoSQL Metadata Datasets 40

Knowledge Hut

DECEMBER 21, 2023

Postico can be used by business analysts, software developers, business owners in varied industries like healthcare, finance, and marketing to design new databases, data entries, importing CSV datasets and more. Navicat Navicat is a GUI for MySQL, PostgreSQL, Oracle, and MongoDB. The UI of TablePlus is a simple UI.

PostgreSQL 52

PostgreSQL MySQL MongoDB SQL 52

AltexSoft

JUNE 26, 2023

Data collection is a methodical practice aimed at acquiring meaningful information to build a consistent and complete dataset for a specific business purpose — such as decision-making, answering research questions, or strategic planning. They can be accumulated in NoSQL databases like MongoDB or Cassandra. No wonder only 0.5

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

ProjectPro

JANUARY 31, 2023

Big data operations require specialized tools and techniques since a relational database cannot manage such a large amount of data. MapReduce is a Hadoop framework used for processing large datasets. Another name for it is a programming model that enables us to process big datasets across computer clusters.

Big Data 52

Big Data Hadoop Relational Database AWS 52

Knowledge Hut

JUNE 23, 2023

Data architecture to tackle datasets and the relationship between processes and applications. Coding helps you link your database and work with all programming languages. You should be well-versed in Python and R, which are beneficial in various data-related operations. You can also post your work on your LinkedIn profile.

Data Engineering 52

Data Engineering Data Engineer Engineering NoSQL 52

AltexSoft

MAY 12, 2023

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. Semi-structured data is typically stored in NoSQL databases, such as MongoDB, Cassandra, and Couchbase, following hierarchical or graph data models.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

U-Next

AUGUST 11, 2022

Many activities require you to interact with database management systems regularly. You may need to design a database, create datasets, map, order, and/or interlink key values. Depending on the data modelling need, you may need to work with relational databases (like MYSQL, db2 or PostgreSQL) or NoSQL databases (like MongoDB).

Data Science 40

Data Science Relational Database PostgreSQL MongoDB 40

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 Database 52

Knowledge Hut

NOVEMBER 17, 2023

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. To be an Azure Data Engineer, you must have a working knowledge of SQL (Structured Query Language), which is used to extract and manipulate data from relational databases.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

Knowledge Hut

JANUARY 9, 2024

3 Cloud Storage This unit covers cloud storage systems, their concepts, object storage (Ceph, OpenStack Swift, and Amazon S3), databases (DynamoDB, HBase, Cassandra, and MongoDB), and distributed file systems (Ceph FS and HDFS ). Additionally, students solve problems using AWS resources within a specific price limit.

Cloud Computing 52

Cloud Computing Cloud Amazon Web Services Cloud Storage 52

Rockset

AUGUST 2, 2023

This enrichment data has changing schemas and new data providers are constantly being added to enhance the insights, making it challenging for Windward to support using relational databases with strict schemas. They used MongoDB as their metadata store to capture vessel and company data.

Database-centric 52

Database-centric PostgreSQL Transportation Insurance 52

Rockset

FEBRUARY 22, 2024

In that way, it can handle similar applications as other databases you might have used, like MySQL, PostgreSQL, MongoDB , or Cassandra. For indexes on a relational database, the index will often contain a pointer to the primary key of the item being indexed.

Database 80

Database Relational Database Accessible Accessibility 80

ProjectPro

JANUARY 19, 2022

The first step is to work on cleaning it and eliminating the unwanted information in the dataset so that data analysts and data scientists can use it for analysis. Interact with the data scientists team and assist them in providing suitable datasets for analysis. These softwares allow editing and querying databases easily.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

ProjectPro

JANUARY 19, 2022

Relational and non-relational databases are among the most common data storage methods. Learning SQL is essential to comprehend the database and its structures. ETL (extract, transform, and load) techniques move data from databases and other systems into a single hub, such as a data warehouse.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Storage 52

Edureka

FEBRUARY 8, 2024

Use cases for memory-optimized instances include- Database Servers- Applications like relational databases benefit from the higher memory capacity to store and retrieve data efficiently. These databases often require high-speed storage to deliver fast read and write operations, making I-Series instances a suitable choice.

AWS 52

AWS NoSQL Deep Learning Machine Learning 52

AltexSoft

NOVEMBER 23, 2021

To join data together from non-relational databases and other unstructured sources, TIBCO has the built-in transformation engine doing all the jobs. For this purpose, make a comprehensive list of all datasets, applications, services, and systems producing information. Know your data sources.

Process 69

Process Data Lake Metadata Data Warehouse 69

ProjectPro

NOVEMBER 14, 2015

This failure of relational database management systems triggered organizations to move their data from RDBMS to Hadoop. Data migration from legacy systems to the cloud is a major use case in organizations that have been into relational databases. Data Integration 3.Scalability Scalability 4.Link Link Prediction 5.Cloud

Hadoop 52

Hadoop Project Big Data Healthcare 52

AltexSoft

OCTOBER 8, 2021

ODI has a wide array of connections to integrate with relational database management systems ( RDBMS) , cloud data warehouses, Hadoop, Spark , CRMs, B2B systems, while also supporting flat files, JSON, and XML formats. They include NoSQL databases (e.g., MongoDB), SQL databases (e.g., Pre-built connectors.

Data Integration 52

Data Integration Hadoop Data Warehouse Data Lake 52

ProjectPro

DECEMBER 7, 2021

It can also consist of simple or advanced processes like ETL (Extract, Transform and Load) or handle training datasets in machine learning applications. Data Pipeline Architecture An efficient data pipeline requires dedicated infrastructure; it has several components that help you process large datasets.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

AltexSoft

MARCH 14, 2023

Databases store key information that powers a company’s product, such as user data and product data. The ones that keep only relational data in a tabular format are called SQL or relational database management systems (RDBMSs). Some popular databases are Postgres and MongoDB.

IT 59

IT Data Warehouse Data Governance Data Lake 59

Rockset

SEPTEMBER 13, 2022

It has direct connectors for a number of primary data stores, including DynamoDB, MongoDB, Kafka, and many relational databases. As Rockset ingests data from your primary database, it then indexes your data in a Converged Index , which borrows concepts from: a row index, an inverted index, and a columnar index.

SQL 52

SQL Database Relational Database NoSQL 52

ProjectPro

JULY 27, 2021

Differentiate between relational and non-relational database management systems. Relational Database Management Systems (RDBMS) Non-relational Database Management Systems Relational Databases primarily work with structured data using SQL (Structured Query Language).

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

Knowledge Hut

SEPTEMBER 6, 2023

IBM Data Analyst Professional Certificate Introduction : IBM Data Analyst Professional Certificate helps you become proficient in applying different analytical techniques by analyzing real-world datasets, creating visualizations & interactive dashboards, and presenting reports to share findings of data analysis. It is a 13-course series.

Big Data 52

Big Data Certification Hadoop Kafka 52

ProjectPro

JULY 30, 2021

Apache Spark - Apache Spark is an open-source analytics engine that computes and processes large datasets. They get used in NoSQL databases like Redis, MongoDB, data warehousing. It backs up storage in a routine fashion without the hassle of Database administrators interfering.

Cloud Computing 40

Cloud Computing Cloud Amazon Web Services AWS 40

U-Next

AUGUST 10, 2022

Gather Information: Before beginning any database activity, information must be gathered from reliable sources. Data Engineers then store the processed datasets after creating a set of procedures. Without a solid understanding of SQL, you cannot administer an RDBMS (relational database management).

Data Engineering 52

Data Engineering Data Engineer Engineering Data Science 52

AltexSoft

JULY 29, 2022

Apache Hadoop is an open-source Java-based framework that relies on parallel processing and distributed storage for analyzing massive datasets. You can use the whole dataset for different analytical purposes again and again, but there is no way to edit or change the dataset once you save it. Say, you have a dataset of 1 GB.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

U-Next

AUGUST 3, 2022

Database Management: A Data Scientist has to have a solid understanding of data processing and data managerial staff, in addition to being skilled with machine learning and statistical models. They must organise, integrate, clean, and arrange a sizable amount of data to make it ready for future usage. Non-Technical Competencies.

Data Science 52

Data Science Retail Computer Science Entertainment 52