Knowledge Hut

NOVEMBER 3, 2023

MongoDB is used for data science, meaning that we utilize the capabilities of this NoSQL database system as part of our data analysis and data modeling processes, which fall under the realm of data science. There are several benefits to MongoDB for data science operations.

MongoDB 52

MongoDB Data Science NoSQL ETL Tools 52

Edureka

JULY 5, 2024

Tableau Prep has brought in a new perspective where novice IT users and power users who are not backward faithfully can use drag and drop interfaces, visual data preparation workflows, etc., simultaneously making raw data efficient to form insights. Validate data integrity at key stages to maintain accuracy throughout your flow.

Data Preparation 40

Data Preparation Process BI ETL Tools 40

ProjectPro

JANUARY 24, 2023

With over 20 pre-built connectors and 40 pre-built transformers, AWS Glue is an extract, transform, and load (ETL) service that is fully managed and allows users to easily process and import their data for analytics. You can leverage AWS Glue to discover, transform, and prepare your data for analytics.

AWS 52

AWS ETL Tools Data Lake Scala 52

AltexSoft

AUGUST 4, 2021

A data warehouse (DW) is a data repository that allows for storing and managing all the historical enterprise data, coming from disparate internal and external sources like CRMs, ERPs, flat files, etc. Initially, DWs dealt with structured data presented in tabular forms. Hybrid data marts.

Data Lake 64

Data Lake Data Warehouse ETL Tools Database 64

Edureka

JULY 16, 2024

Introduction Amazon Redshift, a cloud data warehouse service from Amazon Web Services (AWS), will directly query your structured and semi-structured data with SQL. While it offers robust data integration and analytical features, its cost-to-performance ratio depends on workload particulars.

AWS 40

AWS Data Warehouse Amazon Web Services Business Intelligence 40

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. In broader terms, two types of data -- structured and unstructured data -- flow through a data pipeline. Monitoring: It is a component that ensures data integrity.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

Edureka

FEBRUARY 7, 2023

It does away with the requirement to import data from an outside source. Use a few straightforward T-SQL queries to import data from Hadoop, Azure Blob Storage, or Azure Data Lake Store without having to install a third-party ETL tool. Export information to Azure Data Lake Store, Azure Blob Storage, or Hadoop.

Data Engineering 52

Data Engineering Data Engineer Engineering Hadoop 52

ProjectPro

SEPTEMBER 30, 2014

The conventional ETL software and server setup are plagued by problems related to scalability and cost overruns, which are ably addressed by Hadoop. If you encounter Big Data on a regular basis, the limitations of the traditional ETL tools in terms of storage, efficiency and cost is likely to force you to learn Hadoop.

Hadoop 52

Hadoop ETL Tools Unstructured Data ETL System 52

Edureka

JULY 4, 2024

It’s a Swiss Army knife for data pros, merging data integration, warehousing, and big data analytics into one sleek package. In other words, Synapse lets users ingest, prepare, manage, and serve data for immediate BI and machine learning needs. Is Azure Synapse an ETL tool? No worries.

Data Lake 40

Data Lake Pipeline-centric Data Warehouse ETL Tools 40

AltexSoft

MARCH 30, 2023

What is Databricks Databricks is an analytics platform with a unified set of tools for data engineering, data management , data science, and machine learning. It combines the best elements of a data warehouse, a centralized repository for structured data, and a data lake used to host large amounts of raw data.

Scala 64

Scala Data Lake BI Machine Learning 64