AltexSoft

DECEMBER 23, 2022

All available data is pulled from a particular data source. This process can involve extracting all rows and columns of data from a relational database, all records from a file, or all data from an API endpoint. Partial data extraction with update notifications. Full extraction. Aggregation.

Process 52

Process Building Raw Data Data Lake 52

Knowledge Hut

JANUARY 30, 2024

Whether it's aggregating customer interactions, analyzing historical sales trends, or processing real-time sensor data, data extraction initiates the process. Utilizes structured data or datasets that may have already undergone extraction and preparation. Primary Focus Structuring and preparing data for further analysis.

ETL Tools 52

ETL Tools Database-centric Data Mining Raw Data 52

AltexSoft

AUGUST 29, 2023

Data sources In a data lake architecture, the data journey starts at the source. Data sources can be broadly classified into three categories. Structured data sources. These are the most organized forms of data, often originating from relational databases and tables where the structure is clearly defined.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 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 Relational Database AWS 52

U-Next

OCTOBER 25, 2022

In a database, this programming data manipulation language is used to add, delete, and update information in a database by inserting, omitting, and updating the data. The data can easily be cleansed and mapped to be used for further analysis using this method. . Tips for Data Manipulation .

Business Intelligence 40

Business Intelligence Raw Data Data Cleanse Database 40

Knowledge Hut

NOVEMBER 28, 2023

Technical Data Engineer Skills 1.Python Python Python is one of the most looked upon and popular programming languages, using which data engineers can create integrations, data pipelines, integrations, automation, and data cleansing and analysis. ETL is central to getting your data where you need it.

Data Engineering 52

Data Engineering Data Engineer Engineering Generalist 52

phData: Data Engineering

AUGUST 4, 2023

Snowflake’s ‘staging area’ is a specific storage location where raw files are first loaded before they’re imported into the Snowflake database. Once the data is loaded into Snowflake, it can be further processed and transformed using SQL queries or other tools within the Snowflake environment.

Cloud Storage 52

Cloud Storage Google Cloud Amazon Web Services 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. In-Memory Caching- Memory-optimized instances are suitable for in-memory caching solutions, enhancing the speed of data access.

AWS 52

AWS NoSQL Deep Learning Machine Learning 52

ProjectPro

DECEMBER 7, 2021

The following is a list of the data analyst skills you'll need to learn if you’re willing to build an entry-level data analyst portfolio- 1) SQL The common language for communicating with databases is SQL or Structured Query Language. In reality, a technical screening using SQL is a regular part of data analyst interviews.

Portfolio 52

Portfolio Building Data Mining Data Science 52