RandomTrees

NOVEMBER 29, 2023

Here the practice of data warehousing and warehouse system is very important and the use of right modelling techniques has become a very important factor in todays’ competitive world. In this choice, Big Data will play an important role and its choice is also inevitably crucial in the Business Intelligence and related systems.

Data Warehouse 52

Data Warehouse Data Lake Database-centric Data Cleanse 52

Knowledge Hut

JUNE 26, 2023

If you want to break into the field of data engineering but don't yet have any expertise in the field, compiling a portfolio of data engineering projects may help. Data pipeline best practices should be shown in these initiatives. Source: Use Stack Overflow Data for Analytic Purposes 4.

Data Engineering 98

Data Engineering Data Engineer Coding Project 98

Knowledge Hut

MAY 3, 2024

Spark Streaming Kafka Streams 1 Data received from live input data streams is Divided into Micro-batched for processing. processes per data stream(real real-time) 2 A separate processing Cluster is required No separate processing cluster is required. it's better for functions like row parsing, data cleansing, etc.

Kafka 98

Kafka Scala Java Amazon Web Services 98

ProjectPro

JANUARY 27, 2023

Top ETL Business Use Cases for Streamlining Data Management Data Quality - ETL tools can be used for data cleansing, validation, enriching, and standardization before loading the data into a destination like a data lake or data warehouse.

BI 52

BI ETL Tools Retail Healthcare 52

Knowledge Hut

JANUARY 30, 2024

Once stored in the destination repository, the data can undergo further transformations, such as data cleansing, feature engineering, statistical analysis, and machine learning. Utilizes structured data or datasets that may have already undergone extraction and preparation. Output Structured data ready for analysis.

ETL Tools 52

ETL Tools Database-centric Data Mining Data Cleanse 52

AltexSoft

AUGUST 29, 2023

In 2010, a transformative concept took root in the realm of data storage and analytics — a data lake. The term was coined by James Dixon , Back-End Java, Data, and Business Intelligence Engineer, and it started a new era in how organizations could store, manage, and analyze their data.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

AltexSoft

DECEMBER 23, 2022

It is a data integration process with which you first extract raw information (in its original formats) from various sources and load it straight into a central repository such as a cloud data warehouse , a data lake , or a data lakehouse where you transform it into suitable formats for further analysis and reporting.

Process 52

Process Building Raw Data Data Lake 52

Edureka

FEBRUARY 8, 2024

Introduction to AWS Instances Selecting the right AWS instance type is a critical decision that can significantly influence the success of your cloud-based applications and infrastructure. Instance types serve as virtual servers in the cloud, providing a combination of computing power, memory, storage, and networking capacity.

AWS 52

AWS NoSQL Deep Learning Datasets 52

AltexSoft

MAY 14, 2021

With the ETL approach, data transformation happens before it gets to a target repository like a data warehouse, whereas ELT makes it possible to transform data after it’s loaded into a target system. Data storage and processing. Data cleansing. Before getting thoroughly analyzed, data ?

Big Data 78

Big Data Data Analytics IT NoSQL 78

ProjectPro

AUGUST 24, 2021

This is an end-to-end big data project for building a data engineering pipeline involving data extraction, data cleansing, data transformation, exploratory analysis , data visualization, data modeling, and data flow orchestration of event data on the cloud.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

phData: Data Engineering

JULY 18, 2023

With the birth of cloud data warehouses, data applications, and generative AI , processing large volumes of data faster and cheaper is more approachable and desired than ever. First up, let’s dive into the foundation of every Modern Data Stack, a cloud-based data warehouse.

Data Warehouse 52

Data Warehouse Pipeline-centric Government Data 52

ProjectPro

DECEMBER 7, 2021

Kaggle : Kaggle, a Jupyter Notebooks cloud environment that may be modified, can also be used as a free portfolio of your work. You may showcase the results of any Kaggle data science competitions you've entered, as well as any data sets or code you've developed. jpeg, PDF, PowerPoint, Word, and others).

Portfolio 52

Portfolio Building Data Mining Data Analysis 52

ProjectPro

OCTOBER 20, 2021

The orchestration of pipelines can happen on various platforms but are generally integrated with cloud providers such as Microsoft Azure, Amazon Web Services , or Google Cloud Platform at an Enterprise Level. AI Interview Questions and Answers on AI Cloud Services 6) What is an API? 8) What Cloud Service would you prefer?

Machine Learning 52

Machine Learning Algorithm Government Data Science 52

ProjectPro

JANUARY 31, 2023

Map tasks deal with mapping and data splitting, whereas Reduce tasks shuffle and reduce data. Map Reduce programs in cloud computing are parallel, making them ideal for executing large-scale data processing across multiple machines in a cluster. When to use MapReduce with Big Data.

Big Data 52

Big Data Hadoop AWS Relational Database 52