Knowledge Hut

OCTOBER 30, 2023

Data Transformation and ETL: Handle more complex data transformation and ETL (Extract, Transform, Load) processes, including handling data from multiple sources and dealing with complex data structures. Ensure compliance with data protection regulations. Identify and address bottlenecks and performance issues.

BI 52

BI Business Intelligence Data Cleanse Business Analyst 52

Databand.ai

JULY 19, 2023

ELT is commonly used in big data projects and real-time processing where speed and scalability are critical. In the past, data was often stored in a single location, such as a database or a data warehouse. This dispersed data environment creates a challenge for businesses that need to access and analyze their data.

Data Cleanse 52

Data Cleanse Raw Data Data Storage Data Warehouse 52

Knowledge Hut

APRIL 23, 2024

Cybersecurity and Fraud Detection: Big data analytics can identify suspicious activity, possible fraud, and cybersecurity concerns by examining blockchain data and trends. Large datasets are processed and stored using cost-effective methods, and organizations can extend their infrastructure as data quantities rise.

Big Data 52

Big Data Retail Recruitment Transportation 52

Databand.ai

AUGUST 30, 2023

Poor data quality can lead to incorrect or misleading insights, which can have significant consequences for an organization. DataOps tools help ensure data quality by providing features like data profiling, data validation, and data cleansing. Genie manages and allocates resources for big data jobs.

Data Cleanse 52

Data Cleanse Data Pipeline Data Ingestion Data Validation 52

RandomTrees

FEBRUARY 6, 2024

Over the years, the field of data engineering has seen significant changes and paradigm shifts driven by the phenomenal growth of data and by major technological advances such as cloud computing, data lakes, distributed computing, containerization, serverless computing, machine learning, graph database, etc.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

ProjectPro

FEBRUARY 8, 2023

ETL Developer Roles and Responsibilities Below are the roles and responsibilities of an ETL developer: Extracting data from various sources such as databases, flat files, and APIs. Data Warehousing Knowledge of data cubes, dimensional modeling, and data marts is required.

ETL Tools 52

ETL Tools Data Cleanse Data Warehouse Big Data 52

Precisely

JUNE 26, 2023

Forward-thinking businesses invest in digital transformation, cloud adoption, advanced analytics and predictive modeling, and supply chain resiliency. Successful organizations also developed intentional strategies for improving and maintaining data quality at scale using automated tools.

Data Integration 52

Data Integration Data Cleanse Data Governance Data Programming 52

Knowledge Hut

JANUARY 18, 2024

As data analytics professionals navigate this rapidly evolving landscape, they must adapt and develop new skills to stay relevant. Fortunately, short term Data Science courses can help you take the first step into this field and work your way upwards.

Data Analytics 52

Data Analytics Healthcare Machine Learning Algorithm 52

Towards Data Science

FEBRUARY 10, 2023

As we move firmly into the data cloud era, data leaders need metrics for the robustness and reliability of the machine–the data pipelines, systems, and engineers–just as much as the final (data) product it spits out. Where do we need to have data streaming vs batch? ETL vs ELT?

Data Pipeline 94

Data Pipeline Data Cleanse Data Machine Learning 94

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

ProjectPro

JANUARY 27, 2023

If you're wondering how the ETL process can drive your company to a new era of success, this blog will help you discover what use cases of ETL make it a critical component in many data management and analytic systems. Business Intelligence - ETL is a key component of BI systems for extracting and preparing data for analytics.

BI 52

BI ETL Tools Retail Healthcare 52

Monte Carlo

FEBRUARY 7, 2023

As we move firmly into the data cloud era, data leaders need metrics for the robustness and reliability of the machine–the data pipelines, systems, and engineers–just as much as the final (data) product it spits out. Where do we need to have data streaming vs batch ? ETL vs ELT ?

Management 72

Management Data Data Pipeline Data Cleanse 72

phData: Data Engineering

AUGUST 4, 2023

Data storage is a vital aspect of any Snowflake Data Cloud database. Within Snowflake, data can either be stored locally or accessed from other cloud storage systems. In Snowflake, there are three different storage layers available, Database, Stage, and Cloud Storage.

Cloud Storage 52

Cloud Storage Google Cloud Amazon Web Services Data Storage 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

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

Knowledge Hut

SEPTEMBER 26, 2023

By understanding how to cleanse, organize, and calculate data, you can ensure that your data is accurate and reliable. To understand further, let us look in detail at the advanced power BI skills required to prepare data and transform it into the right formats. before feeding it into the Power BI system.

BI 52

BI Business Intelligence Raw Data Data Analysis 52

AltexSoft

AUGUST 29, 2023

ELT choice: In data warehouses, Extract and Transform processes usually occur before data is loaded into the warehouse. Many organizations also deploy data marts , which are dedicated storage repositories for specific business lines or workgroups. After residing in the raw zone, data undergoes various transformations.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52