Knowledge Hut

APRIL 20, 2023

Data governance refers to the set of policies, procedures, mix of people and standards that organisations put in place to manage their data assets. It involves establishing a framework for data management that ensures data quality, privacy, security, and compliance with regulatory requirements.

Data Governance 59

Data Governance Government Data Cleanse Data Security 59

AltexSoft

AUGUST 29, 2023

Instead of relying on traditional hierarchical structures and predefined schemas, as in the case of data warehouses, a data lake utilizes a flat architecture. This structure is made efficient by data engineering practices that include object storage. Watch our video explaining how data engineering works.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

phData: Data Engineering

AUGUST 4, 2023

Snowflake hides user data objects and makes them accessible only through SQL queries through the compute layer. It handles the metadata related to these objects, access control configurations, and query optimization statistics. This includes tasks such as data cleansing, enrichment, and aggregation.

Cloud Storage 52

Cloud Storage Google Cloud Amazon Web Services Data Storage 52

phData: Data Engineering

JULY 18, 2023

Why Migrate to a Modern Data Stack? Better Transparency: There’s more clarity about where data is coming from, where it’s going, why it’s being transformed, and how it’s being used. These things limit the ability of these systems to keep up with the requirements of today’s data-driven business culture.

Data Warehouse 52

Data Warehouse Pipeline-centric Government Data 52

ProjectPro

AUGUST 24, 2021

This project is an opportunity for data enthusiasts to engage in the information produced and used by the New York City government. 18) GCP Project to Explore Cloud Functions The three popular cloud service providers in the market are Amazon Web Services, Microsoft Azure, and GCP.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

ProjectPro

OCTOBER 20, 2021

This would include the automation of a standard machine learning workflow which would include the steps of Gathering the data Preparing the Data Training Evaluation Testing Deployment and Prediction This includes the automation of tasks such as Hyperparameter Optimization, Model Selection, and Feature Selection.

Machine Learning 52

Machine Learning Algorithm Government Data Science 52