DataKitchen

SEPTEMBER 21, 2023

L1 is usually the raw, unprocessed data ingested directly from various sources; L2 is an intermediate layer featuring data that has undergone some form of transformation or cleaning; and L3 contains highly processed, optimized, and typically ready for analytics and decision-making processes. What is Data in Use?

Raw Data 67

Raw Data Data Business Intelligence High Quality Data 67

Cloudera

AUGUST 21, 2021

million customers worldwide, recognized how the immense volume of data they maintained could provide better insight into customers’ needs. Since leveraging Cloudera’s data platform, Rabobank has been able to improve its customers’ financial management. Rabobank , headquartered in the Netherlands with over 8.3

Banking 101

Banking Raw Data High Quality Data Business Intelligence 101

Knowledge Hut

JUNE 28, 2023

Data Sources Diverse and vast data sources, including structured, unstructured, and semi-structured data. Structured data from databases, data warehouses, and operational systems. Goal Extracting valuable information from raw data for predictive or descriptive purposes.

Data Mining 52

Data Mining Business Intelligence BI Datasets 52

Workfall

JULY 4, 2023

Reading Time: 8 minutes In the world of data engineering, a mighty tool called DBT (Data Build Tool) comes to the rescue of modern data workflows. Imagine a team of skilled data engineers on an exciting quest to transform raw data into a treasure trove of insights.

Data Warehouse 69

Data Warehouse SQL PostgreSQL Database 69

DataKitchen

JULY 27, 2023

Azure Databricks Delta Live Table s: These provide a more straightforward way to build and manage Data Pipelines for the latest, high-quality data in Delta Lake. Azure Blob Storage serves as the data lake to store raw data. Databricks Notebooks are often used in conjunction with Workflows.

Data Pipeline 52

Data Pipeline BI Machine Learning Data Preparation 52

Databand.ai

JULY 10, 2023

Observability platforms not only supply raw data but also offer actionable insights through visualizations, dashboards, and alerts. Databand allows data engineering and data science teams to define data quality rules, monitor data consistency, and identify data drift or anomalies.

Data Pipeline 52

Data Pipeline Algorithm Raw Data Aggregated Data 52

Knowledge Hut

JANUARY 25, 2024

Trustworthy Analytics: Reliable data supports accurate statistical analysis. Enhanced Visualization: Clean data leads to clearer data visualizations. Efficient Machine Learning: High-quality data is vital for training accurate ML models. What is the difference between data cleaning and data transformation?

Data Cleanse 52

Data Cleanse Datasets Data Preparation Data Science 52