ODSC - Open Data Science

SEPTEMBER 27, 2023

Cost-Efficiency By leveraging cost-effective storage solutions like the Hadoop Distributed File System (HDFS) or cloud-based storage, data lakes can handle large-scale data without incurring prohibitive costs. This is particularly advantageous when dealing with exponentially growing data volumes.

Data Lakes 98

Data Lakes Data Warehouse Database Big Data 98

Becoming Human

JANUARY 23, 2023

Just like this in Data Science we have Data Analysis , Business Intelligence , Databases , Machine Learning , Deep Learning , Computer Vision , NLP Models , Data Architecture , Cloud & many things, and the combination of these technologies is called Data Science.

Data Science 105

Data Science Big Data Big Data Deep Learning 105

Pickl AI

OCTOBER 10, 2024

Inconsistent or unstructured data can lead to faulty insights, so transformation helps standardise data, ensuring it aligns with the requirements of Analytics, Machine Learning , or Business Intelligence tools. AWS Glue AWS Glue is a fully managed ETL service provided by Amazon Web Services.

Data Quality 52

Data Quality AWS Machine Learning Machine Learning 52

Pickl AI

NOVEMBER 15, 2023

It involves the extraction, transformation, and loading (ETL) process to organize data for business intelligence purposes. Transactional databases, containing operational data generated by day-to-day business activities, feed into the Data Warehouse for analytical processing.

Data Lakes 52

Data Lakes Data Warehouse Database ETL 52

phData

FEBRUARY 25, 2025

Over the years, businesses have increasingly turned to Snowflake AI Data Cloud for various use cases beyond just data analytics and business intelligence. Datavolo is more than just an ETL toolit provides functionality for Reverse ETL as well, enabling organizations to push data from Snowflake into other systems.

Data Pipeline 52

Data Pipeline ETL Data Engineering Data Engineering 52

IBM Journey to AI blog

JANUARY 18, 2023

Towards the turn of millennium, enterprises started to realize that the reporting and business intelligence workload required a new solution rather than the transactional applications. This adds an additional ETL step, making the data even more stale. Data platform architecture has an interesting history. It was Datawarehouse.

Data Lakes 52

Data Lakes Data Warehouse Azure Apache Hadoop 52

DagsHub

NOVEMBER 11, 2024

These capture the semantic relationships between words, facilitating tasks like classification and clustering within ETL pipelines. Multimodal embeddings help combine unstructured data from various sources in data warehouses and ETL pipelines. The features extracted in the ETL process would then be inputted into the ML models.

AI 52

AI AI Data Lakes Database 52

Alation

FEBRUARY 20, 2020

Business Intelligence used to require months of effort from BI and ETL teams. More recently, we’ve seen Extract, Transform and Load (ETL) tools like Informatica and IBM Datastage disrupted by self-service data preparation tools. You used to be able to get those standards from your colleague in the BI/ETL team.

ETL 52

ETL Hadoop Tableau Data Scientist 52

Pickl AI

MARCH 19, 2025

It is commonly used for analytics and business intelligence, helping organisations make data-driven decisions. It allows businesses to store and analyse large datasets without worrying about infrastructure management. Looker : A business intelligence tool for data exploration and visualization.

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52