Smart Data Collective

SEPTEMBER 23, 2020

The market for data warehouses is booming. While there is a lot of discussion about the merits of data warehouses, not enough discussion centers around data lakes. We talked about enterprise data warehouses in the past, so let’s contrast them with data lakes. Data Warehouse.

Data Lakes 135

Data Lakes Data Warehouse Big Data Big Data 135

Smart Data Collective

AUGUST 28, 2021

Data lakes and data warehouses are probably the two most widely used structures for storing data. Data Warehouses and Data Lakes in a Nutshell. A data warehouse is used as a central storage space for large amounts of structured data coming from various sources. Key Differences.

Data Lakes 140

Data Lakes Data Warehouse ETL Data Scientist 140

Pickl AI

AUGUST 9, 2024

Big Data Technologies and Tools A comprehensive syllabus should introduce students to the key technologies and tools used in Big Data analytics. Some of the most notable technologies include: Hadoop An open-source framework that allows for distributed storage and processing of large datasets across clusters of computers.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 52

IBM Journey to AI blog

JULY 6, 2023

Data from various sources, collected in different forms, require data entry and compilation. That can be made easier today with virtual data warehouses that have a centralized platform where data from different sources can be stored. One challenge in applying data science is to identify pertinent business issues.

Machine Learning 70

Machine Learning Machine Learning Data Science Big Data 70

Pickl AI

JULY 25, 2023

They create data pipelines, ETL processes, and databases to facilitate smooth data flow and storage. With expertise in programming languages like Python , Java , SQL, and knowledge of big data technologies like Hadoop and Spark, data engineers optimize pipelines for data scientists and analysts to access valuable insights efficiently.

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52

DagsHub

NOVEMBER 11, 2024

Creating multimodal embeddings means training models on datasets with multiple data types to understand how these types of information are related. Multimodal embeddings help combine unstructured data from various sources in data warehouses and ETL pipelines.

AI 52

AI AI Data Lakes Database 52

DagsHub

AUGUST 23, 2024

It provides visibility into data flows, offers various data quality checks (including custom rules), and inspects pipeline performance (job execution times, data volumes, and error rates). With this tool, you can implement and monitor data quality rules across different data sources.

Data Quality 52

Data Quality Data Governance Machine Learning Machine Learning 52