Pickl AI

AUGUST 9, 2024

Data Warehousing Solutions Tools like Amazon Redshift, Google BigQuery, and Snowflake enable organisations to store and analyse large volumes of data efficiently. Students should learn about the architecture of data warehouses and how they differ from traditional databases.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 52

Pickl AI

JULY 25, 2023

Skills and Tools of Data Scientists To excel in the field of Data Science, professionals need a diverse skill set, including: Programming Languages: Python, R, SQL, etc. Machine Learning: Supervised and unsupervised learning techniques, deep learning, etc. Big Data Technologies: Hadoop, Spark, etc.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

Pickl AI

SEPTEMBER 5, 2024

Azure Synapse Analytics Previously known as Azure SQL Data Warehouse , Azure Synapse Analytics offers a limitless analytics service that combines big data and data warehousing. This service enables Data Scientists to query data on their terms using serverless or provisioned resources at scale.

Azure 52

Azure Data Scientist Data Science Machine Learning 52

Pickl AI

APRIL 26, 2024

Data Warehousing and ETL Processes What is a data warehouse, and why is it important? A data warehouse is a centralised repository that consolidates data from various sources for reporting and analysis. It is essential to provide a unified data view and enable business intelligence and analytics.

Data Analyst 52

Data Analyst Data Analysis Data Analysis Machine Learning 52

Data Science Blog

MARCH 30, 2023

Eine bessere Idee ist es daher, Event Logs nicht in einzelnen Process Mining Tools aufzubereiten, sondern zentral in einem dafür vorgesehenen Data Warehouse zu erstellen, zu katalogisieren und darüber auch die grundsätzliche Data Governance abzusichern. Dank AI werden damit noch viel verborgenere Prozesse sichtbar.

Data Warehouse 147

Data Warehouse Business Intelligence Business Intelligence Power BI 147