phData

SEPTEMBER 14, 2023

One of the great things about Power BI is all of the native connectors that exist, making it extremely easy for developers to seamlessly connect to the source system and pull their data into Power BI. Check out this blog on how to enable SSO for Snowflake in Power BI.

Power BI 69

Power BI Data Governance Clustering Business Intelligence 69

Pickl AI

JANUARY 12, 2025

Moreover, regulatory requirements concerning data utilisation, like the EU’s General Data Protection Regulation GDPR, further complicate the situation. Such challenges can be mitigated by durable data governance, continuous training, and high commitment toward ethical standards.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence AI AI 52

Pickl AI

DECEMBER 2, 2024

Data lakes and cloud storage provide scalable solutions for large datasets. Processing frameworks like Hadoop enable efficient data analysis across clusters. Analytics tools help convert raw data into actionable insights for businesses. Strong data governance ensures accuracy, security, and compliance in data management.

Big Data 52

Big Data Big Data Data Lakes Apache Hadoop 52

Pickl AI

NOVEMBER 25, 2024

Data lakes and cloud storage provide scalable solutions for large datasets. Processing frameworks like Hadoop enable efficient data analysis across clusters. Analytics tools help convert raw data into actionable insights for businesses. Strong data governance ensures accuracy, security, and compliance in data management.

Big Data 52

Big Data Big Data Data Lakes Apache Hadoop 52

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

Pickl AI

APRIL 26, 2024

I would perform exploratory data analysis to understand the distribution of customer transactions and identify potential segments. Then, I would use clustering techniques such as k-means or hierarchical clustering to group customers based on similarities in their purchasing behaviour. What approach would you take?

Data Analyst 52

Data Analyst Data Analysis Data Analysis Machine Learning 52

Pickl AI

JULY 25, 2023

Model Development Data Scientists develop sophisticated machine-learning models to derive valuable insights and predictions from the data. These models may include regression, classification, clustering, and more. Data Quality and Governance Ensuring data quality is a critical aspect of a Data Engineer’s role.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52