Dataconomy

MAY 10, 2023

This module enables businesses to leverage sophisticated data analysis tools and techniques to gain meaningful insights into their operations and drive informed decision-making. BIDW: What makes business intelligence and data warehouses inseparable?

Business Intelligence 178

Business Intelligence Business Intelligence Power BI Data Analysis 178

Dataconomy

MAY 26, 2025

Aggregation of data: Compiling relevant business data from various sources. Data cleansing and integration: Ensuring data quality through processes that contribute to a centralized data repository (data warehouse or data mart).

Analytics 91

Analytics Analytics Data Analysis Data Analysis 91

Pickl AI

MARCH 19, 2025

Learning these tools is crucial for building scalable data pipelines. offers Data Science courses covering these tools with a job guarantee for career growth. Introduction Imagine a world where data is a messy jungle, and we need smart tools to turn it into useful insights.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

Pickl AI

JULY 25, 2023

Together, data engineers, data scientists, and machine learning engineers form a cohesive team that drives innovation and success in data analytics and artificial intelligence. Their collective efforts are indispensable for organizations seeking to harness data’s full potential and achieve business growth.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

Alation

JANUARY 17, 2023

The modern data stack is a combination of various software tools used to collect, process, and store data on a well-integrated cloud-based data platform. It is known to have benefits in handling data due to its robustness, speed, and scalability. A typical modern data stack consists of the following: A data warehouse.

Data Warehouse 52

Data Warehouse ETL Tableau Cloud Data 52

Women in Big Data

DECEMBER 9, 2024

There is a plethora of BI tools available in the market today, with new ones being added yearly. Through a comparative analysis of some of the leading BI tools: Google Looker, Microsoft Power BI, Tableau and Qlik Sense, discover which BI solution best fits your organization’s data analytics needs to empower informed decision-making.

Big Data 52

Big Data Big Data Power BI Tableau 52

ODSC - Open Data Science

FEBRUARY 6, 2024

This open-source streaming platform enables the handling of high-throughput data feeds, ensuring that data pipelines are efficient, reliable, and capable of handling massive volumes of data in real-time. Each platform offers unique features and benefits, making it vital for data engineers to understand their differences.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

Pickl AI

SEPTEMBER 5, 2024

Summary: This blog provides a comprehensive roadmap for aspiring Azure Data Scientists, outlining the essential skills, certifications, and steps to build a successful career in Data Science using Microsoft Azure. Integration: Seamlessly integrates with popular Data Science tools and frameworks, such as TensorFlow and PyTorch.

Azure 52

Azure Data Scientist Data Science Machine Learning 52

Pickl AI

MAY 7, 2024

This newfound proficiency not only empowers them to become true data storytellers but also elevates their value within their organizations, placing them at the forefront of data-driven success. Here it is important to mention that Tableau for Data Science is eaully significant. This course prepares you for the future.

Data Analyst 52

Data Analyst Tableau Data Science Data Analysis 52

Pickl AI

AUGUST 11, 2024

Retail Sales In a retail data warehouse , the sales fact table might include metrics such as sales revenue, units sold, discounts applied, and profit margins. Web Analytics In a web analytics data warehouse, the page views fact table might include metrics such as total page views, unique visitors, session duration, and bounce rate.

Data Quality 52

Data Quality Data Warehouse Data Governance Analytics 52

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. js for creating interactive visualisations.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 52

Pickl AI

AUGUST 9, 2024

Real-world Examples To illustrate the practical applications of hierarchies in dimensional modelling, this section explores real-world examples across various industries, showcasing how hierarchies enhance data organisation, analysis, and decision-making.

Data Warehouse 52

Data Warehouse Data Quality ETL Business Intelligence 52

Pickl AI

OCTOBER 15, 2024

ETL (Extract, Transform, Load) is a core process in data integration that involves extracting data from various sources, transforming it into a usable format, and loading it into a target system, such as a data warehouse. ADF allows users to create complex ETL pipelines using a drag-and-drop interface.

ETL 52

ETL Azure AWS Data Governance 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

FEBRUARY 7, 2023

Für Data Science ja sowieso. Vor einen Jahrzehnt war es immer noch recht üblich, sich einfach ein BI Tool zu nehmen, sowas wie QlikView, Tableau oder PowerBI, mittlerweile gibt es ja noch einige mehr, und da direkt die Daten reinzuladen und dann halt loszulegen mit dem Aufbau der Reports. Es ist ein komplexes System.

Business Intelligence 286

Business Intelligence Business Intelligence Data Warehouse Data Lakes 286

Data Science Blog

JULY 20, 2024

Die Bedeutung effizienter und zuverlässiger Datenpipelines in den Bereichen Data Science und Data Engineering ist enorm. Es bietet vollständige Automatisierung des BI-Stacks und unterstützt ein breites Spektrum an Data Warehouses, analytischen Datenbanken und Frontends.

Azure 130

Azure SQL Power BI Data Lakes 130

Data Science Blog

SEPTEMBER 3, 2024

Dabei arbeiten wir technologie-offen und mit nahezu allen Tools – Und oft in enger Verbindung mit Initiativen der Business Intelligence und Data Science. Process Mining wurde kürzlich in die Power Automate Plattform und in Power BI integriert. – Fluxicon (Disco) ist vom Chart verschwunden.

Data Science 130

Data Science Power BI Azure Data Warehouse 130

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. appeared first on Data Science Blog.

Data Warehouse 147

Data Warehouse Business Intelligence Business Intelligence Power BI 147