Data Science Blog

MARCH 14, 2023

Datenqualität hingegen, wurde zum wichtigen Faktor jeder Unternehmensbewertung, was Themen wie Reporting, Data Governance und schließlich dann das Data Engineering mehr noch anschob als die Data Science. Google Trends – Big Data (blue), Data Science (red), Business Intelligence (yellow) und Process Mining (green).

Big Data 147

Big Data Big Data Apache Hadoop Data Science 147

Data Science Dojo

MAY 18, 2023

Data Storytelling in Action: This panel will discuss the importance of data visualization in storytelling in different industries, different visualization tools, tips on improving one’s visualization skills, personal experiences, breakthroughs, pressures, and frustrations as well as successes and failures.

Data Science 195

Data Science AI AI SQL 195

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

Diese Anwendungsfälle sind jedoch analytisch recht trivial und bereits mit einfacher BI (Business Intelligence) oder dedizierten Analysen ganz ohne Process Mining bereits viel schneller aufzuspüren. Oft bieten bereits ERP-Systeme eine eigene Erkennung hierfür an, die sich mit einfach gestrikter BI leicht erweitern lässt.

Data Warehouse 147

Data Warehouse Business Intelligence Business Intelligence Power BI 147

Analytics Vidhya

OCTOBER 6, 2023

In today’s rapidly evolving digital landscape, seamless data, applications, and device integration are more pressing than ever. Enter Microsoft Fabric, a cutting-edge solution designed to revolutionize how we interact with technology.

Analytics 343

Analytics Analytics Power BI Data Lakes 343

Dataconomy

JULY 24, 2023

” Data visualization and communication It’s not enough to uncover insights from data; a data scientist must also communicate these insights effectively. This is where data visualization comes in. Tools like Tableau, Matplotlib, Seaborn, or Power BI can be incredibly helpful.

Data Scientist 172

Data Scientist Data Science Data Analyst Machine Learning 172

IBM Journey to AI blog

SEPTEMBER 19, 2023

Data analytics is a task that resides under the data science umbrella and is done to query, interpret and visualize datasets. Data scientists will often perform data analysis tasks to understand a dataset or evaluate outcomes.

Data Science 94

Data Science Analytics Analytics Data Scientist 94

Alation

JANUARY 17, 2023

A typical modern data stack consists of the following: A data warehouse. Data ingestion/integration services. Data orchestration tools. Business intelligence (BI) platforms. How Did the Modern Data Stack Get Started? Business analysts. Data scientists. Software engineers.

Data Warehouse 52

Data Warehouse ETL Tableau Cloud Data 52

Data Science Blog

JULY 23, 2023

Companies use Business Intelligence (BI), Data Science , and Process Mining to leverage data for better decision-making, improve operational efficiency, and gain a competitive edge. Data Mesh on Azure Cloud with Databricks and Delta Lake for Applications of Business Intelligence, Data Science and Process Mining.

Data Science 246

Data Science Azure Power BI Business Intelligence 246

Mlearning.ai

MAY 3, 2023

I have Lead & Managed a team of data analysts, business analysts, data engineers, ML engineers, DevOps engineers, and Data Scientists. I have worked on several key strategic & data-monetization initiatives in the past.

Python 52

Python Natural Language Processing Data Scientist Citizen Data Scientist 52

Pickl AI

MARCH 19, 2025

Summary: Data engineering tools streamline data collection, storage, and processing. Tools like Python, SQL, Apache Spark, and Snowflake help engineers automate workflows and improve efficiency. Learning these tools is crucial for building scalable data pipelines. Thats where data engineering tools come in!

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52