Pickl AI

JULY 3, 2023

Here are steps you can follow to pursue a career as a BI Developer: Acquire a solid foundation in data and analytics: Start by building a strong understanding of data concepts, relational databases, SQL (Structured Query Language), and data modeling.

Business Intelligence 52

Business Intelligence Business Intelligence SQL Data Visualization 52

IBM Journey to AI blog

SEPTEMBER 19, 2023

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

Data Science 76

Data Science Analytics Analytics Data Scientist 76

Data Science Blog

NOVEMBER 15, 2023

The lower part of the iceberg is barely visible to the normal analyst on the tool interface, but is essential for implementation and success: this is the Event Log as the data basis for graph and data analysis in Process Mining. The creation of this data model requires the data connection to the source system (e.g.

Data Modeling 245

Data Modeling Data Models Business Intelligence Business Intelligence 245

Pickl AI

JUNE 12, 2023

A Data Scientist requires to be able to visualize quickly the data before creating the model and Tableau is helpful for that. Tableau is useful for summarising the metrics of success. Disadvantages of Tableau for Data Science However, apart from the advantages, Tableau for Data Science also has its own disadvantages.

Tableau 52

Tableau Data Science Data Scientist Data Analysis 52

Pickl AI

APRIL 2, 2024

There are three main types, each serving a distinct purpose: Descriptive Analytics (Business Intelligence): This focuses on understanding what happened. Think of it as summarizing past data to answer questions like “Which products are selling best?” ” or “What are our customer demographics?”

Data Science 52

Data Science Machine Learning Machine Learning Predictive Analytics 52